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Research - Papers

Explore a selection of our published work on a variety of key research challenges in AI.

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Deep Research, Shallow Evaluation: A Case Study in Meta-Evaluation for Long-Form QA Benchmarks

Jena D. HwangV. KishoreAmanpreet SinghSergey Feldman
2026
arXiv.org

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, along with… 

Understanding Usage and Engagement in AI-Powered Scientific Research Tools: The Asta Interaction Dataset

Dany HaddadDan BareketJ. ChangDoug Downey
2026
arXiv.org

AI-powered scientific research tools are rapidly being integrated into research workflows, yet the field lacks a clear lens into how researchers use these systems in real-world settings. We present… 

PreScience: A Dataset and Benchmark for Scientific Forecasting

Anirudh AjithAmanpreet SinghJay DeYoungDoug Downey
2026
arXiv

Can AI systems trained on the existing scientific record forecast the advances that will follow? We introduce PreScience, a dataset and benchmark for scientific forecasting built around 98K recent… 

SciArena: An Open Evaluation Platform for Non-Verifiable Scientific Literature-Grounded Tasks

Yilun ZhaoKaiyan ZhangTiansheng HuArman Cohan
2025
NeurIPS

We present SciArena, an open and collaborative platform for evaluating foundation models on scientific literature-grounded tasks. Unlike traditional benchmarks for scientific literature… 

SciRIFF: A Resource to Enhance Language Model Instruction-Following over Scientific Literature

David WaddenKejian ShiJacob Daniel MorrisonArman Cohan
2025
EMNLP

We present SciRIFF (Scientific Resource for Instruction-Following and Finetuning), a dataset of 137K instruction-following instances for training and evaluation, covering 54 tasks. These tasks span… 

Intent-Aware Schema Generation And Refinement For Literature Review Tables

Vishakh PadmakumarJoseph Chee ChangKyle LoAakanksha Naik
2025
EMNLP

The increasing volume of academic literature makes it essential for researchers to organize, compare, and contrast collections of documents. Large language models (LLMs) can support this process by… 

LLMs as Research Tools: A Large Scale Survey of Researchers' Usage and Perceptions

Zhehui LiaoMaria AntoniakInyoung CheongAmy X. Zhang
2025
COLM

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 their research… 

Ai2 Scholar QA: Organized Literature Synthesis with Attribution

Amanpreet SinghJoseph Chee ChangChloe AnastasiadesSergey Feldman
2025
ACL

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 introduce Ai2… 

IdeaSynth: Iterative Research Idea Development Through Evolving and Composing Idea Facets with Literature-Grounded Feedback

Kevin PuK. FengTovi GrossmanPao Siangliulue
2025
CHI

Research ideation involves broad exploring and deep refining ideas. Both require deep engagement with literature. Existing tools focus primarily on idea broad generation, yet offer little support… 

Re-evaluating Automatic LLM System Ranking for Alignment with Human Preference

Mingqi GaoYixin LiuXinyu HuArman Cohan
2025
NAACL

Evaluating and ranking the capabilities of different LLMs is crucial for understanding their performance and alignment with human preferences. Due to the high cost and time-consuming nature of human…