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Viewing 31-40 of 1022 papers
Tailoring Self-Rationalizers with Multi-Reward Distillation
Sahana Ramnath, Brihi Joshi, Skyler Hallinan, Ximing Lu, Liunian Harold Li, Aaron Chan, Jack Hessel, Yejin Choi, Xiang RenICLR • 2024 Large language models (LMs) are capable of generating free-text rationales to aid question answering. However, prior work 1) suggests that useful self-rationalization is emergent only at significant scales (e.g., 175B parameter GPT-3); and 2) focuses largely…The Generative AI Paradox: "What It Can Create, It May Not Understand"
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian R. Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin ChoiICLR • 2024 The recent wave of generative AI has sparked unprecedented global attention, with both excitement and concern over potentially superhuman levels of artificial intelligence: models now take only seconds to produce outputs that would challenge or exceed the…The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu, Nouha Dziri, Melanie Sclar, Khyathi Raghavi Chandu, Chandra Bhagavatula, Yejin ChoiICLR • 2024 The alignment tuning process of large language models (LLMs) typically involves instruction learning through supervised fine-tuning (SFT) and preference tuning via reinforcement learning from human feedback (RLHF). A recent study, LIMA (Zhou et al. 2023…MacGyver: Are Large Language Models Creative Problem Solvers?
Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze BrahmanNAACL • 2024 We explore the creative problem-solving capabilities of modern LLMs in a novel constrained setting. To this end, we create MACGYVER, an automatically generated dataset consisting of over 1,600 real-world problems deliberately designed to trigger innovative…CARE: Extracting Experimental Findings From Clinical Literature
Aakanksha Naik, Bailey Kuehl, Erin Bransom, Doug Downey, Tom HopeNAACL 2024 • 2024 Extracting fine-grained experimental findings from literature can provide dramatic utility for scientific applications. Prior work has developed annotation schemas and datasets for limited aspects of this problem, failing to capture the real-world complexity…A Legal Risk Taxonomy for Generative Artificial Intelligence
David Atkinson, Jacob MorrisonarXiv.org • 2024 For the first time, this paper presents a taxonomy of legal risks associated with generative AI (GenAI) by breaking down complex legal concepts to provide a common understanding of potential legal challenges for developing and deploying GenAI models. The…Estimating the Causal Effect of Early ArXiving on Paper Acceptance
Yanai Elazar, Jiayao Zhang, David Wadden, Boshen Zhang, Noah A. SmithCLearR • 2024 What is the effect of releasing a preprint of a paper before it is submitted for peer review? No randomized controlled trial has been conducted, so we turn to observational data to answer this question. We use data from the ICLR conference (2018--2022) and…The precipitation response to warming and CO2 increase: A comparison of a global storm resolving model and CMIP6 models.
Ilai Guendelman, Timothy M. Merlis, Kai-Yuan Cheng, Lucas M. Harris, Christopher S. Bretherton, Max Bolot, Lin Zhou, Alex Kaltenbaugh, Spencer K. Clark, Stephan FueglistalerGeophysical Research Letters • 2024 Global storm-resolving models (GSRMs) can explicitly resolve some of deep convection are now being integrated for climate timescales. GSRMs are able to simulate more realistic precipitation distributions relative to traditional CMIP6 models. In this study, we…FigurA11y: AI Assistance for Writing Scientific Alt Text
Nikhil Singh, Lucy Lu Wang, Jonathan BraggIUI • 2024 High-quality alt text is crucial for making scientific figures accessible to blind and low-vision readers. Crafting complete, accurate alt text is challenging even for domain experts, as published figures often depict complex visual information and readers…Emulation of cloud microphysics in a climate model
W. Andre Perkins, Noah D. Brenowitz, Christopher S. Bretherton, Jacqueline M. NugentJAMES • 2024 We present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao-Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in…