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data/retrieval_individual-fc2e4671-7e20-44ad-a373-899a077f1401.jsonl

@@ -88,3 +88,9 @@
 {"tstamp": 1726512079.7028, "task_type": "retrieval", "type": "chat", "model": "intfloat/multilingual-e5-large-instruct", "gen_params": {}, "start": 1726512079.0738, "finish": 1726512079.7028, "ip": "", "conv_id": "9fa5e360a4634b9eb781f99879d5a450", "model_name": "intfloat/multilingual-e5-large-instruct", "prompt": "Towards Unified Alignment Between Agents,Humans, and Environment ", "output": [["Towards Unified Alignment Between Agents,Humans, and Environment ", "Title: Towards Unified Alignment Between Agents, Humans, and Environment\n\nAbstract: The rapid progress of foundation models has led to the prosperity of autonomous agents, which leverage the universal capabilities of foundation models to conduct reasoning, decision-making, and environmental interaction. However, the efficacy of agents remains limited when operating in intricate, realistic environments. In this work, we introduce the principles of $\\mathbf{U}$nified $\\mathbf{A}$lignment for $\\mathbf{A}$gents ($\\mathbf{UA}^2$), which advocate for the simultaneous alignment of agents with human intentions, environmental dynamics, and self-constraints such as the limitation of monetary budgets. From the perspective of $\\mathbf{UA}^2$, we review the current agent research and highlight the neglected factors in existing agent benchmarks and method candidates. We also conduct proof-of-concept studies by introducing realistic features to WebShop, including user profiles to demonstrate intentions, personalized reranking for complex environmental dynamics, and runtime cost statistics to reflect self-constraints. We then follow the principles of $\\mathbf{UA}^2$ to propose an initial design of our agent, and benchmark its performance with several candidate baselines in the retrofitted WebShop. The extensive experimental results further prove the importance of the principles of $\\mathbf{UA}^2$. Our research sheds light on the next steps of autonomous agent research with improved general problem-solving abilities."]], "corpus": "arxiv"}
 {"tstamp": 1726513479.8571, "task_type": "retrieval", "type": "chat", "model": "Salesforce/SFR-Embedding-2_R", "gen_params": {}, "start": 1726513479.4783, "finish": 1726513479.8571, "ip": "", "conv_id": "2879018da7ca4d8ca57c95f99af06a21", "model_name": "Salesforce/SFR-Embedding-2_R", "prompt": "A benchmark to measure the performance of contextualized word embeddings against traditional embeddings.", "output": [["A benchmark to measure the performance of contextualized word embeddings against traditional embeddings.", "Title: Word Embeddings for Chemical Patent Natural Language Processing\n\nAbstract: We evaluate chemical patent word embeddings against known biomedical embeddings and show that they outperform the latter extrinsically and intrinsically. We also show that using contextualized embeddings can induce predictive models of reasonable performance for this domain over a relatively small gold standard."]], "corpus": "arxiv"}
 {"tstamp": 1726513479.8571, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1726513479.4783, "finish": 1726513479.8571, "ip": "", "conv_id": "3becfa2a63804aa2a8c0e3a1707cec9f", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "A benchmark to measure the performance of contextualized word embeddings against traditional embeddings.", "output": [["A benchmark to measure the performance of contextualized word embeddings against traditional embeddings.", "Title: A Survey on Contextual Embeddings\n\nAbstract: Contextual embeddings, such as ELMo and BERT, move beyond global word representations like Word2Vec and achieve ground-breaking performance on a wide range of natural language processing tasks. Contextual embeddings assign each word a representation based on its context, thereby capturing uses of words across varied contexts and encoding knowledge that transfers across languages. In this survey, we review existing contextual embedding models, cross-lingual polyglot pre-training, the application of contextual embeddings in downstream tasks, model compression, and model analyses."]], "corpus": "arxiv"}
+{"tstamp": 1726515829.8717, "task_type": "retrieval", "type": "chat", "model": "GritLM/GritLM-7B", "gen_params": {}, "start": 1726515829.6029, "finish": 1726515829.8717, "ip": "", "conv_id": "db19324827684992901a1b1dfa0bd506", "model_name": "GritLM/GritLM-7B", "prompt": "What is the fastest car?", "output": [["What is the fastest car?", "Production car speed record\n\nIn April 2013, following a press release claiming the record for the Hennessey Venom GT due to the electronic limiter issue, The Sunday Times quoted Guinness public relations director Jaime Strang as saying: \"As the car's speed limiter was deactivated, this modification was against the official guidelines. Consequently, the vehicle's record set at  is no longer valid.\" Five days later, Guinness World Records officially posted on its website that it: \"...would like to confirm that Bugatti's record has not been disqualified; the record category is currently under review.\" Five days later Bugatti's speed record was confirmed: \"Following a thorough review conducted with a number of external experts, Guinness World Records is pleased to announce the confirmation of Bugatti's record of Fastest production car achieved by the Veyron 16.4 Super Sport. The focus of the review was with respect to what may constitute a modification to a car's standard specification. Having evaluated all the necessary information, Guinness World Records is now satisfied that a change to the speed limiter does not alter the fundamental design of the car or its engine.\"\nCars excluded from the list\nSome cars were not considered to be the fastest production vehicles, for various reasons. Here is a list of some well-known cars that have not been able to meet standards needed to be the fastest production car."]], "corpus": "wikipedia"}
+{"tstamp": 1726515829.8717, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1726515829.6029, "finish": 1726515829.8717, "ip": "", "conv_id": "ac5937306ebd4d9db17c868cb4c33525", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "What is the fastest car?", "output": [["What is the fastest car?", "List of automotive superlatives\n\nQuickest  with 1 foot rollout – 3.21 seconds – Rimac Nevera\nQuickest  with 1 foot rollout – 4.42 seconds – Rimac Nevera\nQuickest  with 1 foot rollout – 9.22 seconds – Rimac Nevera\nQuickest  with 1 foot rollout – 20.68 seconds – Koenigsegg Regera (with non-standard Michelin Pilot Sport Cup 2 R tyres)\nTop speed\nHighest top speed (forced induction petrol engine) – Bugatti Chiron Super Sport 300+ –\nHighest top speed (naturally aspirated engine) – McLaren F1 –\nHighest top speed (forced induction diesel engine) – BMW Alpina D5 S –\nHighest top speed (electric production vehicle) – Rimac Nevera –\nHighest top speed (unibody SUV) – Lamborghini Urus SE –\nHighest top speed (production half-ton pickup truck) – Dodge Ram SRT-10 –\nHighest top speed (current production half-ton pickup truck) – Ram 1500 TRX –\nHighest rpm redline\nInternal combustion piston-engined production car – Gordon Murray T.50 – 12,100 rpm\nInternal combustion Wankel rotary-engined production car – Mazda RX-8 – 9,000 rpm\nElectric production vehicle – Zeekr 001 FR – 20,620 rpm\nSales\nBest-selling models\nBest-selling vehicle nameplate – Toyota Corolla (more than 50,000,000 sold in 12 generations since 1966)\nBest-selling single model – Volkswagen Beetle (21,529,464 of the same basic design sold worldwide between 1938 and 2003)"]], "corpus": "wikipedia"}
+{"tstamp": 1726515990.9608, "task_type": "retrieval", "type": "chat", "model": "Alibaba-NLP/gte-Qwen2-7B-instruct", "gen_params": {}, "start": 1726515990.6887, "finish": 1726515990.9608, "ip": "", "conv_id": "9a290629cab4402b94abe7f3c973a08e", "model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "prompt": "What is the tallest building?", "output": [["What is the tallest building?", "List of tallest buildings and structures\n\nwhether structures built in and rising above water should have their below-water height included in any assessment.\nwhether a structure, building or tower that is guyed is assessed in the same category as self-supporting structures.\nWithin an accepted definition of a building further controversy has included the following factors:\nwhether only habitable height of the building is considered\nwhether communication towers with observation galleries should be considered \"habitable\" in this sense\nwhether rooftop antennas, viewing platforms or any other architecture that does not form a habitable floor should be included in the assessment\nwhether a floor built at a high level of a telecommunications or viewing tower should change the tower's definition to that of a \"building\"\nTallest structures\nThis category does not require the structure to be \"officially\" open, but does require it to be \"topped out\".\nThe tallest artificial structure is Burj Khalifa, a skyscraper in Dubai that reached  in height on January 17, 2009. By April 8, 2008 it had been built higher than the KVLY-TV mast in North Dakota, US. That September it officially surpassed Poland's  Warsaw radio mast, which stood from 1974 to 1991, to become the tallest structure ever built. Guyed lattice towers such as these masts had held the world height record since 1954."]], "corpus": "wikipedia"}
+{"tstamp": 1726515990.9608, "task_type": "retrieval", "type": "chat", "model": "nomic-ai/nomic-embed-text-v1.5", "gen_params": {}, "start": 1726515990.6887, "finish": 1726515990.9608, "ip": "", "conv_id": "4c959b03506d431493f721066cac35ed", "model_name": "nomic-ai/nomic-embed-text-v1.5", "prompt": "What is the tallest building?", "output": [["What is the tallest building?", "History of the world's tallest buildings\n\nThe tallest building in the world, as of , is the Burj Khalifa in Dubai. The title of \"world's tallest building\" has been held  by various buildings in modern times, including the Lincoln Cathedral in Lincoln, England, and the Empire State Building and the original World Trade Center, both in New York City.\nBefore the modern skyscraper era emerged, between  1311 and 1884 the tallest buildings and structures were mostly Christian churches and cathedrals. Prior to then, the tallest buildings in the world cannot be conclusively determined. For instance, the Lighthouse of Alexandria, which was completed in approximately 280 BC, has been estimated to have been  tall, but its true height is not known. For thousands of years, the Great Pyramid in Egypt was the tallest structure in the world until Lincoln Cathedral of 1311, but the Great Pyramid is not considered a building since it is not habitable. Similarly, the Eiffel Tower was the world's tallest structure from 1889, when it was built, but not the tallest building."]], "corpus": "wikipedia"}
+{"tstamp": 1726516095.8821, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1726516093.726, "finish": 1726516095.8821, "ip": "", "conv_id": "8c1e86ad154c42f28b750bd5d72efb37", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "What is the top grossing movie of 2019?", "output": [["What is the top grossing movie of 2019?", "List of highest-grossing films\n\nFilms generate income from several revenue streams, including theatrical exhibition, home video, television broadcast rights, and merchandising. However, theatrical box-office earnings are the primary metric for trade publications in assessing the success of a film, mostly because of the availability of the data compared to sales figures for home video and broadcast rights, but also because of historical practice. Included on the list are charts of the top box-office earners (ranked by both the nominal and real value of their revenue), a chart of high-grossing films by calendar year, a timeline showing the transition of the highest-grossing film record, and a chart of the highest-grossing film franchises and series. All charts are ranked by international theatrical box-office performance where possible, excluding income derived from home video, broadcasting rights, and merchandise."]], "corpus": "wikipedia"}
+{"tstamp": 1726516095.8821, "task_type": "retrieval", "type": "chat", "model": "jinaai/jina-embeddings-v2-base-en", "gen_params": {}, "start": 1726516093.726, "finish": 1726516095.8821, "ip": "", "conv_id": "f8a50fdf1c7b42e6a39f3749ab75003a", "model_name": "jinaai/jina-embeddings-v2-base-en", "prompt": "What is the top grossing movie of 2019?", "output": [["What is the top grossing movie of 2019?", "List of highest-grossing films\n\nWhile inflation has eroded the achievements of most films from the 1950s, 1960s, and 1970s, there are franchises originating from that period that are still active. Besides the Star Wars and Superman franchises, James Bond and Godzilla films are still being released periodically; all four are among the highest-grossing franchises. Some of the older films that held the record of highest-grossing film still have respectable grosses by today's standards, but no longer compete numerically against today's top-earners in an era of much higher individual ticket prices. When those prices are adjusted for inflation, however, then Gone with the Wind—which was the highest-grossing film outright for twenty-five years—is still the highest-grossing film of all time. All grosses on the list are expressed in U.S. dollars at their nominal value, except where stated otherwise.\nHighest-grossing films\nWith a worldwide box-office gross of over $2.9 billion, Avatar is proclaimed to be the \"highest-grossing\" film, but such claims usually refer to theatrical revenues only and do not take into account home video and television income, which can form a significant portion of a film's earnings. Once revenue from home entertainment is factored in, it is not immediately clear which film is the most successful. Titanic earned $1.2 billion from video and DVD sales and rentals, in addition to the $2.2 billion it grossed in theaters. While complete sales data are not available for Avatar, it earned $345 million from the sale of sixteen million DVD and Blu-ray units in North America, and ultimately sold a total of thirty million DVD and Blu-ray units worldwide. After home video income is accounted for, both films have earned over $3 billion each. Television broadcast rights will also substantially add to a film's earnings, with a film often earning the equivalent of as much as 20–25% of its theatrical box office for two television runs, on top of pay-per-view revenues; Titanic earned a further $55 million from the NBC and HBO broadcast rights, equating to about 9% of its North American gross."]], "corpus": "wikipedia"}

data/retrieval_side_by_side-fc2e4671-7e20-44ad-a373-899a077f1401.jsonl

@@ -6,3 +6,4 @@
 {"tstamp": 1726487359.2199, "task_type": "retrieval", "type": "tievote", "models": ["intfloat/e5-mistral-7b-instruct", "intfloat/multilingual-e5-large-instruct"], "ip": "", "0_conv_id": "d3bdac600cff4199af8264ed03d3daca", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "三重彩", "0_output": [["三重彩", "Komusō\n\nHifumi—Hachigaeshi no Shirabe 一二三鉢返の調 Taki-ochi no Kyoku (Taki-otoshi no Kyoku) 瀧落の曲\nAkita Sugagaki 秋田菅垣\nKoro Sugagaki 転菅垣\nKyūshū Reibo 九州鈴慕\nShizu no Kyoku 志図の曲\nKyō Reibo 京鈴慕\nMukaiji Reibo 霧海箎\nKokū Reibo  虚空\na)  Kokū Kaete (Ikkan-ryū) 虚空替手 (一関流) b) Banshikichō 盤渉調\nShin Kyorei 真虚霊\nKinsan Kyorei 琴三虚霊\nYoshiya Reibo 吉野鈴慕\nYūgure no Kyoku 夕暮の曲\nSakai Jishi 栄獅子\nUchikae Kyorei 打替虚霊\nIgusa Reibo 葦草鈴慕\nIzu Reibo 伊豆鈴慕\nReibo Nagashi 鈴慕流\nSōkaku Reibo 巣鶴鈴慕\nSanya Sugagaki 三谷菅垣\nShimotsuke Kyorei 下野虚霊\nMeguro-jishi 目黒獅子\nGinryū Kokū 吟龍虚空\nSayama Sugagaki 佐山菅垣\nSagari Ha no Kyoku 下り葉の曲\nNamima Reibo 波間鈴慕\nShika no Tōne 鹿の遠音\nHōshōsu 鳳将雛\nAkebono no Shirabe 曙の調\nAkebono Sugagaki 曙菅垣\nAshi no Shirabe 芦の調\nKotoji no Kyoku 琴柱の曲\nKinuta Sugomori 砧巣籠\nTsuki no Kyoku 月の曲\nKotobuki no Shirabe 寿の調\nAt least three additional pieces were later added to the Kinko-Ryu repertoire:\nKumoi Jishi 雲井獅子\nAzuma no Kyoku 吾妻の曲\nSugagaki  菅垣\nThe earliest list of the repertoire is dated to the first half of the 18th century, and the compositions don't contain direct references to the terminology of the Kyotaku denki, indication that the incorporation of Zen-philosophy, or \"shakuhachi-Zen,\" is a 19th-century phenomenon.\nComplete recordings\nRecordings of the complete honkyoku of the Kinko School have been recorded by\nAraki Kodo V (Chikuo II)\nAoki Reibo II"]], "0_corpus": "wikipedia", "1_conv_id": "11217a02d89f43dd8f12b29c9e475cfd", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "三重彩", "1_output": [["三重彩", "Parimutuel betting\n\nQuinella-Place (拡大連勝複式, Kakudai Renshō Fukushiki), also known as Wide (ワイド) or Kaku-renpuku (拡連複): The bettor must pick the two runners which finish the top three—no need to specify an order (For example, when the result of race is 3-6-2-4-5-1, the top three runners are 2, 3 and 6, and winning combinations are 2-3, 2-6 and 3-6.) (all four).\nTrio (3連勝複式, Sanrensho Fukushiki), abbreviated as San-renpuku (3連複): The bettor must pick the three runners which finish the top three, but no need to specify an order (all four).\nTrifecta (3連勝単式, Sanrensho Tanshiki), abbreviated as San-ren-tan (3連単): The bettor must correctly pick the three runners which finish first, second, and third (all four).\nWIN 5 / Select 5: The bettor must pick the winners of five designated races. Betting on operators' website by PC or cellular phone only (horse racing only).\nFrance\nThe following bet type are offered by the government-controlled betting agency Pari Mutuel Urbain (PMU).\nSimple Gagnant (Win): The bettor must correctly pick the runner that finishes first.\nSimple Placé (Place): The bettor must pick a runner that finishes either first, second or third in the race. If there are 7 or less starters in the race then third place is not counted and the bettor must pick a horse that finishes either first or second. This bet type is not available on events with 3 or fewer runners."]], "1_corpus": "wikipedia"}
 {"tstamp": 1726487417.0678, "task_type": "retrieval", "type": "tievote", "models": ["intfloat/e5-mistral-7b-instruct", "intfloat/multilingual-e5-large-instruct"], "ip": "", "0_conv_id": "e048e87222014ff7b20aa5f7ca5f8c21", "0_model_name": "intfloat/e5-mistral-7b-instruct", "0_prompt": "三重彩係咩？", "0_output": [["三重彩係咩？", "Anita Mui\n\n戀之火 今宵多珍重\n我要\n給我一個吻\n玫瑰、玫瑰、我愛你\n情歸何處\n你留我在此\n將冰山劈開\n床前明月光\n心窩已瘋\nBig Bad Girl\n夢伴\nOpening\nStand By Me\n將冰山劈開\n愛我便說愛我吧\n長藤掛銅鈴\nMedley:\n艷舞台\n烈焰紅唇\nMedley:\n憑甚麼\n假如我是男人\n黑夜的豹\n蔓珠莎華\nOh No! Oh Yes!\nWonderful Night\nFaithfully\n是這樣的\n夢幻的擁抱\n夢姬\n烈女\n心債\n一舞傾情\n約會\n胭脂扣\n床前明月光\n心窩已瘋\n芳華絕代\n床呀！床！\n似水流年\n似是故人來\n抱緊眼前人\n親密愛人\nMedley:\n孤身走我路\n夕陽之歌\nMedley:\n愛將\n壞女孩\n淑女\n妖女\n放開你的頭腦\n夢伴\n冰山大火\nOverture\n夢裡共醉\n是這樣的\n抱緊眼前人\n心肝寶貝\nMedley:\n何日\n李香蘭\n何日 Reprise\n心債\n第四十夜\n夏日戀人\n'O Sole Mio\n親密愛人\nMedley:\n愛情的代價\n我願意\n似夢迷離\n今生今世\n深愛著你\n孤身走我路\n胭脂扣\n似是故人來\n似水流年\nSukiyaki\n花月佳期\n夕陽之歌\nAwards\nNew Talent Singing Awards winner 1982\nTop 10 Jade Solid Gold Best Female Singer Award 1985–1989\nTop 10 Jade Solid Gold Gold Song Gold Award for Sunset Melody () 1989\nHong Kong Film Awards for Best Supporting Actress 1985 for Behind the Yellow Line\nGolden Horse Award for Best Leading Actress 1988 for Rouge\nAsia-Pacific Film Festival Awards for Best Actress 1989 for Rouge\nHong Kong Film Award for Best Actress 1989 for Rouge\nHong Kong Film Awards for Best Supporting Actress 1998 for Eighteen Springs\nGolden Bauhinia Awards for Best Supporting Actress 1998 for Eighteen Springs\nRTHK Golden Needle Award 1998\nGolden Deer Awards for Best Actress 2002 for July Rhapsody\nConcert tours/specials\nFilmography\nTV series"]], "0_corpus": "wikipedia", "1_conv_id": "e1af05c9e62141cca8d2a49003edd6f2", "1_model_name": "intfloat/multilingual-e5-large-instruct", "1_prompt": "三重彩係咩？", "1_output": [["三重彩係咩？", "Anita Mui\n\n戀之火 今宵多珍重\n我要\n給我一個吻\n玫瑰、玫瑰、我愛你\n情歸何處\n你留我在此\n將冰山劈開\n床前明月光\n心窩已瘋\nBig Bad Girl\n夢伴\nOpening\nStand By Me\n將冰山劈開\n愛我便說愛我吧\n長藤掛銅鈴\nMedley:\n艷舞台\n烈焰紅唇\nMedley:\n憑甚麼\n假如我是男人\n黑夜的豹\n蔓珠莎華\nOh No! Oh Yes!\nWonderful Night\nFaithfully\n是這樣的\n夢幻的擁抱\n夢姬\n烈女\n心債\n一舞傾情\n約會\n胭脂扣\n床前明月光\n心窩已瘋\n芳華絕代\n床呀！床！\n似水流年\n似是故人來\n抱緊眼前人\n親密愛人\nMedley:\n孤身走我路\n夕陽之歌\nMedley:\n愛將\n壞女孩\n淑女\n妖女\n放開你的頭腦\n夢伴\n冰山大火\nOverture\n夢裡共醉\n是這樣的\n抱緊眼前人\n心肝寶貝\nMedley:\n何日\n李香蘭\n何日 Reprise\n心債\n第四十夜\n夏日戀人\n'O Sole Mio\n親密愛人\nMedley:\n愛情的代價\n我願意\n似夢迷離\n今生今世\n深愛著你\n孤身走我路\n胭脂扣\n似是故人來\n似水流年\nSukiyaki\n花月佳期\n夕陽之歌\nAwards\nNew Talent Singing Awards winner 1982\nTop 10 Jade Solid Gold Best Female Singer Award 1985–1989\nTop 10 Jade Solid Gold Gold Song Gold Award for Sunset Melody () 1989\nHong Kong Film Awards for Best Supporting Actress 1985 for Behind the Yellow Line\nGolden Horse Award for Best Leading Actress 1988 for Rouge\nAsia-Pacific Film Festival Awards for Best Actress 1989 for Rouge\nHong Kong Film Award for Best Actress 1989 for Rouge\nHong Kong Film Awards for Best Supporting Actress 1998 for Eighteen Springs\nGolden Bauhinia Awards for Best Supporting Actress 1998 for Eighteen Springs\nRTHK Golden Needle Award 1998\nGolden Deer Awards for Best Actress 2002 for July Rhapsody\nConcert tours/specials\nFilmography\nTV series"]], "1_corpus": "wikipedia"}
 {"tstamp": 1726510519.7279, "task_type": "retrieval", "type": "share", "models": ["### Model A: BAAI/bge-large-en-v1.5", "### Model B: mixedbread-ai/mxbai-embed-large-v1"], "ip": "", "0_conv_id": "88f9df5b49104d45b110adc5e7827600", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "inference-time scaling", "0_output": [["inference-time scaling", "Title: Patterns of Scalable Bayesian Inference\n\nAbstract: Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with few clear overarching principles. In this paper, we seek to identify unifying principles, patterns, and intuitions for scaling Bayesian inference. We review existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, we characterize the general principles that have proven successful for designing scalable inference procedures and comment on the path forward."]], "0_corpus": "arxiv", "1_conv_id": "e2611d4f43b547b7af3007e43d5db65a", "1_model_name": "mixedbread-ai/mxbai-embed-large-v1", "1_prompt": "inference-time scaling", "1_output": [["inference-time scaling", "Title: Patterns of Scalable Bayesian Inference\n\nAbstract: Datasets are growing not just in size but in complexity, creating a demand for rich models and quantification of uncertainty. Bayesian methods are an excellent fit for this demand, but scaling Bayesian inference is a challenge. In response to this challenge, there has been considerable recent work based on varying assumptions about model structure, underlying computational resources, and the importance of asymptotic correctness. As a result, there is a zoo of ideas with few clear overarching principles. In this paper, we seek to identify unifying principles, patterns, and intuitions for scaling Bayesian inference. We review existing work on utilizing modern computing resources with both MCMC and variational approximation techniques. From this taxonomy of ideas, we characterize the general principles that have proven successful for designing scalable inference procedures and comment on the path forward."]], "1_corpus": "arxiv"}
+{"tstamp": 1726516016.3348, "task_type": "retrieval", "type": "tievote", "models": ["Alibaba-NLP/gte-Qwen2-7B-instruct", "nomic-ai/nomic-embed-text-v1.5"], "ip": "", "0_conv_id": "9a290629cab4402b94abe7f3c973a08e", "0_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "0_prompt": "What is the tallest building?", "0_output": [["What is the tallest building?", "List of tallest buildings and structures\n\nwhether structures built in and rising above water should have their below-water height included in any assessment.\nwhether a structure, building or tower that is guyed is assessed in the same category as self-supporting structures.\nWithin an accepted definition of a building further controversy has included the following factors:\nwhether only habitable height of the building is considered\nwhether communication towers with observation galleries should be considered \"habitable\" in this sense\nwhether rooftop antennas, viewing platforms or any other architecture that does not form a habitable floor should be included in the assessment\nwhether a floor built at a high level of a telecommunications or viewing tower should change the tower's definition to that of a \"building\"\nTallest structures\nThis category does not require the structure to be \"officially\" open, but does require it to be \"topped out\".\nThe tallest artificial structure is Burj Khalifa, a skyscraper in Dubai that reached  in height on January 17, 2009. By April 8, 2008 it had been built higher than the KVLY-TV mast in North Dakota, US. That September it officially surpassed Poland's  Warsaw radio mast, which stood from 1974 to 1991, to become the tallest structure ever built. Guyed lattice towers such as these masts had held the world height record since 1954."]], "0_corpus": "wikipedia", "1_conv_id": "4c959b03506d431493f721066cac35ed", "1_model_name": "nomic-ai/nomic-embed-text-v1.5", "1_prompt": "What is the tallest building?", "1_output": [["What is the tallest building?", "History of the world's tallest buildings\n\nThe tallest building in the world, as of , is the Burj Khalifa in Dubai. The title of \"world's tallest building\" has been held  by various buildings in modern times, including the Lincoln Cathedral in Lincoln, England, and the Empire State Building and the original World Trade Center, both in New York City.\nBefore the modern skyscraper era emerged, between  1311 and 1884 the tallest buildings and structures were mostly Christian churches and cathedrals. Prior to then, the tallest buildings in the world cannot be conclusively determined. For instance, the Lighthouse of Alexandria, which was completed in approximately 280 BC, has been estimated to have been  tall, but its true height is not known. For thousands of years, the Great Pyramid in Egypt was the tallest structure in the world until Lincoln Cathedral of 1311, but the Great Pyramid is not considered a building since it is not habitable. Similarly, the Eiffel Tower was the world's tallest structure from 1889, when it was built, but not the tallest building."]], "1_corpus": "wikipedia"}