Papers
See AI2's Award Winning Papers
Learn more about AI2's Lasting Impact Award
Viewing 21-30 of 844 papers
Scim: Intelligent Faceted Highlights for Interactive, Multi-Pass Skimming of Scientific Papers
Raymond Fok, Hita Kambhamettu, Luca Soldaini, Jonathan Bragg, Kyle Lo, Andrew Head, Marti A. Hearst, Daniel S. WeldIUI • 2023 Researchers are expected to keep up with an immense literature, yet often find it prohibitively time-consuming to do so. This paper ex-plores how intelligent agents can help scaffold in-situ information seeking across scientific papers. Specifically, we…The Semantic Reader Project: Augmenting Scholarly Documents through AI-Powered Interactive Reading Interfaces
Kyle Lo, Joseph Chee Chang, Andrew Head, Jonathan Bragg, Amy X. Zhang, Cassidy Trier, Chloe Anastasiades, Tal August, Russell Authur, Danielle Bragg, Erin Bransom, Isabel Cachola, Stefan Candra, Yoganand Chandrasekhar, Yen-Sung Chen, Evie (Yu-Yen) Cheng, Yvonne Chou, Doug Downey, Rob Evans, Raymond Fok, F.Q. Hu, Regan Huff, Dongyeop Kang, Tae Soo Kim, Rodney Kinney, Aniket Kittur, Hyeonsu B Kang, Egor Klevak, Bailey Kuehl, Michael Langan, Matt Latzke, Jaron Lochner, Kelsey MacMillan, Eric Marsh, Tyler Murray, Aakanksha Naik, Ngoc-Uyen Nguyen, Srishti Palani, Soya Park, Caroline Paulic, Napol Rachatasumrit, Smita Rao, Paul Sayre, Zejiang Shen, Pao Siangliulue, Luca Soldaini, Huy Tran, Madeleine van Zuylen, Lucy Lu Wang, Christopher Wilhelm, Caroline Wu, Jiangjiang Yang, Angele Zamarron, Marti A. Hearst, Daniel S. WeldarXiv • 2023 Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the need for new technology to support the reading process grows. In…Comparing Sentence-Level Suggestions to Message-Level Suggestions in AI-Mediated Communication
Liye Fu, Benjamin Newman, Maurice Jakesch, Sarah KrepsInternational Conference on Human Factors in Computing Systems • 2023 Traditionally, writing assistance systems have focused on short or even single-word suggestions. Recently, large language models like GPT-3 have made it possible to generate significantly longer natural-sounding suggestions, offering more advanced assistance…BotPercent: Estimating Twitter Bot Populations from Groups to Crowds
Zhaoxuan Tan, Shangbin Feng, Melanie Sclar, Herun Wan, Minnan Luo, Yejin Choi, Yulia TsvetkovarXiv • 2023 Twitter bot detection has become increasingly important in combating misinformation, identifying malicious online campaigns, and protecting the integrity of social media discourse. While existing bot detection literature mostly focuses on identifying…Do Embodied Agents Dream of Pixelated Sheep?: Embodied Decision Making using Language Guided World Modelling
Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hanna Hajishirzi, Sameer Singh, Roy FoxarXiv • 2023 Reinforcement learning (RL) agents typically learn tabula rasa, without prior knowledge of the world, which makes learning complex tasks with sparse rewards difficult. If initialized with knowledge of high-level subgoals and transitions between subgoals, RL…Transformers Can Be Expressed In First-Order Logic with Majority
William Merrill, Ashish SabharwalarXiv • 2023 Characterizing the implicit structure of the computation within neural networks is a foundational problem in the area of deep learning interpretability. Can the inner decision process of neural networks be captured symbolically in some familiar logic? We show…Improving stratocumulus cloud amounts in a 200-m resolution multi-scale modeling framework through tuning of its interior physics
Liran Peng, Michael Pritchard, Peter N. Blossey, Walter M. Hannah, Christopher S. Bretherton, Christopher R. Terai, and Andrea M. JenneyESSOAr (submitted to the American Geophysical Union journal JAMES) • 2023 High-Resolution Multi-scale Modeling Frameworks (HR) -- global climate models that embed separate, convection-resolving models with high enough resolution to resolve boundary layer eddies -- have exciting potential for investigating low cloud feedback…The Semantic Scholar Open Data Platform
Rodney Michael Kinney, Chloe Anastasiades, Russell Authur, Iz Beltagy, Jonathan Bragg, Alexandra Buraczynski, Isabel Cachola, Stefan Candra, Yoganand Chandrasekhar, Arman Cohan, Miles Crawford, Doug Downey, J. Dunkelberger, Oren Etzioni, R. Evans, Sergey Feldman, Joseph Gorney, D. Graham, F.Q. Hu, Regan Huff, Daniel King, Sebastian Kohlmeier, Bailey Kuehl, Michael Langan, Daniel Lin, Haokun Liu, Kyle Lo, Jaron Lochner, Kelsey MacMillan, Tyler Murray, Christopher Newell, Smita Rao, Shaurya Rohatgi, P. Sayre, Zejiang Shen, Amanpreet Singh, Luca Soldaini, Shivashankar Subramanian, A. Tanaka, Alex D Wade, Linda M. Wagner, Lucy Lu Wang, Christopher Wilhelm, Caroline Wu, Jiangjiang Yang, A. Zamarron, Madeleine van Zuylen, Daniel S. WeldarXiv • 2023 The volume of scientific output is creating an urgent need for automated tools to help scientists keep up with developments in their field. Semantic Scholar (S2) is an open data platform and website aimed at accelerating science by helping scholars discover…Does progress on ImageNet transfer to real-world datasets?
Alexander W. Fang, Simon Kornblith, Ludwig SchmidtarXiv • 2023 Does progress on ImageNet transfer to real-world datasets? We investigate this question by evaluating ImageNet pre-trained models with varying accuracy (57% - 83%) on six practical image classification datasets. In particular, we study datasets collected with…MAUVE Scores for Generative Models: Theory and Practice
Krishna Pillutla, Lang Liu, John Thickstun, S. Welleck, Swabha Swayamdipta, Rowan Zellers, Sewoong Oh, Yejin Choi, Z. HarchaouiarXiv • 2022 Generative AI has matured to a point where large-scale models can generate text that seems indistinguishable from human-written text and remarkably photorealistic images. Automatically measuring how close the distribution of generated data is to the target…