‘ML dataset’ tag

Annotations sorted by machine learning into inferred 'tags'. This provides an alternative way to browse: instead of by date order, one can browse in topic order. The 'sorted' list has been automatically clustered into multiple sections & auto-labeled for easier browsing.

Beginning with the newest annotation, it uses the embedding of each annotation to attempt to create a list of nearest-neighbor annotations, creating a progression of topics. For more details, see the link.

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Miscellaneous

Bibliography

2025-johri.pdf: “An Evaluation Framework for Clinical Use of Large Language Models in Patient Interaction Tasks”, Shreya Johri, Jaehwan Jeong, Benjamin A. Tran, Daniel I. Schlessinger, Shannon Wongvibulsin, Leandra A. Barnes, Hong-Yu Zhou, Zhuo Ran Cai, Eliezer M. Van Allen, David Kim, Roxana Daneshjou, Pranav Rajpurkar

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https://arxiv.org/abs/2411.13543: “BALROG: Benchmarking Agentic LLM and VLM Reasoning On Games”, Davide Paglieri, Bartłomiej Cupiał, Samuel Coward, Ulyana Piterbarg, Maciej Wolczyk, Akbir Khan, Eduardo Pignatelli, Łukasz Kuciński, Lerrel Pinto, Rob Fergus, Jakob Nicolaus Foerster, Jack Parker-Holder, Tim Rocktäschel

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https://arxiv.org/abs/2410.07095#openai: “MLE-Bench: Evaluating Machine Learning Agents on Machine Learning Engineering”, Jun Shern Chan, Neil Chowdhury, Oliver Jaffe, James Aung, Dane Sherburn, Evan Mays, Giulio Starace, Kevin Liu, Leon Maksin, Tejal Patwardhan, Lilian Weng, Aleksander Madry

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https://arxiv.org/abs/2407.20020: “ImagiNet: A Multi-Content Dataset for Generalizable Synthetic Image Detection via Contrastive Learning”, Delyan Boychev, Radostin Cholakov

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https://arxiv.org/abs/2407.04694: “Me, Myself, and AI: The Situational Awareness Dataset (SAD) for LLMs”, Rudolf Laine, Bilal Chughtai, Jan Betley, Kaivalya Hariharan, Jeremy Scheurer, Mikita Balesni, Marius Hobbhahn, Alexander Meinke, Owain Evans

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https://arxiv.org/abs/2407.04108: “Future Events As Backdoor Triggers: Investigating Temporal Vulnerabilities in LLMs”, Sara Price, Arjun Panickssery, Samuel R. Bowman, Asa Cooper Stickland

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https://arxiv.org/abs/2406.18906: “Sonnet or Not, Bot? Poetry Evaluation for Large Models and Datasets”, Melanie Walsh, Anna Preus, Maria Antoniak

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https://arxiv.org/abs/2406.18518#salesforce: “APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets”, Zuxin Liu, Thai Hoang, Jianguo Zhang, Ming Zhu, Tian Lan, Shirley Kokane, Juntao Tan, Weiran Yao, Zhiwei Liu, Yihao Feng, Rithesh Murthy, Liangwei Yang, Silvio Savarese, Juan Carlos Niebles, Huan Wang, Shelby Heinecke, Caiming Xiong

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https://arxiv.org/abs/2406.13121#google: “Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More?”, Jinhyuk Lee, Anthony Chen, Zhuyun Dai, Dheeru Dua, Devendra Singh Sachan, Michael Boratko, Yi Luan, Sébastien M. R. Arnold, Vincent Perot, Siddharth Dalmia, Hexiang Hu, Xudong Lin, Panupong Pasupat, Aida Amini, Jeremy R. Cole, Sebastian Riedel, Iftekhar Naim, Ming-Wei Chang, Kelvin Guu

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https://arxiv.org/abs/2406.11794: “DataComp-LM: In Search of the next Generation of Training Sets for Language Models”, Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Chandu, Thao Nguyen, Igor Vasiljevic, Sham Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar

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https://arxiv.org/abs/2405.18870#google: “LLMs Achieve Adult Human Performance on Higher-Order Theory of Mind Tasks”, Winnie Street, John Oliver Siy, Geoff Keeling, Adrien Baranes, Benjamin Barnett, Michael McKibben, Tatenda Kanyere, Alison Lentz, Blaise Aguera y Arcas, Robin I. M. Dunbar

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https://arxiv.org/abs/2405.15306: “DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches With TikZ”, Jonas Belouadi, Simone Paolo Ponzetto, Steffen Eger

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https://arxiv.org/abs/2405.02793#google: “ImageInWords: Unlocking Hyper-Detailed Image Descriptions”, Roopal Garg, Andrea Burns, Burcu Karagol Ayan, Yonatan Bitton, Ceslee Montgomery, Yasumasa Onoe, Andrew Bunner, Ranjay Krishna, Jason Baldridge, Radu Soricut

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https://arxiv.org/abs/2405.00332#scale: “GSM1k: A Careful Examination of Large Language Model Performance on Grade School Arithmetic”, Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, Will Song, Tiffany Zhao, Pranav Raja, Dylan Slack, Qin Lyu, Sean Hendryx, Russell Kaplan, Michele Lunati, Summer Yue

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https://arxiv.org/abs/2404.06664: “CulturalTeaming: AI-Assisted Interactive Red-Teaming for Challenging LLMs’ (Lack Of) Multicultural Knowledge”, Yu Ying Chiu, Liwei Jiang, Maria Antoniak, Chan Young Park, Shuyue Stella Li, Mehar Bhatia, Sahithya Ravi, Yulia Tsvetkov, Vered Shwartz, Yejin Choi

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https://arxiv.org/abs/2404.05955: “VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?”, Junpeng Liu, Yifan Song, Bill Yuchen Lin, Wai Lam, Graham Neubig, Yuanzhi Li, Xiang Yue

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https://www.nytimes.com/2024/04/06/technology/tech-giants-harvest-data-artificial-intelligence.html: “How Tech Giants Cut Corners to Harvest Data for AI: OpenAI, Google and Meta Ignored Corporate Policies, Altered Their Own Rules and Discussed Skirting Copyright Law As They Sought Online Information to Train Their Newest Artificial Intelligence Systems”, Cade Metz, Cecilia Kang, Sheera Frenkel, Stuart A. Thompson, Nico Grant

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https://arxiv.org/abs/2404.01291: “Evaluating Text-To-Visual Generation With Image-To-Text Generation”, Zhiqiu Lin, Deepak Pathak, Baiqi Li, Jiayao Li, Xide Xia, Graham Neubig, Pengchuan Zhang, Deva Ramanan

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https://arxiv.org/abs/2403.18624: “Vulnerability Detection With Code Language Models: How Far Are We?”, Yangruibo Ding, Yanjun Fu, Omniyyah Ibrahim, Chawin Sitawarin, Xinyun Chen, Basel Alomair, David Wagner, Baishakhi Ray, Yizheng Chen

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https://arxiv.org/abs/2403.18802#deepmind: “Long-Form Factuality in Large Language Models”, Jerry Wei, Chengrun Yang, Xinying Song, Yifeng Lu, Nathan Hu, Jie Huang, Dustin Tran, Daiyi Peng, Ruibo Liu, Da Huang, Cosmo Du, Quoc V. Le

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https://arxiv.org/abs/2402.11753: “ArtPrompt: ASCII Art-Based Jailbreak Attacks against Aligned LLMs”, Fengqing Jiang, Zhangchen Xu, Luyao Niu, Zhen Xiang, Bhaskar Ramasubramanian, Bo Li, Radha Poovendran

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https://arxiv.org/abs/2312.11556: “StarVector: Generating Scalable Vector Graphics Code from Images”, Juan A. Rodriguez, Shubham Agarwal, Issam H. Laradji, Pau Rodriguez, David Vazquez, Christopher Pal, Marco Pedersoli

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https://arxiv.org/abs/2312.06281: “EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models”, Samuel J. Paech

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https://arxiv.org/abs/2311.13657: “Efficient Transformer Knowledge Distillation: A Performance Review”, Nathan Brown, Ashton Williamson, Tahj Anderson, Logan Lawrence

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https://arxiv.org/abs/2310.16825: “CommonCanvas: An Open Diffusion Model Trained With Creative-Commons Images”, Aaron Gokaslan, A. Feder Cooper, Jasmine Collins, Landan Seguin, Austin Jacobson, Mihir Patel, Jonathan Frankle, Cory Stephenson, Volodymyr Kuleshov

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https://arxiv.org/abs/2310.06786: “OpenWebMath: An Open Dataset of High-Quality Mathematical Web Text”, Keiran Paster, Marco Dos Santos, Zhangir Azerbayev, Jimmy Ba

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https://arxiv.org/abs/2310.03214#google: “FreshLLMs: Refreshing Large Language Models With Search Engine Augmentation”, Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc Le, Thang Luong

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https://arxiv.org/abs/2310.01377: “UltraFeedback: Boosting Language Models With High-Quality Feedback”, Ganqu Cui, Lifan Yuan, Ning Ding, Guanming Yao, Wei Zhu, Yuan Ni, Guotong Xie, Zhiyuan Liu, Maosong Sun

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https://arxiv.org/abs/2309.16671: “Demystifying CLIP Data”, Hu Xu, Saining Xie, Xiaoqing Ellen Tan, Po-Yao Huang, Russell Howes, Vasu Sharma, Shang-Wen Li, Gargi Ghosh, Luke Zettlemoyer, Christoph Feichtenhofer

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https://arxiv.org/abs/2309.12269: “The Cambridge Law Corpus: A Corpus for Legal AI Research”, Andreas Östling, Holli Sargeant, Huiyuan Xie, Ludwig Bull, Alexander Terenin, Leif Jonsson, Måns Magnusson, Felix Steffek

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https://arxiv.org/abs/2309.12284: “MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models”, Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu

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https://arxiv.org/abs/2309.10818#cerebras: “SlimPajama-DC: Understanding Data Combinations for LLM Training”, Zhiqiang Shen, Tianhua Tao, Liqun Ma, Willie Neiswanger, Zhengzhong Liu, Hongyi Wang, Bowen Tan, Joel Hestness, Natalia Vassilieva, Daria Soboleva, Eric Xing

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https://arxiv.org/abs/2309.04269: “From Sparse to Dense: GPT-4 Summarization With Chain of Density (CoD) Prompting”, Griffin Adams, Alexander Fabbri, Faisal Ladhak, Eric Lehman, Noémie Elhadad

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https://arxiv.org/abs/2308.12477: “American Stories: A Large-Scale Structured Text Dataset of Historical U.S. Newspapers”, Melissa Dell, Jacob Carlson, Tom Bryan, Emily Silcock, Abhishek Arora, Zejiang Shen, Luca D’Amico-Wong, Quan Le, Pablo Querubin, Leander Heldring

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https://arxiv.org/abs/2307.08701#samsung: “AlpaGasus: Training A Better Alpaca With Fewer Data”, Lichang Chen, Shiyang Li, Jun Yan, Hai Wang, Kalpa Gunaratna, Vikas Yadav, Zheng Tang, Vijay Srinivasan, Tianyi Zhou, Heng Huang, Hongxia Jin

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https://arxiv.org/abs/2307.05014: “Test-Time Training on Video Streams”, Renhao Wang, Yu Sun, Yossi Gandelsman, Xinlei Chen, Alexei A. Efros, Xiaolong Wang

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https://arxiv.org/abs/2306.15626: “LeanDojo: Theorem Proving With Retrieval-Augmented Language Models”, Kaiyu Yang, Aidan M. Swope, Alex Gu, Rahul Chalamala, Peiyang Song, Shixing Yu, Saad Godil, Ryan Prenger, Anima Anandkumar

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https://arxiv.org/abs/2306.12587: “ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews”, Mike D’Arcy, Alexis Ross, Erin Bransom, Bailey Kuehl, Jonathan Bragg, Tom Hope, Doug Downey

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https://arxiv.org/abs/2306.15448: “Understanding Social Reasoning in Language Models With Language Models”, Kanishk Gandhi, Jan-Philipp Fränken, Tobias Gerstenberg, Noah D. Goodman

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https://www.theverge.com/features/23764584/ai-artificial-intelligence-data-notation-labor-scale-surge-remotasks-openai-chatbots: “AI Is a Lot of Work: As the Technology Becomes Ubiquitous, a Vast Tasker Underclass Is Emerging—And Not Going Anywhere”, Josh Dzieza

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2023-yi.pdf: “Anime Character Identification and Tag Prediction by Multimodality Modeling: Dataset and Model”, Fan Yi, Jiaxiang Wu, Minyi Zhao, Shuigeng Zhou

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https://www.theinformation.com/articles/why-youtube-could-give-google-an-edge-in-ai: “Why YouTube Could Give Google an Edge in AI”, Jon Victor

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https://arxiv.org/abs/2305.20050#openai: “Let’s Verify Step by Step”, Hunter Lightman, Vineet Kosaraju, Yura Burda, Harri Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, Karl Cobbe

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https://arxiv.org/abs/2305.07759#microsoft: “TinyStories: How Small Can Language Models Be and Still Speak Coherent English?”, Ronen Eldan, Yuanzhi Li

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https://arxiv.org/abs/2305.01569: “Pick-A-Pic: An Open Dataset of User Preferences for Text-To-Image Generation”, Yuval Kirstain, Adam Polyak, Uriel Singer, Shahbuland Matiana, Joe Penna, Omer Levy

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https://arxiv.org/abs/2304.05538: “ImageNet-Hard: The Hardest Images Remaining from a Study of the Power of Zoom and Spatial Biases in Image Classification”, Mohammad Reza Taesiri, Giang Nguyen, Sarra Habchi, Cor-Paul Bezemer, Anh Nguyen

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https://arxiv.org/abs/2304.02015#alibaba: “How Well Do Large Language Models Perform in Arithmetic Tasks?”, Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang, Songfang Huang

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https://arxiv.org/abs/2302.14520: “Large Language Models Are State-Of-The-Art Evaluators of Translation Quality”, Tom Kocmi, Christian Federmann

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https://arxiv.org/abs/2302.03169: “Data Selection for Language Models via Importance Resampling”, Sang Michael Xie, Shibani Santurkar, Tengyu Ma, Percy Liang

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https://arxiv.org/abs/2212.13138#google: “Med-PaLM: Large Language Models Encode Clinical Knowledge”, Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Scharli, Aakanksha Chowdhery, Philip Mansfield, Blaise Aguera y Arcas, Dale Webster, Greg S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan

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https://arxiv.org/abs/2212.03533#microsoft: “Text Embeddings by Weakly-Supervised Contrastive Pre-Training”, Liang Wang, Nan Yang, Xiaolong Huang, Binxing Jiao, Linjun Yang, Daxin Jiang, Rangan Majumder, Furu Wei

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https://arxiv.org/abs/2211.15533: “The Stack: 3 TB of Permissively Licensed Source Code”, Denis Kocetkov, Raymond Li, Loubna Ben Allal, Jia Li, Chenghao Mou, Carlos Muñoz Ferrandis, Yacine Jernite, Margaret Mitchell, Sean Hughes, Thomas Wolf, Dzmitry Bahdanau, Leandro von Werra, Harm de Vries

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https://arxiv.org/abs/2211.06679#baai: “AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities”, Zhongzhi Chen, Guang Liu, Bo-Wen Zhang, Fulong Ye, Qinghong Yang, Ledell Wu

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https://arxiv.org/abs/2211.01786: “BLOOMZ/mT0: Crosslingual Generalization through Multitask Finetuning”, Niklas Muennighoff, Thomas Wang, Lintang Sutawika, Adam Roberts, Stella Biderman, Teven Le Scao, M. Saiful Bari, Sheng Shen, Zheng-Xin Yong, Hailey Schoelkopf, Xiangru Tang, Dragomir Radev, Alham Fikri Aji, Khalid Almubarak, Samuel Albanie, Zaid Alyafeai, Albert Webson, Edward Raff, Colin Raffel

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https://arxiv.org/abs/2210.11610#google: “Large Language Models Can Self-Improve”, Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han

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https://arxiv.org/abs/2210.07792#eleutherai: “CARP: Robust Preference Learning for Storytelling via Contrastive Reinforcement Learning”, Louis Castricato, Alexander Havrilla, Shahbul, Matiana, Michael Pieler, Anbang Ye, Ian Yang, Spencer Frazier, Mark Riedl

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https://aclanthology.org/2022.cai-1.2.pdf: “Most Language Models Can Be Poets Too: An AI Writing Assistant and Constrained Text Generation Studio”, Allen Roush, Sanjay Basu, Akshay Moorthy, Dmitry Dubovoy

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https://arxiv.org/abs/2210.03350#allen: “Self-Ask: Measuring and Narrowing the Compositionality Gap in Language Models (Bamboogle)”, Ofir Press, Muru Zhang, Sewon Min, Ludwig Schmidt, Noah A. Smith, Mike Lewis

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https://arxiv.org/abs/2209.00840: “FOLIO: Natural Language Reasoning With First-Order Logic”, Simeng Han, Hailey Schoelkopf, Yilun Zhao, Zhenting Qi, Martin Riddell, Luke Benson, Lucy Sun, Ekaterina Zubova, Yujie Qiao, Matthew Burtell, David Peng, Jonathan Fan, Yixin Liu, Brian Wong, Malcolm Sailor, Ansong Ni, Linyong Nan, Jungo Kasai, Tao Yu, Rui Zhang, Shafiq Joty, Alexander R. Fabbri, Wojciech Kryscinski, Xi Victoria Lin, Caiming Xiong, Dragomir Radev

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https://www.anthropic.com/red_teaming.pdf: “Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned”, Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, Andy L. Jones, Samuel R. Bowman, Anna Chen, Tom Conerly, Nova DasSarma, Dawn Drain, Nelson Elhage, Sheer El-Showk, Stanislav Fort, Zac Hatfield Dodds, Tom Henighan, Danny Hernandez, Tristan Hume, Josh Jacobson, Scott Johnston, Shauna Kravec, Catherine Olsson, Sam Ringer, Eli Tran-Johnson, Dario Amodei, Tom Brown, Nicholas Joseph, Sam McCandlish, Chris Olah, Jared Kaplan, Jack Clark

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https://arxiv.org/abs/2208.08831#deepmind: “Discovering Bugs in Vision Models Using Off-The-Shelf Image Generation and Captioning”, Olivia Wiles, Isabela Albuquerque, Sven Gowal

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https://arxiv.org/abs/2208.05516: “Quality Not Quantity: On the Interaction between Dataset Design and Robustness of CLIP”, Thao Nguyen, Gabriel Ilharco, Mitchell Wortsman, Sewoong Oh, Ludwig Schmidt

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https://arxiv.org/abs/2207.13061: “NewsStories: Illustrating Articles With Visual Summaries”, Reuben Tan, Bryan A. Plummer, Kate Saenko, J. P. Lewis, Avneesh Sud, Thomas Leung

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https://arxiv.org/abs/2206.15474: “Forecasting Future World Events With Neural Networks”, Andy Zou, Tristan Xiao, Ryan Jia, Joe Kwon, Mantas Mazeika, Richard Li, Dawn Song, Jacob Steinhardt, Owain Evans, Dan Hendrycks

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https://arxiv.org/abs/2205.09665#bair: “Automated Crossword Solving”, Eric Wallace, Nicholas Tomlin, Albert Xu, Kevin Yang, Eshaan Pathak, Matthew Ginsberg, Dan Klein

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https://arxiv.org/abs/2205.09073#google: “Dialog Inpainting: Turning Documents into Dialogues”, Zhuyun Dai, Arun Tejasvi Chaganty, Vincent Zhao, Aida Amini, Qazi Mamunur Rashid, Mike Green, Kelvin Guu

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https://arxiv.org/abs/2205.03983#google: “Building Machine Translation Systems for the Next Thousand Languages”, Ankur Bapna, Isaac Caswell, Julia Kreutzer, Orhan Firat, Daan van Esch, Aditya Siddhant, Mengmeng Niu, Pallavi Baljekar, Xavier Garcia, Wolfgang Macherey, Theresa Breiner, Vera Axelrod, Jason Riesa, Yuan Cao, Mia Xu Chen, Klaus Macherey, Maxim Krikun, Pidong Wang, Alexander Gutkin, Apurva Shah, Yanping Huang, Zhifeng Chen, Yonghui Wu, Macduff Hughes

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https://arxiv.org/abs/2205.04596#google: “When Does Dough Become a Bagel? Analyzing the Remaining Mistakes on ImageNet”, Vijay Vasudevan, Benjamin Caine, Raphael Gontijo-Lopes, Sara Fridovich-Keil, Rebecca Roelofs

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https://arxiv.org/abs/2205.01397: “Data Determines Distributional Robustness in Contrastive Language Image Pre-Training (CLIP)”, Alex Fang, Gabriel Ilharco, Mitchell Wortsman, Yuhao Wan, Vaishaal Shankar, Achal Dave, Ludwig Schmidt

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https://arxiv.org/abs/2204.07705: “Tk-Instruct: Benchmarking Generalization via In-Context Instructions on 1,600+ Language Tasks”, Yizhong Wang, Swaroop Mishra, Pegah Alipoormolabashi, Yeganeh Kordi, Amirreza Mirzaei, Anjana Arunkumar, Arjun Ashok, Arut Selvan Dhanasekaran, Atharva Naik, David Stap, Eshaan Pathak, Giannis Karamanolakis, Haizhi Gary Lai, Ishan Purohit, Ishani Mondal, Jacob Anderson, Kirby Kuznia, Krima Doshi, Maitreya Patel, Kuntal Kumar Pal, Mehrad Moradshahi, Mihir Parmar, Mirali Purohit, Neeraj Varshney, Phani Rohitha Kaza, Pulkit Verma, Ravsehaj Singh Puri, Rushang Karia, Shailaja Keyur Sampat, Savan Doshi, Siddhartha Mishra, Sujan Reddy, Sumanta Patro, Tanay Dixit, Xudong Shen, Chitta Baral, Yejin Choi, Noah A. Smith, Hannaneh Hajishirzi, Daniel Khashabi

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https://arxiv.org/abs/2204.03067: “ByT5 Model for Massively Multilingual Grapheme-To-Phoneme Conversion”, Jian Zhu, Cong Zhang, David Jurgens

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https://arxiv.org/abs/2203.11096: “CLIP Meets GamePhysics: Towards Bug Identification in Gameplay Videos Using Zero-Shot Transfer Learning”, Mohammad Reza Taesiri, Finlay Macklon, Cor-Paul Bezemer

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https://arxiv.org/abs/2202.12211#google: “Self-Distilled StyleGAN: Towards Generation from Internet Photos”, Ron Mokady, Michal Yarom, Omer Tov, Oran Lang, Daniel Cohen-Or, Tali Dekel, Michal Irani, Inbar Mosseri

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https://arxiv.org/abs/2202.06767#huawei: “Wukong: 100 Million Large-Scale Chinese Cross-Modal Pre-Training Dataset and A Foundation Framework”, Jiaxi Gu, Xiaojun Meng, Guansong Lu, Lu Hou, Minzhe Niu, Hang Xu, Xiaodan Liang, Wei Zhang, Xin Jiang, Chunjing Xu

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https://arxiv.org/abs/2202.00273: “StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets”, Axel Sauer, Katja Schwarz, Andreas Geiger

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https://arxiv.org/abs/2201.12086#salesforce: “BLIP: Bootstrapping Language-Image Pre-Training for Unified Vision-Language Understanding and Generation”, Junnan Li, Dongxu Li, Caiming Xiong, Steven Hoi

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https://arxiv.org/abs/2201.08371#facebook: “SWAG: Revisiting Weakly Supervised Pre-Training of Visual Perception Models”, Mannat Singh, Laura Gustafson, Aaron Adcock, Vinicius de Freitas Reis, Bugra Gedik, Raj Prateek Kosaraju, Dhruv Mahajan, Ross Girshick, Piotr Dollár, Laurens van der Maaten

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https://swabhs.com/assets/pdf/wanli.pdf#allen: “WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation”, Alisa Liu, Swabha Swayamdipta, Noah A. Smith, Yejin Choi

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https://arxiv.org/abs/2201.04684: “BigDatasetGAN: Synthesizing ImageNet With Pixel-Wise Annotations”, Daiqing Li, Huan Ling, Seung Wook Kim, Karsten Kreis, Adela Barriuso, Sanja Fidler, Antonio Torralba

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https://arxiv.org/abs/2112.15283#baidu: “ERNIE-ViLG: Unified Generative Pre-Training for Bidirectional Vision-Language Generation”, Han Zhang, Weichong Yin, Yewei Fang, Lanxin Li, Boqiang Duan, Zhihua Wu, Yu Sun, Hao Tian, Hua Wu, Haifeng Wang

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https://arxiv.org/abs/2112.09332#openai: “WebGPT: Browser-Assisted Question-Answering With Human Feedback”, Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, John Schulman

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https://arxiv.org/abs/2111.10050#google: “BASIC: Combined Scaling for Open-Vocabulary Image Classification”, Hieu Pham, Zihang Dai, Golnaz Ghiasi, Kenji Kawaguchi, Hanxiao Liu, Adams Wei Yu, Jiahui Yu, Yi-Ting Chen, Minh-Thang Luong, Yonghui Wu, Mingxing Tan, Quoc V. Le

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https://arxiv.org/abs/2111.09162: “It’s About Time: Analog Clock Reading in the Wild”, Charig Yang, Weidi Xie, Andrew Zisserman

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https://arxiv.org/abs/2111.08267: “Solving Probability and Statistics Problems by Program Synthesis”, Leonard Tang, Elizabeth Ke, Nikhil Singh, Nakul Verma, Iddo Drori

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https://arxiv.org/abs/2111.02114#laion: “LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs”, Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, Aran Komatsuzaki

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https://arxiv.org/abs/2110.14168#openai: “Training Verifiers to Solve Math Word Problems”, Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, John Schulman

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https://elifesciences.org/articles/66039: “A Connectome of the Drosophila Central Complex Reveals Network Motifs Suitable for Flexible Navigation and Context-Dependent Action Selection”, Brad K. Hulse, Hannah Haberkern, Romain Franconville, Daniel B. Turner-Evans, Shin-ya Takemura, Tanya Wolff, Marcella Noorman, Marisa Dreher, Chuntao Dan, Ruchi Parekh, Ann M. Hermundstad, Gerald M. Rubin, Vivek Jayaraman

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https://arxiv.org/abs/2109.07958: “TruthfulQA: Measuring How Models Mimic Human Falsehoods”, Stephanie Lin, Jacob Hilton, Owain Evans

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https://laion.ai/blog/laion-400-open-dataset/: “LAION-400-Million Open Dataset”, Christoph Schuhmann

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https://arxiv.org/abs/2106.04560#google: “Scaling Vision Transformers”, Xiaohua Zhai, Alexander Kolesnikov, Neil Houlsby, Lucas Beyer

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https://arxiv.org/abs/2103.14749: “Pervasive Label Errors in Test Sets Destabilize Machine Learning Benchmarks”, Curtis G. Northcutt, Anish Athalye, Jonas Mueller

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