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20242026
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cs.CL2026

On the Role of Citations in Preference Data

Yu Hou, Hal Daumé, Rachel Rudinger +1

Many NLP tasks require systems to provide attribution in their outputs--i.e. citations to grounding sources. Attribution serves as a bulwark against model hallucination and as a me…

cs.CL2026

DoGMaTiQ: Automated Generation of Question-and-Answer Nuggets for Report Evaluation

Bryan Li, William Walden, Yu Hou +6

Evaluation of long-form, citation-backed reports has lately received significant attention due to the wide-scale adoption of retrieval-augmented generation (RAG) systems. Core to m…

cs.CL2026

Seeing Through the MiRAGE: Evaluating Multimodal Retrieval Augmented Generation

Alexander Martin, William Walden, Reno Kriz +5

We introduce MiRAGE, an evaluation framework for retrieval-augmented generation (RAG) from multimodal sources. As audiovisual media becomes a prevalent source of information online…

cs.CL2026

Investigating Retrieval-Augmented Generation Systems on Unanswerable, Uncheatable, Realistic, Multi-hop Queries

Gabrielle Kaili-May Liu, Bryan Li, Arman Cohan +2

Real-world use cases often present RAG systems with complex queries for which relevant information is missing from the corpus or is incomplete. In these settings, RAG systems must…

cs.CL2025

How Grounded is Wikipedia? A Study on Structured Evidential Support and Retrieval

William Walden, Kathryn Ricci, Miriam Wanner +4

Wikipedia is a critical resource for modern NLP, serving as a rich repository of up-to-date and citation-backed information on a wide variety of subjects. The reliability of Wikipe…

cs.CL2024

Cross-Document Event-Keyed Summarization

William Walden, Pavlo Kuchmiichuk, Alexander Martin +5

Event-keyed summarization (EKS) requires summarizing a specific event described in a document given the document text and an event representation extracted from it. In this work, w…