collaborators

14 papers

cs.CV2026

Findings of the MAGMaR 2026 Shared Task

Alexander Martin, Dengjia Zhang, Joel Brogan +7

This overview paper presents the results of the shared task for the second workshop on Multimodal Augmented Generation via Multimodal Retrieval (MAGMaR). In this shared task partic…

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.IR2026

MARQUIS: A Three-Stage Pipeline for Video Retrieval-Augmented Generation

Debashish Chakraborty, Dengjia Zhang, Jialiang Jin +7

Retrieval-augmented generation from videos requires systems to retrieve relevant audiovisual evidence from large corpora and synthesize it into coherent, attributed text. Current a…

cs.IR2026

A Replicability Study of XTR

Rohan Jha, Reno Kriz, Benjamin Van Durme

The XTR (conteXtual Token Retrieval) algorithm is a modification to ColBERT retrieval that avoids the costly step of fully gathering and reranking the candidates' embeddings by imp…

cs.CV2026

Unified Multimodal Uncertain Inference

Dengjia Zhang, Alexander Martin, William Jurayj +3

We introduce Unified Multimodal Uncertain Inference (UMUI), a multimodal inference task spanning text, audio, and video, where models must produce calibrated probability estimates…

cs.IR2026

A Brief Comparison of Training-Free Multi-Vector Sequence Compression Methods

Rohan Jha, Chunsheng Zuo, Reno Kriz +1

While multi-vector retrieval models outperform single-vector models of comparable size in retrieval quality, their practicality is limited by substantially larger index sizes, driv…