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data/retrieval_battle-dd51f1d2-bf9d-4e42-9a72-5b30dd2bd338.jsonl

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 {"tstamp": 1722356200.3701, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "2719b38b30a44cb08b58c23cfaaac5fe", "0_model_name": "intfloat/multilingual-e5-large-instruct", "0_prompt": "Research improving code generation models using CommitPack and HumanEvalPack datasets.", "0_output": [["Research improving code generation models using CommitPack and HumanEvalPack datasets.", "Title: Self-Edit: Fault-Aware Code Editor for Code Generation\n\nAbstract: Large language models (LLMs) have demonstrated an impressive ability to generate codes on competitive programming tasks. However, with limited sample numbers, LLMs still suffer from poor accuracy. Inspired by the process of human programming, we propose a generate-and-edit approach named Self-Edit that utilizes execution results of the generated code from LLMs to improve the code quality on the competitive programming task. We execute the generated code on the example test case provided in the question and wrap execution results into a supplementary comment. Utilizing this comment as guidance, our fault-aware code editor is employed to correct errors in the generated code. We perform extensive evaluations across two competitive programming datasets with nine different LLMs. Compared to directly generating from LLMs, our approach can improve the average of pass@1 by 89\\% on APPS-dev, 31\\% on APPS-test, and 48\\% on HumanEval over nine popular code generation LLMs with parameter sizes ranging from 110M to 175B. Compared to other post-processing methods, our method demonstrates superior accuracy and efficiency."]], "0_corpus": "arxiv", "1_conv_id": "9f392c55ce0242e699bcfa03f3da8923", "1_model_name": "nomic-ai/nomic-embed-text-v1.5", "1_prompt": "Research improving code generation models using CommitPack and HumanEvalPack datasets.", "1_output": [["Research improving code generation models using CommitPack and HumanEvalPack datasets.", "Title: Enhancement of the superconducting transition temperature in La2-xSrxCuO4 bilayers: Role of pairing and phase stiffness\n\nAbstract: The superconducting transition temperature, Tc, of bilayers comprising underdoped La2-xSrxCuO4 films capped by a thin heavily overdoped metallic La1.65Sr0.35CuO4 layer, is found to increase with respect to Tc of the bare underdoped films. The highest Tc is achieved for x = 0.12, close to the 'anomalous' 1/8 doping level, and exceeds that of the optimally-doped bare film. Our data suggest that the enhanced superconductivity is confined to the interface between the layers. We attribute the effect to a combination of the high pairing scale in the underdoped layer with an enhanced phase stiffness induced by the overdoped film."]], "1_corpus": "arxiv"}
 {"tstamp": 1722356865.2174, "task_type": "retrieval", "type": "rightvote", "models": ["", ""], "ip": "", "0_conv_id": "b3ad6f75148142cca47ea52be709f00e", "0_model_name": "nomic-ai/nomic-embed-text-v1.5", "0_prompt": "Research on enhancing Chinese word segmentation by leveraging Bidirectional Encoder Representations from Transformers to handle various annotation criteria across datasets.", "0_output": [["Research on enhancing Chinese word segmentation by leveraging Bidirectional Encoder Representations from Transformers to handle various annotation criteria across datasets.", "Title: Diffusion in normal and critical transient chaos\n\nAbstract: In this paper we investigate deterministic diffusion in systems which are spatially extended in certain directions but are restricted in size and open in other directions, consequently particles can escape. We introduce besides the diffusion coefficient D on the chaotic repeller a coefficient ${\\hat D}$ which measures the broadening of the distribution of trajectories during the transient chaotic motion. Both coefficients are explicitly computed for one-dimensional models, and they are found to be different in most cases. We show furthermore that a jump develops in both of the coefficients for most of the initial distributions when we approach the critical borderline where the escape rate equals the Liapunov exponent of a periodic orbit."]], "0_corpus": "arxiv", "1_conv_id": "bf0d0a6ae2d04641ac0d1978086695e0", "1_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "1_prompt": "Research on enhancing Chinese word segmentation by leveraging Bidirectional Encoder Representations from Transformers to handle various annotation criteria across datasets.", "1_output": [["Research on enhancing Chinese word segmentation by leveraging Bidirectional Encoder Representations from Transformers to handle various annotation criteria across datasets.", "Title: BERT Meets Chinese Word Segmentation\n\nAbstract: Chinese word segmentation (CWS) is a fundamental task for Chinese language understanding. Recently, neural network-based models have attained superior performance in solving the in-domain CWS task. Last year, Bidirectional Encoder Representation from Transformers (BERT), a new language representation model, has been proposed as a backbone model for many natural language tasks and redefined the corresponding performance. The excellent performance of BERT motivates us to apply it to solve the CWS task. By conducting intensive experiments in the benchmark datasets from the second International Chinese Word Segmentation Bake-off, we obtain several keen observations. BERT can slightly improve the performance even when the datasets contain the issue of labeling inconsistency. When applying sufficiently learned features, Softmax, a simpler classifier, can attain the same performance as that of a more complicated classifier, e.g., Conditional Random Field (CRF). The performance of BERT usually increases as the model size increases. The features extracted by BERT can be also applied as good candidates for other neural network models."]], "1_corpus": "arxiv"}
 {"tstamp": 1722357180.6325, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "42394a8aba7e4beda1c9a6de11159583", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "How do people think about the current Iran president?", "0_output": [["How do people think about the current Iran president?", "President of Iran\n\nThe president of Iran () is the head of government of the Islamic Republic of Iran and the second highest-ranking official, after the Supreme Leader. The first election was held in 1980 and was won by Abulhassan Banisadr. Mohammad Mokhber currently serves as the acting President of Iran following the death of Ebrahim Raisi, the former president, on 19 May 2024. He is expected to be succeeded by Masoud Pezeshkian on July 30, who won the 2024 Iranian presidential election.\nHistory\nAfter the Iranian Revolution of 1979 and 1979 Iranian Islamic Republic referendum on March 29 and 30, the new government needed to craft a new constitution. Supreme Leader Ruhollah Khomeini, ordered an election for the Assembly of Experts, the body tasked with writing the constitution. The assembly presented the constitution on October 24, 1979, and Supreme Leader Ruhollah Khomeini and Prime Minister Mehdi Bazargan approved it."]], "0_corpus": "wikipedia", "1_conv_id": "52214b21d0284944897b648b75b8af91", "1_model_name": "voyage-multilingual-2", "1_prompt": "How do people think about the current Iran president?", "1_output": [["How do people think about the current Iran president?", "History of the Islamic Republic of Iran\n\n2009 election controversy Ahmadinejad's 2009 election victory was hotly disputed and marred by large protests that formed the \"greatest domestic challenge\" to the leadership of the Islamic Republic \"in 30 years\". Despite high turnout and large enthusiastic crowds for reformist opponent Mir-Hossein Mousavi, Ahmadinejad was officially declared to have won by a 2–1 margin against three opponents.  Allegations of voting irregularities and protest by Mousavi his supporters were immediate and by 1 July 2009 1000 people had been arrested and 20 killed in street demonstrations. Supreme Leader Ali Khamenei and others Islamic officials blamed foreign powers for fomenting the protest. However, according to World Public Opinion (a United States poll), the protest does not mean Iran is in a \"pre-revolutionary\" situation as a WPO poll of Iranians taken in early September 2009 found high levels of satisfaction with the regime. 80% of the Iranians respondents said President Ahmadinejad was honest, 64% expressed a lot of confidence in him, and nine in ten said they were satisfied with Iran's system of government.\nPublic opinion\nAccording to the (U.S.) International Peace Institute's 2010-poll conducted in Persian by a representative sample of the Iranian people:\nIranians are divided on the government's performance.\nDissatisfied with the economy.\nWorry over sanctions and isolation.\nWant to focus on domestic affairs.\nFavor closer ties to the West.\nRising tensions sparked hostility toward the US, Europe, and U.N.\nFavor nuclear arms and do not want to back deals to halt enrichment.\nIndependent polls do not contradict official turnout of 2009 election, which gave around 60% of the vote to Ahmadinejad.\nRouhani Administration\nHassan Rouhani was elected as President of Iran on 12 June 2013 and took office on 3 August. He is known as a moderate left-leaner, supported by reformists in the election. He has open ideas in the area of economics and a high-level foreign policy, as he served as a diplomat before his election.  He has moved quickly to engage in diplomatic negotiations with Western countries, seeking the lifting of crippling economic sanctions on oil exports in exchange for Iran's cooperation with UN treaties regarding the development of nuclear weapons. Economic conditions improved during Rouhani's first term and led to his reelection in 2017 with his reformist agenda."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722357524.4041, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "3d09c01e7dfb4691b24743a8201671cf", "0_model_name": "sentence-transformers/all-MiniLM-L6-v2", "0_prompt": "Winter war", "0_output": [["Winter war", "Winter War\n\nOn 30 November 1939, Soviet forces invaded Finland with 21 divisions, totalling 450,000 men, and bombed Helsinki, killing about 100 citizens and destroying more than 50 buildings. In response to international criticism, Soviet Foreign Minister Vyacheslav Molotov stated that the Soviet Air Force was not bombing Finnish cities but rather dropping humanitarian aid to the starving Finnish population; the bombs were sarcastically dubbed Molotov bread baskets by Finns. The Finnish statesman J. K. Paasikivi commented that the Soviet attack without a declaration of war violated three separate non-aggression pacts: the Treaty of Tartu, which was signed in 1920, the non-aggression pact between Finland and the Soviet Union, which was signed in 1932 and again in 1934; and also the Covenant of the League of Nations, which the Soviet Union signed in 1934. Field Marshal C.G.E. Mannerheim was appointed Commander-in-Chief of the Finnish Defence Forces after the Soviet attack. In a further reshuffling, Aimo Cajander's caretaker cabinet was replaced by Risto Ryti and his cabinet, with Väinö Tanner as foreign minister because of opposition to Cajander's prewar politics. Finland brought the matter of the Soviet invasion before the League of Nations. The League expelled the Soviet Union on 14 December 1939 and exhorted its members to aid Finland.\nHeaded by Otto Wille Kuusinen, the Finnish Democratic Republic puppet government operated in the parts of Finnish Karelia occupied by the Soviets, and was also referred to as the \"Terijoki Government\", after the village of Terijoki, the first settlement captured by the advancing Red Army. After the war, the puppet government was reabsorbed into the Soviet Union. From the very outset of the war, working-class Finns stood behind the legitimate government in Helsinki. Finnish national unity against the Soviet invasion was later called the spirit of the Winter War.\nFirst battles and Soviet advance to Mannerheim Line"]], "0_corpus": "wikipedia", "1_conv_id": "b082f7b0fd6a44e9b625a592b31c17dc", "1_model_name": "BM25", "1_prompt": "Winter war", "1_output": [["Winter war", "Arab Winter\n\nThe Arab Winter () is a term referring to the resurgence of authoritarianism and Islamic extremism in some Arab countries in the 2010s in the aftermath of the Arab Spring protests. The term \"Arab Winter\" refers to the events across Arab League countries in the Middle East and North Africa, including the Syrian civil war, the Iraqi insurgency and the subsequent War in Iraq, the Egyptian Crisis, the First Libyan Civil War and the subsequent Second Libyan Civil War, and the Yemeni civil war. Events referred to as the Arab Winter include those in Egypt that led to the removal from office in 2013 of Mohamed Morsi and the subsequent election in 2014 of Abdel Fattah el-Sisi.\nThe term was first coined by Chinese political scientist Zhang Weiwei during a debate with American political scientist Francis Fukuyama on June 27, 2011. Fukuyama believed the Arab Spring movement would inevitably spread to China, while Zhang predicted the Arab Spring would soon turn into an Arab Winter.\nAccording to scholars of the University of Warsaw, the Arab Spring fully devolved into the Arab Winter four years after its onset, in 2014. The Arab Winter is characterized by the emergence of multiple regional wars, mounting regional instability, economic and demographic decline of Arab countries, and ethno-religious sectarian strife. According to a study by the American University of Beirut, by the summer of 2014, the Arab Winter had resulted in nearly a quarter of a million deaths and millions of refugees. Perhaps the most significant event in the Arab Winter was the rise of the extremist group Islamic State of Iraq and the Levant, which controlled swathes of land in the region from 2014 to 2019."]], "1_corpus": "wikipedia"}
+{"tstamp": 1722357588.6391, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "d4f10aa5072847e6823253fa571550a1", "0_model_name": "nomic-ai/nomic-embed-text-v1.5", "0_prompt": "Suomen startup skene", "0_output": [["Suomen startup skene", "Startup company\n\nA startup or start-up is a company or project undertaken by an entrepreneur to seek, develop, and validate a scalable business model. While entrepreneurship includes all new businesses including self-employment and businesses that do not intend to go public, startups are new businesses that intend to grow large beyond the solo-founder. During the beginning, startups face high uncertainty and have high rates of failure, but a minority of them do go on to become successful and influential.\nActions\nStartups typically begin by a founder (solo-founder) or co-founders who have a way to solve a problem. The founder of a startup will do the market validation by problem interview, solution interview, and building a minimum viable product (MVP), i.e. a prototype, to develop and validate their business models. The startup process can take a long period of time; hence, sustaining effort is required. Over the long term, sustaining effort is especially challenging because of the high failure rates and uncertain outcomes. Having a business plan in place outlines what to do and how to plan and achieve an idea in the future. Typically, these plans outline the first three to five years of your business strategy.\nDesign principles\nModels behind startups presenting as ventures are usually associated with design science. Design science uses design principles considered to be a coherent set of normative ideas and propositions to design and construct the company's backbone. For example, one of the initial design principles is affordable loss.\nHeuristics and biases in startup actions"]], "0_corpus": "wikipedia", "1_conv_id": "7d2dccb966ad4902a22b492ec1a01a3b", "1_model_name": "jinaai/jina-embeddings-v2-base-en", "1_prompt": "Suomen startup skene", "1_output": [["Suomen startup skene", "Suseok\n\nHistory Suseok began as votive art over 3000 years ago and became a fixture of Korean society during the Joseon Dynasty, when Confucian scholars displayed them on their writing desks. From here is where the English name \"scholar's rock\" originates. Suseok regained popularity amongst nouveau riche businessmen in the 1980s during Korea's economic boom.\nThe art usually works on three scales: large installations of monumental shaped stones as ornamental gates; medium-sized shaped stones for landscape decoration within Korean gardens; and the smaller shaped stones for scholar's tables, the most important of these scales.\nChinese gongshi influenced the development of suseok in Korea.\nEvaluation\nEarly on, important sites within landscape were marked with shaped stones, similarly to distance markers on post roads. Burial sites were also given permanent marking by large scale tumuli or mounds, often surrounded by anthropomorphic shaped stones much akin to that of Inuit or First Nations' memory markers. The animistic belief of nature being alive, and large-scaled elements of nature having souls, has led to the continued use of massive sculpted stone in natural forms throughout Korean traditional entranceways, as the firstgrowth cedarwood traditionally used for gates is now rare.\nAs Confucian scholarship ascended into the golden age of the Joseon dynasty, scholar rocks became an essential fixture of the writing tables of the yangban class of scholars, and a brilliant example of Confucian art."]], "1_corpus": "wikipedia"}

data/retrieval_individual-dd51f1d2-bf9d-4e42-9a72-5b30dd2bd338.jsonl

@@ -16,3 +16,15 @@
 {"tstamp": 1722357461.541, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722357461.3518, "finish": 1722357461.541, "ip": "", "conv_id": "713ed5efdf0945449e06f4bb0c3ed60c", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Kuhmo is magnificant city", "output": [["Kuhmo is magnificant city", "Kuopio\n\nKuopio ( , ) is a city in Finland and the regional capital of North Savo. It is located in the Finnish Lakeland. The population of Kuopio is approximately , while the sub-region has a population of approximately . It is the  most populous municipality in Finland, and the seventh most populous urban area in the country.\nKuopio has a total area of , of which  is water and half is forest. Though the city's population is spread out , the city's urban areas are populated comparably densely (urban area: 1,618 /km²), making Kuopio Finland's second-most densely populated city.  At the end of 2018, its urban area had a population of approximately 90,000. Along with Joensuu, Kuopio is one of the major urban, economic, and cultural hubs of Eastern Finland."]], "corpus": "wikipedia"}
 {"tstamp": 1722357475.1337, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722357474.934, "finish": 1722357475.1337, "ip": "", "conv_id": "e195ef6369e04ff4bc0f882f4c7978d8", "model_name": "GritLM/GritLM-7B", "prompt": "Janne pesonen", "output": [["Janne pesonen", "Jani Hakanpää\n\nJani Hakanpää (born 31 March 1992) is a Finnish professional ice hockey defenceman for the Toronto Maple Leafs of the National Hockey League (NHL). Hakanpää was selected by the St. Louis Blues in the fourth round (104th overall) of the 2010 NHL Entry Draft.\nPlaying career\nHakanpää played in his native Finland for the Espoo Blues of the SM-liiga during the 2011–12 and 2012–13 seasons.\nOn 22 May 2012, Hakanpää was signed to a three-year, entry-level contract with draft club, the St. Louis Blues, who had drafted him 104th overall in the 2010 NHL Entry Draft.\nAfter attending the Blues training camp, Hakanpää was returned to the Espoo Blues on loan to begin the 2012–13 season. He contributed with 5 points through 34 games on the blueline in Finland before returning to North America to play out the 2012–13 AHL season with the St. Louis Blues' AHL affiliate, the Peoria Rivermen. He registered one goal and three assists in fourteen games.\nAt the completion of his entry-level deal with the Blues, Hakanpää opted to return to Finland signing a two-year contract with the Liiga club Oulun Kärpät on 2 July 2015."]], "corpus": "wikipedia"}
 {"tstamp": 1722357475.1337, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722357474.934, "finish": 1722357475.1337, "ip": "", "conv_id": "059749eedabb4a1b855581248f82ab6b", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Janne pesonen", "output": [["Janne pesonen", "Janine Jansen\n\nJanine Jansen (born 7 January 1978) is a Dutch violinist and violist.\nEarly life and education\nJansen was born in Soest in the Netherlands into a musical family. Her father  plays organ, harpsichord and piano; from 1987 to mid-2011 he was the organist of St. Martin's Cathedral, Utrecht, and was invested as a Knight of the Order of Orange-Nassau. Her mother was a classical singer; her brother David (nl) is a harpsichordist and organist; her brother Maarten is a cellist; and her uncle is the bass singer Peter Kooy. She began to study the violin at age 6, and has studied with Coosje Wijzenbeek, Philippe Hirschhorn, and Boris Belkin.\nShe competed as a Junior Competitor in the Menuhin Competition in 1991 and 1993, advancing to the finals in 1991.\nShe is married to Swedish conductor  and lives in Utrecht, the Netherlands.\nCareer\nShe appeared as soloist with the National Youth Orchestra of Scotland in 2001, where she performed the Brahms Violin Concerto. She opened the BBC Proms in 2005."]], "corpus": "wikipedia"}
+{"tstamp": 1722357496.8379, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1722357496.6714, "finish": 1722357496.8379, "ip": "", "conv_id": "eed40ad1044b4f288cb314b533d88941", "model_name": "GritLM/GritLM-7B", "prompt": "Teemu selänne ja tre kronor", "output": [["Teemu selänne ja tre kronor", "Teemu Selänne\n\nA popular figure in Finland, Selänne's success in the NHL has been credited with aiding the growth of hockey in the country. He was once named the sexiest man in Finland by fashion magazine Eeva, and is the subject of the 2013 documentary film Selänne, directed by JP Siili, and which chronicles his life. The film became the highest grossing documentary in Finnish history within a month of its September 27 release, and was the third highest grossing locally produced film of the year.\nAfter retiring from professional ice hockey, Selänne has become an active political commentator on Twitter. Selänne has said that he got interested in politics in 2015 after Donald Trump started his political campaign. Selänne supported Trump for president in the 2016 United States presidential elections, but has later stated that he has been falsely labeled a Trump supporter. In 2023, he mentioned Mike Pence and Ron DeSantis as politicians he prefers over Trump. In Finnish politics, Selänne has supported the centre-right National Coalition Party.\nIn November 2019, Selänne released his authorized biography in North America titled \"Teemu Selänne: My Life.\" In March 2024, Selänne and his wife Sirpa gained Citizenship of the United States from the USCIS. They have lived in Southern California since 1996.\nCareer statistics\nRegular season and playoffs\nBold indicates led league\nInternational\nAwards and achievements"]], "corpus": "wikipedia"}
+{"tstamp": 1722357496.8379, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1722357496.6714, "finish": 1722357496.8379, "ip": "", "conv_id": "e318bf883d83408fac08906d0e973e45", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "Teemu selänne ja tre kronor", "output": [["Teemu selänne ja tre kronor", "Teemu Selänne\n\nSelänne was a first-round selection of the Jets, tenth overall, at the 1988 NHL Entry Draft, but initially remained in Finland. He led the SM-liiga in scoring as part of Jokerit's Kanada-malja winning team in 1991–92 before moving to North America. He broke into the NHL by scoring 76 goals and 132 points in the 1992–93. It remains the league record for most goals and points by a rookie and earned him the Calder Memorial Trophy as the top first-year player in the NHL. He has scored 50 goals in a season three times and topped 100 points on four occasions. He played in 10 NHL All-Star Games, was named to four post-season All-Star teams and won the inaugural Maurice \"Rocket\" Richard Trophy in 1998–99 as the league's leading goal scorer. He was named recipient of the Bill Masterton Memorial Trophy in 2005–06 for perseverance and dedication to the game and was a member of the Ducks' 2007 Stanley Cup championship team.\nInternationally, Selänne was a long-time member of the Finland national team. He played in five World Championships, winning a silver and bronze medal, and in three Canada Cup/World Cup of Hockey tournaments. A six-time Olympian, Selänne helped Finland win three bronze medals and, in 2006, a silver medal.  He is the all-time leader in scoring at the Olympic ice hockey tournament with 43 points. A national star in his native country, Selänne is the subject of a top-grossing biographical documentary in Finland. He was inducted into the IIHF Hall of Fame in 2017.\nEarly life\nSelänne was born on July 3, 1970, in Helsinki, Finland. He has a twin brother, Paavo and another brother, Panu. He was raised by his mother Liisa Viitanen (died 2018) and father Ilmari Selänne until they divorced in the late 1980s. The family lived for a time in Rauma before settling in Espoo around the time Teemu was 10 years old."]], "corpus": "wikipedia"}
+{"tstamp": 1722357519.2296, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722357518.8665, "finish": 1722357519.2296, "ip": "", "conv_id": "3d09c01e7dfb4691b24743a8201671cf", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "Winter war", "output": [["Winter war", "Winter War\n\nOn 30 November 1939, Soviet forces invaded Finland with 21 divisions, totalling 450,000 men, and bombed Helsinki, killing about 100 citizens and destroying more than 50 buildings. In response to international criticism, Soviet Foreign Minister Vyacheslav Molotov stated that the Soviet Air Force was not bombing Finnish cities but rather dropping humanitarian aid to the starving Finnish population; the bombs were sarcastically dubbed Molotov bread baskets by Finns. The Finnish statesman J. K. Paasikivi commented that the Soviet attack without a declaration of war violated three separate non-aggression pacts: the Treaty of Tartu, which was signed in 1920, the non-aggression pact between Finland and the Soviet Union, which was signed in 1932 and again in 1934; and also the Covenant of the League of Nations, which the Soviet Union signed in 1934. Field Marshal C.G.E. Mannerheim was appointed Commander-in-Chief of the Finnish Defence Forces after the Soviet attack. In a further reshuffling, Aimo Cajander's caretaker cabinet was replaced by Risto Ryti and his cabinet, with Väinö Tanner as foreign minister because of opposition to Cajander's prewar politics. Finland brought the matter of the Soviet invasion before the League of Nations. The League expelled the Soviet Union on 14 December 1939 and exhorted its members to aid Finland.\nHeaded by Otto Wille Kuusinen, the Finnish Democratic Republic puppet government operated in the parts of Finnish Karelia occupied by the Soviets, and was also referred to as the \"Terijoki Government\", after the village of Terijoki, the first settlement captured by the advancing Red Army. After the war, the puppet government was reabsorbed into the Soviet Union. From the very outset of the war, working-class Finns stood behind the legitimate government in Helsinki. Finnish national unity against the Soviet invasion was later called the spirit of the Winter War.\nFirst battles and Soviet advance to Mannerheim Line"]], "corpus": "wikipedia"}
+{"tstamp": 1722357519.2296, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1722357518.8665, "finish": 1722357519.2296, "ip": "", "conv_id": "b082f7b0fd6a44e9b625a592b31c17dc", "model_name": "BM25", "prompt": "Winter war", "output": [["Winter war", "Arab Winter\n\nThe Arab Winter () is a term referring to the resurgence of authoritarianism and Islamic extremism in some Arab countries in the 2010s in the aftermath of the Arab Spring protests. The term \"Arab Winter\" refers to the events across Arab League countries in the Middle East and North Africa, including the Syrian civil war, the Iraqi insurgency and the subsequent War in Iraq, the Egyptian Crisis, the First Libyan Civil War and the subsequent Second Libyan Civil War, and the Yemeni civil war. Events referred to as the Arab Winter include those in Egypt that led to the removal from office in 2013 of Mohamed Morsi and the subsequent election in 2014 of Abdel Fattah el-Sisi.\nThe term was first coined by Chinese political scientist Zhang Weiwei during a debate with American political scientist Francis Fukuyama on June 27, 2011. Fukuyama believed the Arab Spring movement would inevitably spread to China, while Zhang predicted the Arab Spring would soon turn into an Arab Winter.\nAccording to scholars of the University of Warsaw, the Arab Spring fully devolved into the Arab Winter four years after its onset, in 2014. The Arab Winter is characterized by the emergence of multiple regional wars, mounting regional instability, economic and demographic decline of Arab countries, and ethno-religious sectarian strife. According to a study by the American University of Beirut, by the summer of 2014, the Arab Winter had resulted in nearly a quarter of a million deaths and millions of refugees. Perhaps the most significant event in the Arab Winter was the rise of the extremist group Islamic State of Iraq and the Levant, which controlled swathes of land in the region from 2014 to 2019."]], "corpus": "wikipedia"}
+{"tstamp": 1722357546.4549, "task_type": "retrieval", "type": "chat", "model": "text-embedding-3-large", "gen_params": {}, "start": 1722357545.7017, "finish": 1722357546.4549, "ip": "", "conv_id": "6abdade40a384065b9fdc298f12878fa", "model_name": "text-embedding-3-large", "prompt": "Lauri Törni", "output": [["Lauri Törni", "Lauri Törni\n\nLauri Allan Törni (28 May 1919 – 18 October 1965), later known as Larry Alan Thorne, was a Finnish-born soldier who fought under three flags: as a Finnish Army officer in the Winter War and the Continuation War ultimately gaining a rank of captain; as a Waffen-SS captain (under the alias Larry Laine) of the Finnish Volunteer Battalion of the Waffen-SS when he fought the Red Army on the Eastern Front in World War II; and as a United States Army Major (under the alias \"Larry Thorne\") when he served in the U.S. Army Special Forces in the Vietnam War."]], "corpus": "wikipedia"}
+{"tstamp": 1722357546.4549, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722357545.7017, "finish": 1722357546.4549, "ip": "", "conv_id": "64b884ca93e943e5afd7ccd95e0297d8", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "Lauri Törni", "output": [["Lauri Törni", "Lauri Törni\n\nLauri Allan Törni (28 May 1919 – 18 October 1965), later known as Larry Alan Thorne, was a Finnish-born soldier who fought under three flags: as a Finnish Army officer in the Winter War and the Continuation War ultimately gaining a rank of captain; as a Waffen-SS captain (under the alias Larry Laine) of the Finnish Volunteer Battalion of the Waffen-SS when he fought the Red Army on the Eastern Front in World War II; and as a United States Army Major (under the alias \"Larry Thorne\") when he served in the U.S. Army Special Forces in the Vietnam War."]], "corpus": "wikipedia"}
+{"tstamp": 1722357559.7581, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1722357559.5518, "finish": 1722357559.7581, "ip": "", "conv_id": "83015c358da44260975716dc1559f45d", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "Kalakukko", "output": [["Kalakukko", "Kokkola\n\nKokkola (; , ) is a town in Finland and the regional capital of Central Ostrobothnia. It is located on the west coast of the country, on the Gulf of Bothnia. The population of Kokkola is approximately , while the sub-region has a population of approximately . It is the  most populous municipality in Finland, and the 20th most populous urban area in the country.\nKokkola covers an area of  of which  is water. The population density is . Neighbour municipalities are Halsua, Kalajoki, Kannus, Kaustinen, Kronoby, Lestijärvi, Larsmo and Toholampi."]], "corpus": "wikipedia"}
+{"tstamp": 1722357559.7581, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722357559.5518, "finish": 1722357559.7581, "ip": "", "conv_id": "ffd567fa8a084b38a441cfdcc909d94e", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Kalakukko", "output": [["Kalakukko", "Kalaburagi\n\nKalaburagi, formerly known as Gulbarga, is a city in the Indian state of Karnataka. It is the administrative headquarters of the Kalaburagi district and is the largest city in the region of North Karnataka (Kalyana-Karnataka). Kalaburagi is 568 km north of the state capital city of Bangalore. It was incorporated into the newly formed Mysore State (now known as Karnataka) through the States Reorganisation Act in 1956."]], "corpus": "wikipedia"}
+{"tstamp": 1722357577.8054, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1722357575.6654, "finish": 1722357577.8054, "ip": "", "conv_id": "d4f10aa5072847e6823253fa571550a1", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "Suomen startup skene", "output": [["Suomen startup skene", "Startup company\n\nA startup or start-up is a company or project undertaken by an entrepreneur to seek, develop, and validate a scalable business model. While entrepreneurship includes all new businesses including self-employment and businesses that do not intend to go public, startups are new businesses that intend to grow large beyond the solo-founder. During the beginning, startups face high uncertainty and have high rates of failure, but a minority of them do go on to become successful and influential.\nActions\nStartups typically begin by a founder (solo-founder) or co-founders who have a way to solve a problem. The founder of a startup will do the market validation by problem interview, solution interview, and building a minimum viable product (MVP), i.e. a prototype, to develop and validate their business models. The startup process can take a long period of time; hence, sustaining effort is required. Over the long term, sustaining effort is especially challenging because of the high failure rates and uncertain outcomes. Having a business plan in place outlines what to do and how to plan and achieve an idea in the future. Typically, these plans outline the first three to five years of your business strategy.\nDesign principles\nModels behind startups presenting as ventures are usually associated with design science. Design science uses design principles considered to be a coherent set of normative ideas and propositions to design and construct the company's backbone. For example, one of the initial design principles is affordable loss.\nHeuristics and biases in startup actions"]], "corpus": "wikipedia"}
+{"tstamp": 1722357577.8054, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1722357575.6654, "finish": 1722357577.8054, "ip": "", "conv_id": "7d2dccb966ad4902a22b492ec1a01a3b", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "Suomen startup skene", "output": [["Suomen startup skene", "Suseok\n\nHistory Suseok began as votive art over 3000 years ago and became a fixture of Korean society during the Joseon Dynasty, when Confucian scholars displayed them on their writing desks. From here is where the English name \"scholar's rock\" originates. Suseok regained popularity amongst nouveau riche businessmen in the 1980s during Korea's economic boom.\nThe art usually works on three scales: large installations of monumental shaped stones as ornamental gates; medium-sized shaped stones for landscape decoration within Korean gardens; and the smaller shaped stones for scholar's tables, the most important of these scales.\nChinese gongshi influenced the development of suseok in Korea.\nEvaluation\nEarly on, important sites within landscape were marked with shaped stones, similarly to distance markers on post roads. Burial sites were also given permanent marking by large scale tumuli or mounds, often surrounded by anthropomorphic shaped stones much akin to that of Inuit or First Nations' memory markers. The animistic belief of nature being alive, and large-scaled elements of nature having souls, has led to the continued use of massive sculpted stone in natural forms throughout Korean traditional entranceways, as the firstgrowth cedarwood traditionally used for gates is now rare.\nAs Confucian scholarship ascended into the golden age of the Joseon dynasty, scholar rocks became an essential fixture of the writing tables of the yangban class of scholars, and a brilliant example of Confucian art."]], "corpus": "wikipedia"}
+{"tstamp": 1722357648.0654, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1722357647.8007, "finish": 1722357648.0654, "ip": "", "conv_id": "40adf2ecfae142f690cf15572d1c2a39", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "A paper with a dataset and methods for Chinese LFQA including real-time web search interaction  ", "output": [["A paper with a dataset and methods for Chinese LFQA including real-time web search interaction  ", "Title: WebCPM: Interactive Web Search for Chinese Long-form Question Answering\n\nAbstract: Long-form question answering (LFQA) aims at answering complex, open-ended questions with detailed, paragraph-length responses. The de facto paradigm of LFQA necessitates two procedures: information retrieval, which searches for relevant supporting facts, and information synthesis, which integrates these facts into a coherent answer. In this paper, we introduce WebCPM, the first Chinese LFQA dataset. One unique feature of WebCPM is that its information retrieval is based on interactive web search, which engages with a search engine in real time. Following WebGPT, we develop a web search interface. We recruit annotators to search for relevant information using our interface and then answer questions. Meanwhile, the web search behaviors of our annotators would be recorded. In total, we collect 5,500 high-quality question-answer pairs, together with 14,315 supporting facts and 121,330 web search actions. We fine-tune pre-trained language models to imitate human behaviors for web search and to generate answers based on the collected facts. Our LFQA pipeline, built on these fine-tuned models, generates answers that are no worse than human-written ones in 32.5% and 47.5% of the cases on our dataset and DuReader, respectively."]], "corpus": "arxiv"}
+{"tstamp": 1722357648.0654, "task_type": "retrieval", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1722357647.8007, "finish": 1722357648.0654, "ip": "", "conv_id": "5b7d23084cf84e698b8ae3ef7e10bdc3", "model_name": "embed-english-v3.0", "prompt": "A paper with a dataset and methods for Chinese LFQA including real-time web search interaction  ", "output": [["A paper with a dataset and methods for Chinese LFQA including real-time web search interaction  ", "Title: WebCPM: Interactive Web Search for Chinese Long-form Question Answering\n\nAbstract: Long-form question answering (LFQA) aims at answering complex, open-ended questions with detailed, paragraph-length responses. The de facto paradigm of LFQA necessitates two procedures: information retrieval, which searches for relevant supporting facts, and information synthesis, which integrates these facts into a coherent answer. In this paper, we introduce WebCPM, the first Chinese LFQA dataset. One unique feature of WebCPM is that its information retrieval is based on interactive web search, which engages with a search engine in real time. Following WebGPT, we develop a web search interface. We recruit annotators to search for relevant information using our interface and then answer questions. Meanwhile, the web search behaviors of our annotators would be recorded. In total, we collect 5,500 high-quality question-answer pairs, together with 14,315 supporting facts and 121,330 web search actions. We fine-tune pre-trained language models to imitate human behaviors for web search and to generate answers based on the collected facts. Our LFQA pipeline, built on these fine-tuned models, generates answers that are no worse than human-written ones in 32.5% and 47.5% of the cases on our dataset and DuReader, respectively."]], "corpus": "arxiv"}