6 citations · 11 across the 4 of their papers we have counts for
4 papers
Intent-Aware Schema Generation And Refinement For Literature Review Tables
Vishakh Padmakumar, Joseph Chee Chang, Kyle Lo +2
The increasing volume of academic literature makes it essential for researchers to organize, compare, and contrast collections of documents. Large language models (LLMs) can suppor…
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…
Contextualized Evaluations: Judging Language Model Responses to Underspecified Queries
Chaitanya Malaviya, Joseph Chee Chang, Dan Roth +3
Language model users often issue queries that lack specification, where the context under which a query was issued -- such as the user's identity, the query's intent, and the crite…
LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions
Zhehui Liao, Maria Antoniak, Inyoung Cheong +5
The rise of large language models (LLMs) has led many researchers to consider their usage for scientific work. Some have found benefits using LLMs to augment or automate aspects of…