Scheduled Commit

data/retrieval_battle-76c7b5f4-5fbc-4311-bf05-8defcdc1ba4e.jsonl

@@ -81,3 +81,5 @@
 {"tstamp": 1723039339.1165, "task_type": "retrieval", "type": "leftvote", "models": ["", ""], "ip": "", "0_conv_id": "80295bed659643e2bf77f8da311dd884", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "Which test was devised to determine whether robots can think?", "0_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)."]], "0_corpus": "wikipedia", "1_conv_id": "85eae3c1152f4540800ece9fcdabfb21", "1_model_name": "BM25", "1_prompt": "Which test was devised to determine whether robots can think?", "1_output": [["Which test was devised to determine whether robots can think?", "Artificial intelligence\n\nIn the late teens and early 2020s, AGI companies began to deliver programs that created enormous interest. In 2015, AlphaGo, developed by DeepMind, beat the world champion Go player. The program was taught only the rules of the game and developed strategy by itself. GPT-3 is a large language model that was released in 2020 by OpenAI and is capable of generating high-quality human-like text. These programs, and others, inspired an aggressive AI boom, where large companies began investing billions in AI research. According to AI Impacts, about $50 billion annually was invested in \"AI\" around 2022 in the U.S. alone and about 20% of the new U.S. Computer Science PhD graduates have specialized in \"AI\".\nAbout 800,000 \"AI\"-related U.S. job openings existed in 2022.\nPhilosophy\nDefining artificial intelligence\nAlan Turing wrote in 1950 \"I propose to consider the question 'can machines think'?\" He advised changing the question from whether a machine \"thinks\", to \"whether or not it is possible for machinery to show intelligent behaviour\". He devised the Turing test, which measures the ability of a machine to simulate human conversation. Since we can only observe the behavior of the machine, it does not matter if it is \"actually\" thinking or literally has a \"mind\". Turing notes that we can not determine these things about other people but \"it is usual to have a polite convention that everyone thinks.\""]], "1_corpus": "wikipedia"}
 {"tstamp": 1723042704.8019, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "8287336f5887464ea4a2397072b74be7", "0_model_name": "Salesforce/SFR-Embedding-2_R", "0_prompt": "Nombre d'habitant annecy", "0_output": [["Nombre d'habitant annecy", "Annecy\n\nAnnecy ( , ) is the prefecture and largest town of the Haute-Savoie department in the Auvergne-Rhône-Alpes region of Southeastern France. It lies on the northern tip of Lake Annecy,  south of Geneva, Switzerland. Nicknamed the \"Pearl of the French Alps\" in Raoul Blanchard's monograph describing its location between lake and mountains, the town  controls the northern entrance to the lake gorge. Due to a lack of available building land between the lake and the protected Semnoz mountain, its population has remained stable, around 50,000 inhabitants, since 1950. However, the 2017 merger with several ex-communes extended the population of the city to 128,199 inhabitants and that of the urban area to 177,622, placing Annecy seventh in the Auvergne-Rhône-Alpes region."]], "0_corpus": "wikipedia", "1_conv_id": "3a0f0866cb6b479eb70787082e944c3a", "1_model_name": "Alibaba-NLP/gte-Qwen2-7B-instruct", "1_prompt": "Nombre d'habitant annecy", "1_output": [["Nombre d'habitant annecy", "Annecy\n\nAnnecy ( , ) is the prefecture and largest town of the Haute-Savoie department in the Auvergne-Rhône-Alpes region of Southeastern France. It lies on the northern tip of Lake Annecy,  south of Geneva, Switzerland. Nicknamed the \"Pearl of the French Alps\" in Raoul Blanchard's monograph describing its location between lake and mountains, the town  controls the northern entrance to the lake gorge. Due to a lack of available building land between the lake and the protected Semnoz mountain, its population has remained stable, around 50,000 inhabitants, since 1950. However, the 2017 merger with several ex-communes extended the population of the city to 128,199 inhabitants and that of the urban area to 177,622, placing Annecy seventh in the Auvergne-Rhône-Alpes region."]], "1_corpus": "wikipedia"}
 {"tstamp": 1723042864.8424, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "f6339e84282d4972bb7c4932db8517f7", "0_model_name": "embed-english-v3.0", "0_prompt": "What are some potentially habitable planets?", "0_output": [["What are some potentially habitable planets?", "List of potentially habitable exoplanets\n\nThe following list include some of the potentially habitable exoplanets discovered so far. It is mostly based on estimates of habitability by the Habitable Worlds Catalog (HWC), and data from the NASA Exoplanet Archive. The HWC is maintained by the Planetary Habitability Laboratory at the University of Puerto Rico at Arecibo. There is also a speculative list being developed of superhabitable planets.\nSurface planetary habitability is thought to require an orbit at the right distance from the host star for liquid surface water to be present, in addition to various geophysical and geodynamical aspects, atmospheric density, radiation type and intensity, and the host star's plasma environment.\nList\nThis is a list of exoplanets within the circumstellar habitable zone that are under 10 Earth masses and smaller than 2.5 Earth radii, and thus have a chance of being rocky. Note that inclusion on this list does not guarantee habitability, and in particular the larger planets are unlikely to have a rocky composition. Earth is included for comparison.\nNote that mass and radius values prefixed with \"~\" have not been measured, but are estimated from a mass-radius relationship.\nEarth and Venus were included for reference.\nPrevious candidates\nSome exoplanet candidates detected by radial velocity that were originally thought to be potentially habitable were later found to most likely be artifacts of stellar activity. These include Gliese 581 d & g, Gliese 667 Ce & f, Gliese 682 b & c, Kapteyn b, and Gliese 832 c."]], "0_corpus": "wikipedia", "1_conv_id": "1313f6aa3fb94c49bc2d365e6d38ec21", "1_model_name": "intfloat/e5-mistral-7b-instruct", "1_prompt": "What are some potentially habitable planets?", "1_output": [["What are some potentially habitable planets?", "List of potentially habitable exoplanets\n\nThe following list include some of the potentially habitable exoplanets discovered so far. It is mostly based on estimates of habitability by the Habitable Worlds Catalog (HWC), and data from the NASA Exoplanet Archive. The HWC is maintained by the Planetary Habitability Laboratory at the University of Puerto Rico at Arecibo. There is also a speculative list being developed of superhabitable planets.\nSurface planetary habitability is thought to require an orbit at the right distance from the host star for liquid surface water to be present, in addition to various geophysical and geodynamical aspects, atmospheric density, radiation type and intensity, and the host star's plasma environment.\nList\nThis is a list of exoplanets within the circumstellar habitable zone that are under 10 Earth masses and smaller than 2.5 Earth radii, and thus have a chance of being rocky. Note that inclusion on this list does not guarantee habitability, and in particular the larger planets are unlikely to have a rocky composition. Earth is included for comparison.\nNote that mass and radius values prefixed with \"~\" have not been measured, but are estimated from a mass-radius relationship.\nEarth and Venus were included for reference.\nPrevious candidates\nSome exoplanet candidates detected by radial velocity that were originally thought to be potentially habitable were later found to most likely be artifacts of stellar activity. These include Gliese 581 d & g, Gliese 667 Ce & f, Gliese 682 b & c, Kapteyn b, and Gliese 832 c."]], "1_corpus": "wikipedia"}
+{"tstamp": 1723044030.564, "task_type": "retrieval", "type": "tievote", "models": ["", ""], "ip": "", "0_conv_id": "37af69d3cb1f421eb64f3c57c1b6add4", "0_model_name": "BAAI/bge-large-en-v1.5", "0_prompt": "How to boil eggs ", "0_output": [["How to boil eggs ", "Boiled egg\n\nBoiled eggs are eggs, typically from a chicken, cooked with their shells unbroken, usually by immersion in boiling water. Hard-boiled eggs are cooked so that the egg white and egg yolk both solidify, while soft-boiled eggs may leave the yolk, and sometimes the white, at least partially liquid and raw. Boiled eggs are a popular breakfast food around the world.\nBesides a boiling water immersion, there are a few different methods to make boiled eggs. Eggs can also be cooked below the boiling temperature, i.e. coddling, or they can be steamed. The egg timer was named for commonly being used to time the boiling of eggs."]], "0_corpus": "wikipedia", "1_conv_id": "0453a61e1d1046788a04a821b5e5a2db", "1_model_name": "sentence-transformers/all-MiniLM-L6-v2", "1_prompt": "How to boil eggs ", "1_output": [["How to boil eggs ", "Boiled egg\n\nBoiled eggs are eggs, typically from a chicken, cooked with their shells unbroken, usually by immersion in boiling water. Hard-boiled eggs are cooked so that the egg white and egg yolk both solidify, while soft-boiled eggs may leave the yolk, and sometimes the white, at least partially liquid and raw. Boiled eggs are a popular breakfast food around the world.\nBesides a boiling water immersion, there are a few different methods to make boiled eggs. Eggs can also be cooked below the boiling temperature, i.e. coddling, or they can be steamed. The egg timer was named for commonly being used to time the boiling of eggs."]], "1_corpus": "wikipedia"}
+{"tstamp": 1723044100.4795, "task_type": "retrieval", "type": "bothbadvote", "models": ["", ""], "ip": "", "0_conv_id": "433be3d608ba410e95d0ba900d1a02c3", "0_model_name": "voyage-multilingual-2", "0_prompt": "are greek and latin related?", "0_output": [["are greek and latin related?", "Tex Stackexchange\n\nQ: Latin Modern and Greek, an issue Here is the code:\n\\documentclass{article}\n\\usepackage[vmargin=1in]{geometry}\n\\usepackage{xfrac,fontspec,unicode-math}\n\\setmathfont[version=lm]{Latin Modern Math}\n\\setmathfont[version=cambria]{Cambria Math}\n\\usepackage{xgreek}\n\n\\begin{document}\n\n\\setmainfont{Latin Modern Roman}\n\\mathversion{lm}\n\\section*{Latin Modern}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\n\\setmainfont{Cambria}\n\\mathversion{cambria}\n\\section*{Cambria, Cambria Math}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\\end{document}\n\nBut in the output the Greek letters are missing, when I use Latin Modern!! In Cambria mode I have no problem with the Greek letters. \n\nA: Latin Modern doesn't support Greek. A similar set of fonts is provided by CMUnicode.\n\\documentclass{article}\n\\usepackage[vmargin=1in]{geometry}\n\\usepackage{unicode-math}\n\n\\setmainfont{CMU Serif}\n\\setmathfont[version=lm]{Latin Modern Math}\n\\setmathfont[version=XITS]{XITS Math}\n\n\\usepackage{xgreek}\n\n\\begin{document}\n\n\\mathversion{lm}\n\\section*{CMU Serif}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\n\\setmainfont{STIX}\n\\mathversion{XITS}\n\\section*{STIX, XITS Math}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\\end{document}\n\n\n"]], "0_corpus": "stackexchange", "1_conv_id": "9cccfab4841849eeb13bf242326da3cb", "1_model_name": "BM25", "1_prompt": "are greek and latin related?", "1_output": [["are greek and latin related?", "English Stackexchange\n\nQ: Plato(n) and similar masculine names What is the etymology of dropped -n in ancient (Greek masculine) names ending with -on?\nI mean Plato, Pluto, etc.\nCuriously, the \"n\" is still preserved in derived words, like platonic or plutonic.\nAnother observation that may be related is that some non-Greek ancient names seemed to acquire -n in languages other than English, e.g., Cato becoming Caton.\n\nA: Because Latin.\nWhen the Ancient Greek names Πλάτων, Πλούτων and others were borrowed into Latin, they were changed into Plato, Pluto. I don't know if there's a single, well-known reason for this, but Latin had a lot of existing third-declension nouns ending in -o, -onis, and these Greek names were easiest to slot into this paradigm. These names then entered English by way of Latin, where they keep the peculiarity of losing the final -n except in derived forms.\n"]], "1_corpus": "stackexchange"}

data/retrieval_individual-76c7b5f4-5fbc-4311-bf05-8defcdc1ba4e.jsonl

@@ -349,3 +349,9 @@
 {"tstamp": 1723042856.4218, "task_type": "retrieval", "type": "chat", "model": "intfloat/e5-mistral-7b-instruct", "gen_params": {}, "start": 1723042856.0821, "finish": 1723042856.4218, "ip": "", "conv_id": "1313f6aa3fb94c49bc2d365e6d38ec21", "model_name": "intfloat/e5-mistral-7b-instruct", "prompt": "What are some potentially habitable planets?", "output": [["What are some potentially habitable planets?", "List of potentially habitable exoplanets\n\nThe following list include some of the potentially habitable exoplanets discovered so far. It is mostly based on estimates of habitability by the Habitable Worlds Catalog (HWC), and data from the NASA Exoplanet Archive. The HWC is maintained by the Planetary Habitability Laboratory at the University of Puerto Rico at Arecibo. There is also a speculative list being developed of superhabitable planets.\nSurface planetary habitability is thought to require an orbit at the right distance from the host star for liquid surface water to be present, in addition to various geophysical and geodynamical aspects, atmospheric density, radiation type and intensity, and the host star's plasma environment.\nList\nThis is a list of exoplanets within the circumstellar habitable zone that are under 10 Earth masses and smaller than 2.5 Earth radii, and thus have a chance of being rocky. Note that inclusion on this list does not guarantee habitability, and in particular the larger planets are unlikely to have a rocky composition. Earth is included for comparison.\nNote that mass and radius values prefixed with \"~\" have not been measured, but are estimated from a mass-radius relationship.\nEarth and Venus were included for reference.\nPrevious candidates\nSome exoplanet candidates detected by radial velocity that were originally thought to be potentially habitable were later found to most likely be artifacts of stellar activity. These include Gliese 581 d & g, Gliese 667 Ce & f, Gliese 682 b & c, Kapteyn b, and Gliese 832 c."]], "corpus": "wikipedia"}
 {"tstamp": 1723042889.53, "task_type": "retrieval", "type": "chat", "model": "embed-english-v3.0", "gen_params": {}, "start": 1723042887.3816, "finish": 1723042889.53, "ip": "", "conv_id": "9d7f11c7e44b43889919d497ca0bd560", "model_name": "embed-english-v3.0", "prompt": "I am searching for a good and large-scale benchmark for testing the performance of video embeddings.", "output": [["I am searching for a good and large-scale benchmark for testing the performance of video embeddings.", "Title: Playing for Benchmarks\n\nAbstract: We present a benchmark suite for visual perception. The benchmark is based on more than 250K high-resolution video frames, all annotated with ground-truth data for both low-level and high-level vision tasks, including optical flow, semantic instance segmentation, object detection and tracking, object-level 3D scene layout, and visual odometry. Ground-truth data for all tasks is available for every frame. The data was collected while driving, riding, and walking a total of 184 kilometers in diverse ambient conditions in a realistic virtual world. To create the benchmark, we have developed a new approach to collecting ground-truth data from simulated worlds without access to their source code or content. We conduct statistical analyses that show that the composition of the scenes in the benchmark closely matches the composition of corresponding physical environments. The realism of the collected data is further validated via perceptual experiments. We analyze the performance of state-of-the-art methods for multiple tasks, providing reference baselines and highlighting challenges for future research. The supplementary video can be viewed at https://youtu.be/T9OybWv923Y"]], "corpus": "arxiv"}
 {"tstamp": 1723042889.53, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723042887.3816, "finish": 1723042889.53, "ip": "", "conv_id": "3e37d217c108450e97fe1cbd927d4927", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "I am searching for a good and large-scale benchmark for testing the performance of video embeddings.", "output": [["I am searching for a good and large-scale benchmark for testing the performance of video embeddings.", "Title: A Model for Managing Collections of Patterns\n\nAbstract: Data mining algorithms are now able to efficiently deal with huge amount of data. Various kinds of patterns may be discovered and may have some great impact on the general development of knowledge. In many domains, end users may want to have their data mined by data mining tools in order to extract patterns that could impact their business. Nevertheless, those users are often overwhelmed by the large quantity of patterns extracted in such a situation. Moreover, some privacy issues, or some commercial one may lead the users not to be able to mine the data by themselves. Thus, the users may not have the possibility to perform many experiments integrating various constraints in order to focus on specific patterns they would like to extract. Post processing of patterns may be an answer to that drawback. Thus, in this paper we present a framework that could allow end users to manage collections of patterns. We propose to use an efficient data structure on which some algebraic operators may be used in order to retrieve or access patterns in pattern bases."]], "corpus": "arxiv"}
+{"tstamp": 1723044015.6734, "task_type": "retrieval", "type": "chat", "model": "BAAI/bge-large-en-v1.5", "gen_params": {}, "start": 1723044013.4843, "finish": 1723044015.6734, "ip": "", "conv_id": "37af69d3cb1f421eb64f3c57c1b6add4", "model_name": "BAAI/bge-large-en-v1.5", "prompt": "How to boil eggs ", "output": [["How to boil eggs ", "Boiled egg\n\nBoiled eggs are eggs, typically from a chicken, cooked with their shells unbroken, usually by immersion in boiling water. Hard-boiled eggs are cooked so that the egg white and egg yolk both solidify, while soft-boiled eggs may leave the yolk, and sometimes the white, at least partially liquid and raw. Boiled eggs are a popular breakfast food around the world.\nBesides a boiling water immersion, there are a few different methods to make boiled eggs. Eggs can also be cooked below the boiling temperature, i.e. coddling, or they can be steamed. The egg timer was named for commonly being used to time the boiling of eggs."]], "corpus": "wikipedia"}
+{"tstamp": 1723044015.6734, "task_type": "retrieval", "type": "chat", "model": "sentence-transformers/all-MiniLM-L6-v2", "gen_params": {}, "start": 1723044013.4843, "finish": 1723044015.6734, "ip": "", "conv_id": "0453a61e1d1046788a04a821b5e5a2db", "model_name": "sentence-transformers/all-MiniLM-L6-v2", "prompt": "How to boil eggs ", "output": [["How to boil eggs ", "Boiled egg\n\nBoiled eggs are eggs, typically from a chicken, cooked with their shells unbroken, usually by immersion in boiling water. Hard-boiled eggs are cooked so that the egg white and egg yolk both solidify, while soft-boiled eggs may leave the yolk, and sometimes the white, at least partially liquid and raw. Boiled eggs are a popular breakfast food around the world.\nBesides a boiling water immersion, there are a few different methods to make boiled eggs. Eggs can also be cooked below the boiling temperature, i.e. coddling, or they can be steamed. The egg timer was named for commonly being used to time the boiling of eggs."]], "corpus": "wikipedia"}
+{"tstamp": 1723044059.9137, "task_type": "retrieval", "type": "chat", "model": "voyage-multilingual-2", "gen_params": {}, "start": 1723044057.4645, "finish": 1723044059.9137, "ip": "", "conv_id": "433be3d608ba410e95d0ba900d1a02c3", "model_name": "voyage-multilingual-2", "prompt": "are greek and latin related?", "output": [["are greek and latin related?", "Tex Stackexchange\n\nQ: Latin Modern and Greek, an issue Here is the code:\n\\documentclass{article}\n\\usepackage[vmargin=1in]{geometry}\n\\usepackage{xfrac,fontspec,unicode-math}\n\\setmathfont[version=lm]{Latin Modern Math}\n\\setmathfont[version=cambria]{Cambria Math}\n\\usepackage{xgreek}\n\n\\begin{document}\n\n\\setmainfont{Latin Modern Roman}\n\\mathversion{lm}\n\\section*{Latin Modern}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\n\\setmainfont{Cambria}\n\\mathversion{cambria}\n\\section*{Cambria, Cambria Math}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\\end{document}\n\nBut in the output the Greek letters are missing, when I use Latin Modern!! In Cambria mode I have no problem with the Greek letters. \n\nA: Latin Modern doesn't support Greek. A similar set of fonts is provided by CMUnicode.\n\\documentclass{article}\n\\usepackage[vmargin=1in]{geometry}\n\\usepackage{unicode-math}\n\n\\setmainfont{CMU Serif}\n\\setmathfont[version=lm]{Latin Modern Math}\n\\setmathfont[version=XITS]{XITS Math}\n\n\\usepackage{xgreek}\n\n\\begin{document}\n\n\\mathversion{lm}\n\\section*{CMU Serif}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\n\\setmainfont{STIX}\n\\mathversion{XITS}\n\\section*{STIX, XITS Math}\nThis is a greek text Ελληνικό Κείμενο\n$\\cos φ$\n\\end{document}\n\n\n"]], "corpus": "stackexchange"}
+{"tstamp": 1723044059.9137, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1723044057.4645, "finish": 1723044059.9137, "ip": "", "conv_id": "9cccfab4841849eeb13bf242326da3cb", "model_name": "BM25", "prompt": "are greek and latin related?", "output": [["are greek and latin related?", "English Stackexchange\n\nQ: Plato(n) and similar masculine names What is the etymology of dropped -n in ancient (Greek masculine) names ending with -on?\nI mean Plato, Pluto, etc.\nCuriously, the \"n\" is still preserved in derived words, like platonic or plutonic.\nAnother observation that may be related is that some non-Greek ancient names seemed to acquire -n in languages other than English, e.g., Cato becoming Caton.\n\nA: Because Latin.\nWhen the Ancient Greek names Πλάτων, Πλούτων and others were borrowed into Latin, they were changed into Plato, Pluto. I don't know if there's a single, well-known reason for this, but Latin had a lot of existing third-declension nouns ending in -o, -onis, and these Greek names were easiest to slot into this paradigm. These names then entered English by way of Latin, where they keep the peculiarity of losing the final -n except in derived forms.\n"]], "corpus": "stackexchange"}
+{"tstamp": 1723044115.9674, "task_type": "retrieval", "type": "chat", "model": "mixedbread-ai/mxbai-embed-large-v1", "gen_params": {}, "start": 1723044114.3086, "finish": 1723044115.9674, "ip": "", "conv_id": "dd55ede43ec043c2afde18ebd3aeb227", "model_name": "mixedbread-ai/mxbai-embed-large-v1", "prompt": "Accuracy of text classification algorithms in identifying fake Covid-19 news", "output": [["Accuracy of text classification algorithms in identifying fake Covid-19 news", "Title: Constraint 2021: Machine Learning Models for COVID-19 Fake News Detection Shared Task\n\nAbstract: In this system paper we present our contribution to the Constraint 2021 COVID-19 Fake News Detection Shared Task, which poses the challenge of classifying COVID-19 related social media posts as either fake or real. In our system, we address this challenge by applying classical machine learning algorithms together with several linguistic features, such as n-grams, readability, emotional tone and punctuation. In terms of pre-processing, we experiment with various steps like stop word removal, stemming/lemmatization, link removal and more. We find our best performing system to be based on a linear SVM, which obtains a weighted average F1 score of 95.19% on test data, which lands a place in the middle of the leaderboard (place 80 of 167)."]], "corpus": "arxiv"}
+{"tstamp": 1723044115.9674, "task_type": "retrieval", "type": "chat", "model": "BM25", "gen_params": {}, "start": 1723044114.3086, "finish": 1723044115.9674, "ip": "", "conv_id": "e8fb15ecba234bf9aaedad6c250a0f8f", "model_name": "BM25", "prompt": "Accuracy of text classification algorithms in identifying fake Covid-19 news", "output": [["Accuracy of text classification algorithms in identifying fake Covid-19 news", "Title: Evaluating Deep Learning Approaches for Covid19 Fake News Detection\n\nAbstract: Social media platforms like Facebook, Twitter, and Instagram have enabled connection and communication on a large scale. It has revolutionized the rate at which information is shared and enhanced its reach. However, another side of the coin dictates an alarming story. These platforms have led to an increase in the creation and spread of fake news. The fake news has not only influenced people in the wrong direction but also claimed human lives. During these critical times of the Covid19 pandemic, it is easy to mislead people and make them believe in fatal information. Therefore it is important to curb fake news at source and prevent it from spreading to a larger audience. We look at automated techniques for fake news detection from a data mining perspective. We evaluate different supervised text classification algorithms on Contraint@AAAI 2021 Covid-19 Fake news detection dataset. The classification algorithms are based on Convolutional Neural Networks (CNN), Long Short Term Memory (LSTM), and Bidirectional Encoder Representations from Transformers (BERT). We also evaluate the importance of unsupervised learning in the form of language model pre-training and distributed word representations using unlabelled covid tweets corpus. We report the best accuracy of 98.41\\% on the Covid-19 Fake news detection dataset."]], "corpus": "arxiv"}