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data/retrieval_battle-dd51f1d2-bf9d-4e42-9a72-5b30dd2bd338.jsonl CHANGED
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  {"tstamp": 1722359624.4824, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "fdd19901cd4547e3815c9d79d5751118", "0_model_name": "BM25", "0_prompt": "How metadata is used with RAG", "0_output": [["How metadata is used with RAG", "Title: Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata\n\nAbstract: The retrieval-augmented generation (RAG) enables retrieval of relevant information from an external knowledge source and allows large language models (LLMs) to answer queries over previously unseen document collections. However, it was demonstrated that traditional RAG applications perform poorly in answering multi-hop questions, which require retrieving and reasoning over multiple elements of supporting evidence. We introduce a new method called Multi-Meta-RAG, which uses database filtering with LLM-extracted metadata to improve the RAG selection of the relevant documents from various sources, relevant to the question. While database filtering is specific to a set of questions from a particular domain and format, we found out that Multi-Meta-RAG greatly improves the results on the MultiHop-RAG benchmark. The code is available at https://github.com/mxpoliakov/Multi-Meta-RAG."]], "0_corpus": "arxiv", "1_conv_id": "c628bf57e2434ce999a71c814ebac2e8", "1_model_name": "embed-english-v3.0", "1_prompt": "How metadata is used with RAG", "1_output": [["How metadata is used with RAG", "Title: Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata\n\nAbstract: The retrieval-augmented generation (RAG) enables retrieval of relevant information from an external knowledge source and allows large language models (LLMs) to answer queries over previously unseen document collections. However, it was demonstrated that traditional RAG applications perform poorly in answering multi-hop questions, which require retrieving and reasoning over multiple elements of supporting evidence. We introduce a new method called Multi-Meta-RAG, which uses database filtering with LLM-extracted metadata to improve the RAG selection of the relevant documents from various sources, relevant to the question. While database filtering is specific to a set of questions from a particular domain and format, we found out that Multi-Meta-RAG greatly improves the results on the MultiHop-RAG benchmark. The code is available at https://github.com/mxpoliakov/Multi-Meta-RAG."]], "1_corpus": "arxiv"}
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  {"tstamp": 1722359625.838, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "cfd7524090934e63a83ff9284cc4d54c", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "0_output": [["Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "Title: StructCoder: Structure-Aware Transformer for Code Generation\n\nAbstract: There has been a recent surge of interest in automating software engineering tasks using deep learning. This paper addresses the problem of code generation, where the goal is to generate target code given source code in a different language or a natural language description. Most state-of-the-art deep learning models for code generation use training strategies primarily designed for natural language. However, understanding and generating code requires a more rigorous comprehension of the code syntax and semantics. With this motivation, we develop an encoder-decoder Transformer model where both the encoder and decoder are explicitly trained to recognize the syntax and data flow in the source and target codes, respectively. We not only make the encoder structure-aware by leveraging the source code's syntax tree and data flow graph, but we also support the decoder in preserving the syntax and data flow of the target code by introducing two novel auxiliary tasks: AST (Abstract Syntax Tree) paths prediction and data flow prediction. To the best of our knowledge, this is the first work to introduce a structure-aware Transformer decoder that models both syntax and data flow to enhance the quality of generated code. The proposed StructCoder model achieves state-of-the-art performance on code translation and text-to-code generation tasks in the CodeXGLUE benchmark, and improves over baselines of similar size on the APPS code generation benchmark. Our code is publicly available at https://github.com/reddy-lab-code-research/StructCoder/."]], "0_corpus": "arxiv", "1_conv_id": "1e72b400d20445c1a5f905e301166625", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "1_output": [["Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "Title: Empirical Study of Transformers for Source Code\n\nAbstract: Initially developed for natural language processing (NLP), Transformers are now widely used for source code processing, due to the format similarity between source code and text. In contrast to natural language, source code is strictly structured, i.e., it follows the syntax of the programming language. Several recent works develop Transformer modifications for capturing syntactic information in source code. The drawback of these works is that they do not compare to each other and consider different tasks. In this work, we conduct a thorough empirical study of the capabilities of Transformers to utilize syntactic information in different tasks. We consider three tasks (code completion, function naming and bug fixing) and re-implement different syntax-capturing modifications in a unified framework. We show that Transformers are able to make meaningful predictions based purely on syntactic information and underline the best practices of taking the syntactic information into account for improving the performance of the model."]], "1_corpus": "arxiv"}
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  {"tstamp": 1722360183.5049, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "8e4d32f5269142e68ec26538741715ea", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "Why is the sky blue?", "0_output": [["Why is the sky blue?", "Sky\n\nEtymology The word sky comes from the Old Norse , meaning 'cloud, abode of God'. The Norse term is also the source of the Old English , which shares the same Indo-European base as the classical Latin , meaning 'obscure'.\nIn Old English, the term heaven was used to describe the observable expanse above the earth. During the period of Middle English, \"heaven\" began shifting toward its current, religious meaning.\nDuring daytime\nExcept for direct sunlight, most of the light in the daytime sky is caused by scattering, which is dominated by a small-particle limit called Rayleigh scattering. The scattering due to molecule-sized particles (as in air) is greater in the directions both toward and away from the source of light than it is in directions perpendicular to the incident path. Scattering is significant for light at all visible wavelengths, but is stronger at the shorter (bluer) end of the visible spectrum, meaning that the scattered light is bluer than its source: the Sun. The remaining direct sunlight, having lost some of its shorter-wavelength components, appears slightly less blue.\nScattering also occurs even more strongly in clouds. Individual water droplets refract white light into a set of colored rings. If a cloud is thick enough, scattering from multiple water droplets will wash out the set of colored rings and create a washed-out white color."]], "0_corpus": "wikipedia", "1_conv_id": "00cd735a722943bca9ff50386cee6ee3", "1_model_name": "Salesforce/SFR-Embedding-2_R", "1_prompt": "Why is the sky blue?", "1_output": [["Why is the sky blue?", "Rayleigh scattering\n\nRayleigh scattering ( ), named after the 19th-century British physicist Lord Rayleigh (John William Strutt), is the predominantly elastic scattering of light, or other electromagnetic radiation, by particles with a size much smaller than the wavelength of the radiation. For light frequencies well below the resonance frequency of the scattering medium (normal dispersion regime), the amount of scattering is inversely proportional to the fourth power of the wavelength, e.g., a blue color is scattered much more than a red color as light propagates through air.\nRayleigh scattering results from the electric polarizability of the particles. The oscillating electric field of a light wave acts on the charges within a particle, causing them to move at the same frequency. The particle, therefore, becomes a small radiating dipole whose radiation we see as scattered light. The particles may be individual atoms or molecules; it can occur when light travels through transparent solids and liquids, but is most prominently seen in gases.\nRayleigh scattering of sunlight in Earth's atmosphere causes diffuse sky radiation, which is the reason for the blue color of the daytime and twilight sky, as well as the yellowish to reddish hue of the low Sun. Sunlight is also subject to Raman scattering, which changes the rotational state of the molecules and gives rise to polarization effects."]], "1_corpus": "wikipedia"}
 
 
 
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  {"tstamp": 1722359624.4824, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "fdd19901cd4547e3815c9d79d5751118", "0_model_name": "BM25", "0_prompt": "How metadata is used with RAG", "0_output": [["How metadata is used with RAG", "Title: Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata\n\nAbstract: The retrieval-augmented generation (RAG) enables retrieval of relevant information from an external knowledge source and allows large language models (LLMs) to answer queries over previously unseen document collections. However, it was demonstrated that traditional RAG applications perform poorly in answering multi-hop questions, which require retrieving and reasoning over multiple elements of supporting evidence. We introduce a new method called Multi-Meta-RAG, which uses database filtering with LLM-extracted metadata to improve the RAG selection of the relevant documents from various sources, relevant to the question. While database filtering is specific to a set of questions from a particular domain and format, we found out that Multi-Meta-RAG greatly improves the results on the MultiHop-RAG benchmark. The code is available at https://github.com/mxpoliakov/Multi-Meta-RAG."]], "0_corpus": "arxiv", "1_conv_id": "c628bf57e2434ce999a71c814ebac2e8", "1_model_name": "embed-english-v3.0", "1_prompt": "How metadata is used with RAG", "1_output": [["How metadata is used with RAG", "Title: Multi-Meta-RAG: Improving RAG for Multi-Hop Queries using Database Filtering with LLM-Extracted Metadata\n\nAbstract: The retrieval-augmented generation (RAG) enables retrieval of relevant information from an external knowledge source and allows large language models (LLMs) to answer queries over previously unseen document collections. However, it was demonstrated that traditional RAG applications perform poorly in answering multi-hop questions, which require retrieving and reasoning over multiple elements of supporting evidence. We introduce a new method called Multi-Meta-RAG, which uses database filtering with LLM-extracted metadata to improve the RAG selection of the relevant documents from various sources, relevant to the question. While database filtering is specific to a set of questions from a particular domain and format, we found out that Multi-Meta-RAG greatly improves the results on the MultiHop-RAG benchmark. The code is available at https://github.com/mxpoliakov/Multi-Meta-RAG."]], "1_corpus": "arxiv"}
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  {"tstamp": 1722359625.838, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "cfd7524090934e63a83ff9284cc4d54c", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "0_output": [["Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "Title: StructCoder: Structure-Aware Transformer for Code Generation\n\nAbstract: There has been a recent surge of interest in automating software engineering tasks using deep learning. This paper addresses the problem of code generation, where the goal is to generate target code given source code in a different language or a natural language description. Most state-of-the-art deep learning models for code generation use training strategies primarily designed for natural language. However, understanding and generating code requires a more rigorous comprehension of the code syntax and semantics. With this motivation, we develop an encoder-decoder Transformer model where both the encoder and decoder are explicitly trained to recognize the syntax and data flow in the source and target codes, respectively. We not only make the encoder structure-aware by leveraging the source code's syntax tree and data flow graph, but we also support the decoder in preserving the syntax and data flow of the target code by introducing two novel auxiliary tasks: AST (Abstract Syntax Tree) paths prediction and data flow prediction. To the best of our knowledge, this is the first work to introduce a structure-aware Transformer decoder that models both syntax and data flow to enhance the quality of generated code. The proposed StructCoder model achieves state-of-the-art performance on code translation and text-to-code generation tasks in the CodeXGLUE benchmark, and improves over baselines of similar size on the APPS code generation benchmark. Our code is publicly available at https://github.com/reddy-lab-code-research/StructCoder/."]], "0_corpus": "arxiv", "1_conv_id": "1e72b400d20445c1a5f905e301166625", "1_model_name": "BAAI/bge-large-en-v1.5", "1_prompt": "Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "1_output": [["Paper that improves code prediction accuracy using a syntactically-aware Transformer model.", "Title: Empirical Study of Transformers for Source Code\n\nAbstract: Initially developed for natural language processing (NLP), Transformers are now widely used for source code processing, due to the format similarity between source code and text. In contrast to natural language, source code is strictly structured, i.e., it follows the syntax of the programming language. Several recent works develop Transformer modifications for capturing syntactic information in source code. The drawback of these works is that they do not compare to each other and consider different tasks. In this work, we conduct a thorough empirical study of the capabilities of Transformers to utilize syntactic information in different tasks. We consider three tasks (code completion, function naming and bug fixing) and re-implement different syntax-capturing modifications in a unified framework. We show that Transformers are able to make meaningful predictions based purely on syntactic information and underline the best practices of taking the syntactic information into account for improving the performance of the model."]], "1_corpus": "arxiv"}
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  {"tstamp": 1722360183.5049, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "8e4d32f5269142e68ec26538741715ea", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "Why is the sky blue?", "0_output": [["Why is the sky blue?", "Sky\n\nEtymology The word sky comes from the Old Norse , meaning 'cloud, abode of God'. The Norse term is also the source of the Old English , which shares the same Indo-European base as the classical Latin , meaning 'obscure'.\nIn Old English, the term heaven was used to describe the observable expanse above the earth. During the period of Middle English, \"heaven\" began shifting toward its current, religious meaning.\nDuring daytime\nExcept for direct sunlight, most of the light in the daytime sky is caused by scattering, which is dominated by a small-particle limit called Rayleigh scattering. The scattering due to molecule-sized particles (as in air) is greater in the directions both toward and away from the source of light than it is in directions perpendicular to the incident path. Scattering is significant for light at all visible wavelengths, but is stronger at the shorter (bluer) end of the visible spectrum, meaning that the scattered light is bluer than its source: the Sun. The remaining direct sunlight, having lost some of its shorter-wavelength components, appears slightly less blue.\nScattering also occurs even more strongly in clouds. Individual water droplets refract white light into a set of colored rings. If a cloud is thick enough, scattering from multiple water droplets will wash out the set of colored rings and create a washed-out white color."]], "0_corpus": "wikipedia", "1_conv_id": "00cd735a722943bca9ff50386cee6ee3", "1_model_name": "Salesforce/SFR-Embedding-2_R", "1_prompt": "Why is the sky blue?", "1_output": [["Why is the sky blue?", "Rayleigh scattering\n\nRayleigh scattering ( ), named after the 19th-century British physicist Lord Rayleigh (John William Strutt), is the predominantly elastic scattering of light, or other electromagnetic radiation, by particles with a size much smaller than the wavelength of the radiation. For light frequencies well below the resonance frequency of the scattering medium (normal dispersion regime), the amount of scattering is inversely proportional to the fourth power of the wavelength, e.g., a blue color is scattered much more than a red color as light propagates through air.\nRayleigh scattering results from the electric polarizability of the particles. The oscillating electric field of a light wave acts on the charges within a particle, causing them to move at the same frequency. The particle, therefore, becomes a small radiating dipole whose radiation we see as scattered light. The particles may be individual atoms or molecules; it can occur when light travels through transparent solids and liquids, but is most prominently seen in gases.\nRayleigh scattering of sunlight in Earth's atmosphere causes diffuse sky radiation, which is the reason for the blue color of the daytime and twilight sky, as well as the yellowish to reddish hue of the low Sun. Sunlight is also subject to Raman scattering, which changes the rotational state of the molecules and gives rise to polarization effects."]], "1_corpus": "wikipedia"}
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+ {"tstamp": 1722360252.5966, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "1b169b7653ab4c8091ecb4bf186579e2", "0_model_name": "embed-english-v3.0", "0_prompt": "Are there grass or fiber eating birds?", "0_output": [["Are there grass or fiber eating birds?", "Bird\n\nDiet and feeding are varied and often include nectar, fruit, plants, seeds, carrion, and various small animals, including other birds. The digestive system of birds is unique, with a crop for storage and a gizzard that contains swallowed stones for grinding food to compensate for the lack of teeth. Some species such as pigeons and some psittacine species do not have a gallbladder. Most birds are highly adapted for rapid digestion to aid with flight. Some migratory birds have adapted to use protein stored in many parts of their bodies, including protein from the intestines, as additional energy during migration.\nBirds that employ many strategies to obtain food or feed on a variety of food items are called generalists, while others that concentrate time and effort on specific food items or have a single strategy to obtain food are considered specialists. Avian foraging strategies can vary widely by species. Many birds glean for insects, invertebrates, fruit, or seeds. Some hunt insects by suddenly attacking from a branch. Those species that seek pest insects are considered beneficial 'biological control agents' and their presence encouraged in biological pest control programmes. Combined, insectivorous birds eat 400–500 million metric tons of arthropods annually.\nNectar feeders such as hummingbirds, sunbirds, lories, and lorikeets amongst others have specially adapted brushy tongues and in many cases bills designed to fit co-adapted flowers. Kiwis and shorebirds with long bills probe for invertebrates; shorebirds' varied bill lengths and feeding methods result in the separation of ecological niches. Loons, diving ducks, penguins and auks pursue their prey underwater, using their wings or feet for propulsion, while aerial predators such as sulids, kingfishers and terns plunge dive after their prey. Flamingos, three species of prion, and some ducks are filter feeders. Geese and dabbling ducks are primarily grazers."]], "0_corpus": "wikipedia", "1_conv_id": "bf7123c3bf574070873b3438c66a7145", "1_model_name": "mixedbread-ai/mxbai-embed-large-v1", "1_prompt": "Are there grass or fiber eating birds?", "1_output": [["Are there grass or fiber eating birds?", "Bird\n\nDiet and feeding are varied and often include nectar, fruit, plants, seeds, carrion, and various small animals, including other birds. The digestive system of birds is unique, with a crop for storage and a gizzard that contains swallowed stones for grinding food to compensate for the lack of teeth. Some species such as pigeons and some psittacine species do not have a gallbladder. Most birds are highly adapted for rapid digestion to aid with flight. Some migratory birds have adapted to use protein stored in many parts of their bodies, including protein from the intestines, as additional energy during migration.\nBirds that employ many strategies to obtain food or feed on a variety of food items are called generalists, while others that concentrate time and effort on specific food items or have a single strategy to obtain food are considered specialists. Avian foraging strategies can vary widely by species. Many birds glean for insects, invertebrates, fruit, or seeds. Some hunt insects by suddenly attacking from a branch. Those species that seek pest insects are considered beneficial 'biological control agents' and their presence encouraged in biological pest control programmes. Combined, insectivorous birds eat 400–500 million metric tons of arthropods annually.\nNectar feeders such as hummingbirds, sunbirds, lories, and lorikeets amongst others have specially adapted brushy tongues and in many cases bills designed to fit co-adapted flowers. Kiwis and shorebirds with long bills probe for invertebrates; shorebirds' varied bill lengths and feeding methods result in the separation of ecological niches. Loons, diving ducks, penguins and auks pursue their prey underwater, using their wings or feet for propulsion, while aerial predators such as sulids, kingfishers and terns plunge dive after their prey. Flamingos, three species of prion, and some ducks are filter feeders. Geese and dabbling ducks are primarily grazers."]], "1_corpus": "wikipedia"}
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+ {"tstamp": 1722360320.5742, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "b454985e65da4a54967a4a82ac91170c", "0_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "0_prompt": "Can plants get cancer?", "0_output": [["Can plants get cancer?", "Blue agave\n\nTequila production Tequila is made only from a specific cultivar of Agave tequilana called 'Weber Azul'. The plant is from the Asparagaceae family. This cultivar is larger and blue-gray in color compared to the smaller and green normal A. tequilana. It is a rapid grower and prolific offsetter in keeping with its agricultural advantages. Tequila is produced by removing the heart (piña) of the plant in its seventh to fourteenth year (depending on growth rate and whims of harvester). Harvested piñas normally weigh . This heart is stripped of its leaves and heated to convert the inulin to sugars. Then the roasted core is pressed or crushed to release the sugary clear liquid called aguamiel, which is, in turn, fermented and distilled into alcohol. Tequila is also made with a sugar formulation of 51% agave and 49% other sugars. These tequilas are referred to as Mixtos.\nPathogens affecting the plant\nAs agave production has moved to an industrial scale since the end of the 1980s, diseases and pests, collectively referred to as TMA (tristeza y muerte de agave, \"wilting and death of agave\"), have hit the crops. Through the 1990s, diseases spread, particularly Fusarium fungi and Erwinia bacteria, exacerbated by the low genetic diversity of the agave plants. Other problems include the agave weevil, Scyphophorus acupunctatus, and a fungus, Thielaviopsis paradoxa.\nAccording to a 2004 study, additional pathogens, Erwinia carotovora, Enterobacter agglomerans, Pseudomonas mendocina, and Serratia spp. are responsible for continued rot."]], "0_corpus": "wikipedia", "1_conv_id": "8e0a2106198b416899abf77d45576c31", "1_model_name": "voyage-multilingual-2", "1_prompt": "Can plants get cancer?", "1_output": [["Can plants get cancer?", "List of unproven and disproven cancer treatments\n\nVenus flytrap – a carnivorous plant, the extract of which is promoted as a treatment for a variety of human ailments including skin cancer. According to the American Cancer Society, \"available scientific evidence does not support claims that extract from the Venus flytrap plant is effective in treating skin cancer or any other type of cancer\".\nWalnuts – large, hard edible seeds of any tree of the genus Juglans. Black walnut has been promoted as a cancer cure on the basis it kills a \"parasite\" responsible for the disease. However, according to the American Cancer Society, \"available scientific evidence does not support claims that hulls from black walnuts remove parasites from the intestinal tract or that they are effective in treating cancer or any other disease\".\nWheatgrass – a food made from grains of wheat. According to the American Cancer Society, although some wheatgrass champions claim it can \"shrink\" cancer tumors, \"available scientific evidence does not support the idea that wheatgrass or the wheatgrass diet can cure or prevent disease\".\nWild yam (or Chinese yam) – types of yam, the roots of which are made into creams and dietary supplements that are promoted for a variety of medicinal purposes, including cancer prevention. The American Cancer Society says of these products, \"available scientific evidence does not support claims that they are safe or effective.\""]], "1_corpus": "wikipedia"}
data/retrieval_individual-dd51f1d2-bf9d-4e42-9a72-5b30dd2bd338.jsonl CHANGED
@@ -79,3 +79,7 @@
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  {"tstamp": 1722359684.706, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722359682.4835, "finish": 1722359684.706, "ip": "", "conv_id": "51b8e76eb6d04e54b622603ec5dec06a", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "In English when to use –, — vs -?", "output": [["In English when to use –, — vs -?", "English Stackexchange\n\nQ: When to use -, – and —? \nPossible Duplicate:\nWhen should I use an em-dash, an en-dash, and a hyphen? \n\nThis is about hyphens (-), en-dashes (–) and em-dashes (—).\nWhen to use which one? To be honest, I always use em-dashes unless I join words with a hyphen, but I never use an en-dash.\n\nA: Hyphens are used in compound modifiers.\n\n\n*\n\n*a well-trained professional\n\n*over-the-counter drugs\n\n\nEn dashes are used in place of \"to\" to connect numbers or words.\n\n\n*\n\n*The London–Amsterdam flight is delayed.\n\n*The meeting is from 3:00–4:30 p.m.\n\n\nEm dashes help set off amplifying or explanatory statements.\n\n\n*\n\n*The vampire—it had been awake half the night—flew out of its coffin.\n\n"]], "corpus": "stackexchange"}
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  {"tstamp": 1722360172.406, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722360170.2383, "finish": 1722360172.406, "ip": "", "conv_id": "8e4d32f5269142e68ec26538741715ea", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Why is the sky blue?", "output": [["Why is the sky blue?", "Sky\n\nEtymology The word sky comes from the Old Norse , meaning 'cloud, abode of God'. The Norse term is also the source of the Old English , which shares the same Indo-European base as the classical Latin , meaning 'obscure'.\nIn Old English, the term heaven was used to describe the observable expanse above the earth. During the period of Middle English, \"heaven\" began shifting toward its current, religious meaning.\nDuring daytime\nExcept for direct sunlight, most of the light in the daytime sky is caused by scattering, which is dominated by a small-particle limit called Rayleigh scattering. The scattering due to molecule-sized particles (as in air) is greater in the directions both toward and away from the source of light than it is in directions perpendicular to the incident path. Scattering is significant for light at all visible wavelengths, but is stronger at the shorter (bluer) end of the visible spectrum, meaning that the scattered light is bluer than its source: the Sun. The remaining direct sunlight, having lost some of its shorter-wavelength components, appears slightly less blue.\nScattering also occurs even more strongly in clouds. Individual water droplets refract white light into a set of colored rings. If a cloud is thick enough, scattering from multiple water droplets will wash out the set of colored rings and create a washed-out white color."]], "corpus": "wikipedia"}
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  {"tstamp": 1722360172.406, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722360170.2383, "finish": 1722360172.406, "ip": "", "conv_id": "00cd735a722943bca9ff50386cee6ee3", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Why is the sky blue?", "output": [["Why is the sky blue?", "Rayleigh scattering\n\nRayleigh scattering ( ), named after the 19th-century British physicist Lord Rayleigh (John William Strutt), is the predominantly elastic scattering of light, or other electromagnetic radiation, by particles with a size much smaller than the wavelength of the radiation. For light frequencies well below the resonance frequency of the scattering medium (normal dispersion regime), the amount of scattering is inversely proportional to the fourth power of the wavelength, e.g., a blue color is scattered much more than a red color as light propagates through air.\nRayleigh scattering results from the electric polarizability of the particles. The oscillating electric field of a light wave acts on the charges within a particle, causing them to move at the same frequency. The particle, therefore, becomes a small radiating dipole whose radiation we see as scattered light. The particles may be individual atoms or molecules; it can occur when light travels through transparent solids and liquids, but is most prominently seen in gases.\nRayleigh scattering of sunlight in Earth's atmosphere causes diffuse sky radiation, which is the reason for the blue color of the daytime and twilight sky, as well as the yellowish to reddish hue of the low Sun. Sunlight is also subject to Raman scattering, which changes the rotational state of the molecules and gives rise to polarization effects."]], "corpus": "wikipedia"}
 
 
 
 
 
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  {"tstamp": 1722359684.706, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722359682.4835, "finish": 1722359684.706, "ip": "", "conv_id": "51b8e76eb6d04e54b622603ec5dec06a", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "In English when to use –, — vs -?", "output": [["In English when to use –, — vs -?", "English Stackexchange\n\nQ: When to use -, – and —? \nPossible Duplicate:\nWhen should I use an em-dash, an en-dash, and a hyphen? \n\nThis is about hyphens (-), en-dashes (–) and em-dashes (—).\nWhen to use which one? To be honest, I always use em-dashes unless I join words with a hyphen, but I never use an en-dash.\n\nA: Hyphens are used in compound modifiers.\n\n\n*\n\n*a well-trained professional\n\n*over-the-counter drugs\n\n\nEn dashes are used in place of \"to\" to connect numbers or words.\n\n\n*\n\n*The London–Amsterdam flight is delayed.\n\n*The meeting is from 3:00–4:30 p.m.\n\n\nEm dashes help set off amplifying or explanatory statements.\n\n\n*\n\n*The vampire—it had been awake half the night—flew out of its coffin.\n\n"]], "corpus": "stackexchange"}
80
  {"tstamp": 1722360172.406, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722360170.2383, "finish": 1722360172.406, "ip": "", "conv_id": "8e4d32f5269142e68ec26538741715ea", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Why is the sky blue?", "output": [["Why is the sky blue?", "Sky\n\nEtymology The word sky comes from the Old Norse , meaning 'cloud, abode of God'. The Norse term is also the source of the Old English , which shares the same Indo-European base as the classical Latin , meaning 'obscure'.\nIn Old English, the term heaven was used to describe the observable expanse above the earth. During the period of Middle English, \"heaven\" began shifting toward its current, religious meaning.\nDuring daytime\nExcept for direct sunlight, most of the light in the daytime sky is caused by scattering, which is dominated by a small-particle limit called Rayleigh scattering. The scattering due to molecule-sized particles (as in air) is greater in the directions both toward and away from the source of light than it is in directions perpendicular to the incident path. Scattering is significant for light at all visible wavelengths, but is stronger at the shorter (bluer) end of the visible spectrum, meaning that the scattered light is bluer than its source: the Sun. The remaining direct sunlight, having lost some of its shorter-wavelength components, appears slightly less blue.\nScattering also occurs even more strongly in clouds. Individual water droplets refract white light into a set of colored rings. If a cloud is thick enough, scattering from multiple water droplets will wash out the set of colored rings and create a washed-out white color."]], "corpus": "wikipedia"}
81
  {"tstamp": 1722360172.406, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1722360170.2383, "finish": 1722360172.406, "ip": "", "conv_id": "00cd735a722943bca9ff50386cee6ee3", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "Why is the sky blue?", "output": [["Why is the sky blue?", "Rayleigh scattering\n\nRayleigh scattering ( ), named after the 19th-century British physicist Lord Rayleigh (John William Strutt), is the predominantly elastic scattering of light, or other electromagnetic radiation, by particles with a size much smaller than the wavelength of the radiation. For light frequencies well below the resonance frequency of the scattering medium (normal dispersion regime), the amount of scattering is inversely proportional to the fourth power of the wavelength, e.g., a blue color is scattered much more than a red color as light propagates through air.\nRayleigh scattering results from the electric polarizability of the particles. The oscillating electric field of a light wave acts on the charges within a particle, causing them to move at the same frequency. The particle, therefore, becomes a small radiating dipole whose radiation we see as scattered light. The particles may be individual atoms or molecules; it can occur when light travels through transparent solids and liquids, but is most prominently seen in gases.\nRayleigh scattering of sunlight in Earth's atmosphere causes diffuse sky radiation, which is the reason for the blue color of the daytime and twilight sky, as well as the yellowish to reddish hue of the low Sun. Sunlight is also subject to Raman scattering, which changes the rotational state of the molecules and gives rise to polarization effects."]], "corpus": "wikipedia"}
82
+ {"tstamp": 1722360238.9071, "task_type": "retrieval", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722360238.5622, "finish": 1722360238.9071, "ip": "", "conv_id": "1b169b7653ab4c8091ecb4bf186579e2", "model_name": "embed-english-v3.0", "prompt": "Are there grass or fiber eating birds?", "output": [["Are there grass or fiber eating birds?", "Bird\n\nDiet and feeding are varied and often include nectar, fruit, plants, seeds, carrion, and various small animals, including other birds. The digestive system of birds is unique, with a crop for storage and a gizzard that contains swallowed stones for grinding food to compensate for the lack of teeth. Some species such as pigeons and some psittacine species do not have a gallbladder. Most birds are highly adapted for rapid digestion to aid with flight. Some migratory birds have adapted to use protein stored in many parts of their bodies, including protein from the intestines, as additional energy during migration.\nBirds that employ many strategies to obtain food or feed on a variety of food items are called generalists, while others that concentrate time and effort on specific food items or have a single strategy to obtain food are considered specialists. Avian foraging strategies can vary widely by species. Many birds glean for insects, invertebrates, fruit, or seeds. Some hunt insects by suddenly attacking from a branch. Those species that seek pest insects are considered beneficial 'biological control agents' and their presence encouraged in biological pest control programmes. Combined, insectivorous birds eat 400–500 million metric tons of arthropods annually.\nNectar feeders such as hummingbirds, sunbirds, lories, and lorikeets amongst others have specially adapted brushy tongues and in many cases bills designed to fit co-adapted flowers. Kiwis and shorebirds with long bills probe for invertebrates; shorebirds' varied bill lengths and feeding methods result in the separation of ecological niches. Loons, diving ducks, penguins and auks pursue their prey underwater, using their wings or feet for propulsion, while aerial predators such as sulids, kingfishers and terns plunge dive after their prey. Flamingos, three species of prion, and some ducks are filter feeders. Geese and dabbling ducks are primarily grazers."]], "corpus": "wikipedia"}
83
+ {"tstamp": 1722360238.9071, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722360238.5622, "finish": 1722360238.9071, "ip": "", "conv_id": "bf7123c3bf574070873b3438c66a7145", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "Are there grass or fiber eating birds?", "output": [["Are there grass or fiber eating birds?", "Bird\n\nDiet and feeding are varied and often include nectar, fruit, plants, seeds, carrion, and various small animals, including other birds. The digestive system of birds is unique, with a crop for storage and a gizzard that contains swallowed stones for grinding food to compensate for the lack of teeth. Some species such as pigeons and some psittacine species do not have a gallbladder. Most birds are highly adapted for rapid digestion to aid with flight. Some migratory birds have adapted to use protein stored in many parts of their bodies, including protein from the intestines, as additional energy during migration.\nBirds that employ many strategies to obtain food or feed on a variety of food items are called generalists, while others that concentrate time and effort on specific food items or have a single strategy to obtain food are considered specialists. Avian foraging strategies can vary widely by species. Many birds glean for insects, invertebrates, fruit, or seeds. Some hunt insects by suddenly attacking from a branch. Those species that seek pest insects are considered beneficial 'biological control agents' and their presence encouraged in biological pest control programmes. Combined, insectivorous birds eat 400–500 million metric tons of arthropods annually.\nNectar feeders such as hummingbirds, sunbirds, lories, and lorikeets amongst others have specially adapted brushy tongues and in many cases bills designed to fit co-adapted flowers. Kiwis and shorebirds with long bills probe for invertebrates; shorebirds' varied bill lengths and feeding methods result in the separation of ecological niches. Loons, diving ducks, penguins and auks pursue their prey underwater, using their wings or feet for propulsion, while aerial predators such as sulids, kingfishers and terns plunge dive after their prey. Flamingos, three species of prion, and some ducks are filter feeders. Geese and dabbling ducks are primarily grazers."]], "corpus": "wikipedia"}
84
+ {"tstamp": 1722360288.8895, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1722360288.4132, "finish": 1722360288.8895, "ip": "", "conv_id": "b454985e65da4a54967a4a82ac91170c", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "Can plants get cancer?", "output": [["Can plants get cancer?", "Blue agave\n\nTequila production Tequila is made only from a specific cultivar of Agave tequilana called 'Weber Azul'. The plant is from the Asparagaceae family. This cultivar is larger and blue-gray in color compared to the smaller and green normal A. tequilana. It is a rapid grower and prolific offsetter in keeping with its agricultural advantages. Tequila is produced by removing the heart (piña) of the plant in its seventh to fourteenth year (depending on growth rate and whims of harvester). Harvested piñas normally weigh . This heart is stripped of its leaves and heated to convert the inulin to sugars. Then the roasted core is pressed or crushed to release the sugary clear liquid called aguamiel, which is, in turn, fermented and distilled into alcohol. Tequila is also made with a sugar formulation of 51% agave and 49% other sugars. These tequilas are referred to as Mixtos.\nPathogens affecting the plant\nAs agave production has moved to an industrial scale since the end of the 1980s, diseases and pests, collectively referred to as TMA (tristeza y muerte de agave, \"wilting and death of agave\"), have hit the crops. Through the 1990s, diseases spread, particularly Fusarium fungi and Erwinia bacteria, exacerbated by the low genetic diversity of the agave plants. Other problems include the agave weevil, Scyphophorus acupunctatus, and a fungus, Thielaviopsis paradoxa.\nAccording to a 2004 study, additional pathogens, Erwinia carotovora, Enterobacter agglomerans, Pseudomonas mendocina, and Serratia spp. are responsible for continued rot."]], "corpus": "wikipedia"}
85
+ {"tstamp": 1722360288.8895, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1722360288.4132, "finish": 1722360288.8895, "ip": "", "conv_id": "8e0a2106198b416899abf77d45576c31", "model_name": "voyage-multilingual-2", "prompt": "Can plants get cancer?", "output": [["Can plants get cancer?", "List of unproven and disproven cancer treatments\n\nVenus flytrap – a carnivorous plant, the extract of which is promoted as a treatment for a variety of human ailments including skin cancer. According to the American Cancer Society, \"available scientific evidence does not support claims that extract from the Venus flytrap plant is effective in treating skin cancer or any other type of cancer\".\nWalnuts – large, hard edible seeds of any tree of the genus Juglans. Black walnut has been promoted as a cancer cure on the basis it kills a \"parasite\" responsible for the disease. However, according to the American Cancer Society, \"available scientific evidence does not support claims that hulls from black walnuts remove parasites from the intestinal tract or that they are effective in treating cancer or any other disease\".\nWheatgrass – a food made from grains of wheat. According to the American Cancer Society, although some wheatgrass champions claim it can \"shrink\" cancer tumors, \"available scientific evidence does not support the idea that wheatgrass or the wheatgrass diet can cure or prevent disease\".\nWild yam (or Chinese yam) – types of yam, the roots of which are made into creams and dietary supplements that are promoted for a variety of medicinal purposes, including cancer prevention. The American Cancer Society says of these products, \"available scientific evidence does not support claims that they are safe or effective.\""]], "corpus": "wikipedia"}