Research - Papers
Explore a selection of our published work on a variety of key research challenges in AI.
Re-evaluating Automatic LLM System Ranking for Alignment with Human Preference
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…
Social-RAG: Retrieving from Group Interactions to Socially Ground AI Generation
AI agents are increasingly tasked with making proactive suggestions in online spaces where groups collaborate, yet risk being unhelpful or even annoying if they fail to match group preferences or…
Facets, Taxonomies, and Syntheses: Navigating Structured Representations in LLM-Assisted Literature Review
Comprehensive literature review requires synthesizing vast amounts of research — a labor intensive and cognitively demanding process. Most prior work focuses either on helping researchers deeply…
CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation
Despite the surge of interest in autonomous scientific discovery (ASD) of software artifacts (e.g., improved ML algorithms), current ASD systems face two key limitations: (1) they largely explore…
Accelerating Scientific Paper Skimming with Augmented Intelligence Through Customizable Faceted Highlights
Scholars need to keep up with an exponentially increasing flood of scientific papers. To aid this challenge, we introduce Scim, a novel intelligent interface that helps scholars skim papers to…
Paloma: A Benchmark for Evaluating Language Model Fit
Language models (LMs) commonly report perplexity on monolithic data held out from training. Implicitly or explicitly, this data is composed of domains$\unicode{x2013}$varying distributions of…
ArxivDIGESTables: Synthesizing Scientific Literature into Tables using Language Models
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 used to compare and…
SynerGPT: In-Context Learning for Personalized Drug Synergy Prediction and Drug Design
Predicting synergistic drug combinations can help accelerate discovery of cancer treatments, particularly therapies personalized to a patient’s specific tumor via biopsied cells. In this paper, we…
The Semantic Reader Project
Scholarly publications are key to the transfer of knowledge from scholars to others. However, research papers are information-dense, and as the volume of the scientific literature grows, the greater…
ARIES: A Corpus of Scientific Paper Edits Made in Response to Peer Reviews
We introduce the task of automatically revising scientific papers based on peer feedback and release ARIES, a dataset of review comments and their corresponding paper edits. The data is drawn from…