6 citations · 17 across the 24 of their papers we have counts for
11 papers · 1 filter
Attention Sinks in VLMs Are Borrowed, Not Seen
Dengjia Zhang, Alexander Martin, Pengyu Yan +6
We study how to detect and mitigate visual attention sinks in vision-language models (VLMs). Visual attention sinks are image tokens that absorb a large share of attention over the…
LAYERSCOPE: A Layerwise Characterization of Video and Multimodal Learned Representations
Sandra Arcos-Holzinger, Debashish Chakraborty, Rohita Mocharla +7
We propose LAYERSCOPE, a label-free, layerwise framework that aims to characterize a model's learned representations in video and multimodal settings. Evaluating downstream perform…
MultiVENT-Raw: A Benchmark for Retrieval and Reasoning over Raw Videos
Reno Kriz, David Etter, Alexander Martin +11
Online information is increasingly consumed in video format. Much of this comes in the form of *raw video*: continuous footage taken on a cell phone, with a hand-held camera, or vi…
Information Satisfaction: A Reader-Centered Axis for Summarization Evaluation
Isabel Cachola, William Walden, Reno Kriz +1
The majority of work on summarization evaluation focuses on general summary quality (e.g., ROUGE, BERTScore) or specific desired properties (e.g., readability, factuality). However…
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…
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…
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…
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…
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…
Multi-Vector Index Compression in Any Modality
Hanxiang Qin, Alexander Martin, Rohan Jha +3
We study efficient multi-vector retrieval for late interaction in any modality. Late interaction has emerged as a dominant paradigm for information retrieval in text, images, visua…
RANKVIDEO: Reasoning Reranking for Text-to-Video Retrieval
Tyler Skow, Alexander Martin, Benjamin Van Durme +2
Reranking is a critical component of modern retrieval systems, which typically pair an efficient first-stage retriever with a more expressive model to refine results. While large r…