collaborators

23 papers

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.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

Linguistic Nepotism: Trading-off Quality for Language Preference in Multilingual RAG

Dayeon Ki, Marine Carpuat, Paul McNamee +4

Multilingual Retrieval-Augmented Generation (mRAG) systems enable language models to answer knowledge-intensive queries with citation-supported responses across languages. Despite…

cs.IR2026

ColBERTSaR: Sparsified ColBERT Index via Product Quantization

Eugene Yang, Andrew Yates, Dawn Lawrie +3

While ColBERT is an effective neural retrieval architecture, it requires a heavy index structure to support candidate set retrieval based on approximated token embeddings, gatherin…

cs.IR2026

Overview of the TREC 2025 RAGTIME Track

Dawn Lawrie, Sean MacAvaney, James Mayfield +3

The principal goal of the RAG TREC Instrument for Multilingual Evaluation (RAGTIME) track at TREC is to study report generation from multilingual source documents. The track has cr…

cs.CL2026

FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG

Maxime Dassen, Rebecca Kotula, Kenton Murray +5

Retrieval-Augmented Generation (RAG) models are critically undermined by citation hallucinations, a deceptive failure where a model cites a source that fails to support its claim.…