24 citations · 47 across the 9 of their papers we have counts for
13 papers · 1 filter
Ai2 Scholar QA: Organized Literature Synthesis with Attribution
Amanpreet Singh, Joseph Chee Chang, Chloe Anastasiades +15
Retrieval-augmented generation is increasingly effective in answering scientific questions from literature, but many state-of-the-art systems are expensive and closed-source. We in…
OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs
Akari Asai, Jacqueline He, Rulin Shao +22
Scientific progress depends on researchers' ability to synthesize the growing body of literature. Can large language models (LMs) assist scientists in this task? We introduce OpenS…
TOPICAL: TOPIC Pages AutomagicaLly
John Giorgi, Amanpreet Singh, Doug Downey +2
Topic pages aggregate useful information about an entity or concept into a single succinct and accessible article. Automated creation of topic pages would enable their rapid curati…
Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models
Victor S. Bursztyn, David Demeter, Doug Downey +1
How to usefully encode compositional task structure has long been a core challenge in AI. Recent work in chain of thought prompting has shown that for very large neural language mo…
ACCoRD: A Multi-Document Approach to Generating Diverse Descriptions of Scientific Concepts
Sonia K. Murthy, Kyle Lo, Daniel King +7
Systems that can automatically define unfamiliar terms hold the promise of improving the accessibility of scientific texts, especially for readers who may lack prerequisite backgro…
"It doesn't look good for a date": Transforming Critiques into Preferences for Conversational Recommendation Systems
Victor S. Bursztyn, Jennifer Healey, Nedim Lipka +3
Conversations aimed at determining good recommendations are iterative in nature. People often express their preferences in terms of a critique of the current recommendation (e.g.,…