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 {"tstamp": 1725462444.6369, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1725462444.3499, "finish": 1725462444.6369, "ip": "", "conv_id": "5ac93a176b1b40699476a5ba772a4029", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "I am searching for a good and large-scale benchmark for testing the performance of text embeddings.", "output": [["I am searching for a good and large-scale benchmark for testing the performance of text embeddings.", "Title: MTEB: Massive Text Embedding Benchmark\n\nAbstract: Text embeddings are commonly evaluated on a small set of datasets from a single task not covering their possible applications to other tasks. It is unclear whether state-of-the-art embeddings on semantic textual similarity (STS) can be equally well applied to other tasks like clustering or reranking. This makes progress in the field difficult to track, as various models are constantly being proposed without proper evaluation. To solve this problem, we introduce the Massive Text Embedding Benchmark (MTEB). MTEB spans 8 embedding tasks covering a total of 58 datasets and 112 languages. Through the benchmarking of 33 models on MTEB, we establish the most comprehensive benchmark of text embeddings to date. We find that no particular text embedding method dominates across all tasks. This suggests that the field has yet to converge on a universal text embedding method and scale it up sufficiently to provide state-of-the-art results on all embedding tasks. MTEB comes with open-source code and a public leaderboard at https://github.com/embeddings-benchmark/mteb."]], "corpus": "arxiv"}
 {"tstamp": 1725466329.2464, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1725466326.9232, "finish": 1725466329.2464, "ip": "", "conv_id": "df27f20670ff48e7a2d1f8be02f7df87", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe Turing test, originally called the imitation game by Alan Turing in 1950, is a test of a machine's ability to exhibit intelligent behaviour equivalent to, or indistinguishable from, that of a human. Turing proposed that a human evaluator would judge natural language conversations between a human and a machine designed to generate human-like responses. The evaluator would be aware that one of the two partners in conversation was a machine, and all participants would be separated from one another. The conversation would be limited to a text-only channel, such as a computer keyboard and screen, so the result would not depend on the machine's ability to render words as speech. If the evaluator could not reliably tell the machine from the human, the machine would be said to have passed the test. The test results would not depend on the machine's ability to give correct answers to questions, only on how closely its answers resembled those a human would give. Since the Turing test is a test of indistinguishability in performance capacity, the verbal version generalizes naturally to all of human performance capacity, verbal as well as nonverbal (robotic)."]], "corpus": "wikipedia"}
 {"tstamp": 1725466329.2464, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1725466326.9232, "finish": 1725466329.2464, "ip": "", "conv_id": "246cd013d6f0448daf744954400b5a76", "model_name": "GritLM/GritLM-7B", "prompt": "Which test was devised to determine whether robots can think?", "output": [["Which test was devised to determine whether robots can think?", "Turing test\n\nThe test was introduced by Turing in his 1950 paper \"Computing Machinery and Intelligence\" while working at the University of Manchester. It opens with the words: \"I propose to consider the question, 'Can machines think? Because \"thinking\" is difficult to define, Turing chooses to \"replace the question by another, which is closely related to it and is expressed in relatively unambiguous words.\" Turing describes the new form of the problem in terms of a three-person game called the \"imitation game\", in which an interrogator asks questions of a man and a woman in another room in order to determine the correct sex of the two players. Turing's new question is: \"Are there imaginable digital computers which would do well in the imitation game?\" This question, Turing believed, was one that could actually be answered. In the remainder of the paper, he argued against all the major objections to the proposition that \"machines can think\".\nSince Turing introduced his test, it has been both highly influential and widely criticized, and has become an important concept in the philosophy of artificial intelligence. Philosopher John Searle would comment on the Turing test in his Chinese room argument, a thought experiment that stipulates that a machine cannot have a \"mind\", \"understanding\", or \"consciousness\", regardless of how intelligently or human-like the program may make the computer behave. Searle criticizes Turing's test and claims it is insufficient to detect the presence of consciousness.\nHistory"]], "corpus": "wikipedia"}
+{"tstamp": 1725472160.7697, "task_type": "retrieval", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1725472158.5668, "finish": 1725472160.7697, "ip": "", "conv_id": "5559b660da8e42f6839596182048243c", "model_name": "text-embedding-3-large", "prompt": "Penguin falling into tigers mouth", "output": [["Penguin falling into tigers mouth", "Penguin\n\nIn 1941, DC Comics introduced the avian-themed character of the Penguin as a supervillain adversary of the superhero Batman (Detective Comics #58). He became one of the most enduring enemies in Batman's rogues gallery. In the 60s Batman TV series, as played by Burgess Meredith, he was one of the most popular characters, and in Tim Burton's reimagining of the story, the character played by Danny Devito in the 1992 film Batman Returns, employed an actual army of penguins (mostly African penguins and king penguins).\nSeveral pro, minor, college and high school sport teams in the United States have named themselves after the species, including the Pittsburgh Penguins team in the National Hockey League and the Youngstown State Penguins in college athletics.\nPenguins featured regularly in the cartoons of U.K. cartoonist Steve Bell in his strip in The Guardian newspaper, particularly during and following the Falklands War. Opus the Penguin, from the cartoons of Berkeley Breathed, is also described as hailing from the Falklands. Opus was a comical, \"existentialist\" penguin character in the cartoons Bloom County, Outland and Opus. He was also the star in the animated Christmas TV special A Wish for Wings That Work.\nIn the mid-2000s, penguins became one of the most publicized species of animals that form lasting homosexual couples. A children's book, And Tango Makes Three, was written about one such penguin family in the New York Zoo."]], "corpus": "wikipedia"}
+{"tstamp": 1725472160.7697, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1725472158.5668, "finish": 1725472160.7697, "ip": "", "conv_id": "ffb8768926c74b95b60ac44efc41114e", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "Penguin falling into tigers mouth", "output": [["Penguin falling into tigers mouth", "Crested penguin\n\nEudyptes is a genus of penguins whose members are collectively called crested penguins. The exact number of species in the genus varies between four and seven depending on the authority, and a Chatham Islands species became extinct in recent centuries. All are black and white penguins with yellow crests, red bills and eyes, and are found on Subantarctic islands in the world's southern oceans. All lay two eggs, but raise only one young per breeding season; the first egg laid is substantially smaller than the second.\nTaxonomy\nThe genus Eudyptes was introduced by the French ornithologist Louis Pierre Vieillot in 1816; the name is derived from the Ancient Greek words  meaning \"fine\", and  meaning \"diver\". The type species was designated as the southern rockhopper penguin by George Robert Gray in 1840.\nSix extant species have been classically recognised, with the recent splitting of the rockhopper penguin increasing it to seven. Conversely, the close relationship of the macaroni and royal penguins, and the erect-crested and Snares penguins have led some to propose that the two pairs should be regarded as species.\nOrder Sphenisciformes\nFamily Spheniscidae\nFiordland penguin, Eudyptes pachyrhynchus\nSnares penguin, Eudyptes robustus – has been considered a subspecies of the Fiordland penguin\nErect-crested penguin, Eudyptes sclateri\nSouthern rockhopper penguin, Eudyptes chrysocome\nEastern rockhopper penguin, Eudyptes (chrysocome) filholi\nWestern rockhopper penguin, Eudyptes (chrysocome) chrysocome\nNorthern rockhopper penguin, Eudyptes moseleyi – traditionally considered a subspecies of Eudyptes chrysocome as the rockhopper penguin.\nRoyal penguin, Eudyptes schlegeli – sometimes considered a morph of E. chrysolophus\nMacaroni penguin, Eudyptes chrysolophus\nChatham penguin, Eudyptes warhami (extinct)"]], "corpus": "wikipedia"}