activity
20152026
most citedReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension

211 citations · 674 across the 113 of their papers we have counts for

collaborators

127 papers

cs.CL2026

Knowledge Pull Requests for Continual Document Authoring

Alexander Martin, Benjamin Van Durme

We introduce Knowledge Pull Requests (KPRs), a framework for continual document authoring that makes each change interpretable. Documents require ongoing revision as new knowledge…

cs.CL2026

Mining Legal Arguments in U.S. Corporate Case Law

Luis Brena, William Jurayj, Gregory Deyesu +3

Legal argument mining supports passage classification, retrieval, and argument completion. This work introduces an expert-annotated dataset of 42 U.S. federal tax opinions on corpo…

cs.HC2026

FrankenReport: Early Exiting in Long-Form Generation Using Expected Value of Computation

Zhengping Jiang, Gonzalo Ramos, Jina Suh +6

While deep research systems address interactive information-seeking needs impressively, their real-world deployments face latency and resource-consumption challenges. We present Fr…

cs.DL2026

Crystal: Characterizing Relative Impact of Scholarly Publications

Hannah Collison, Benjamin Van Durme, Daniel Khashabi

Assessing a cited paper's impact is typically done by analyzing its citation context in isolation within the citing paper. While this focuses on the most directly relevant text, it…

cs.IR2026

Beyond Relevance: On the Relationship Between Retrieval and RAG Information Coverage

Saron Samuel, Alexander Martin, Eugene Yang +5

Retrieval-augmented generation (RAG) systems combine document retrieval with a generative model to address complex information seeking tasks like report generation. While the relat…

cs.CL2024★ 1 cited

LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error

Boshi Wang, Hao Fang, Jason Eisner +2

Tools are essential for large language models (LLMs) to acquire up-to-date information and take consequential actions in external environments. Existing work on tool-augmented LLMs…