1 citations · 1 across the 9 of their papers we have counts for
10 papers
Asterism: Exploring and Synthesizing Scattered Observations into Literature-Grounded Hypotheses and Theories
Joseph Chee Chang, Michael D'Arcy, Amy X. Zhang +15
A theory draws many independent observations into one framework with novel hypotheses. A researcher building such a theory must synthesize observations scattered across many papers…
DRACULA: Hunting for the Actions Users Want Deep Research Agents to Execute
Nishant Balepur, Malachi Hamada, Varsha Kishore +9
Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their utility, but existing protocols…
Language Models Don't Know What You Want: Evaluating Personalization in Deep Research Needs Real Users
Nishant Balepur, Malachi Hamada, Varsha Kishore +7
Deep Research (DR) systems help researchers cope with ballooning publishing counts. Such tools synthesize scientific papers to answer research queries, but lack understanding of th…
LitPivot: Developing Well-Situated Research Ideas Through Dynamic Contextualization and Critique within the Literature Landscape
Hita Kambhamettu, Bhavana Dalvi Mishra, Andrew Head +4
Developing a novel research idea is hard. It must be distinct enough from prior work to claim a contribution while also building on it. This requires iteratively reviewing literatu…
Deep Research, Shallow Evaluation: A Case Study in Meta-Evaluation for Long-Form QA Benchmarks
Jena D. Hwang, Varsha Kishore, Amanpreet Singh +9
Recent advances have made long-form report-generating systems widely available. This has prompted evaluation frameworks that use LLM-as-judge protocols and claim verification, alon…
Improving Attributed Long-form Question Answering with Intent Awareness
Xinran Zhao, Aakanksha Naik, Jay DeYoung +4
Large language models (LLMs) are increasingly being used to generate comprehensive, knowledge-intensive reports. However, while these models are trained on diverse academic papers…
AstaBench: Rigorous Benchmarking of AI Agents with a Scientific Research Suite
Jonathan Bragg, Mike D'Arcy, Nishant Balepur +36
AI agents hold the potential to revolutionize scientific productivity by automating literature reviews, replicating experiments, analyzing data, and even proposing new directions o…
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…
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…
ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models
Benjamin Newman, Yoonjoo Lee, Aakanksha Naik +6
When conducting literature reviews, scientists often create literature review tables - tables whose rows are publications and whose columns constitute a schema, a set of aspects us…