1 citations · 1 across the 11 of their papers we have counts for
12 papers
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…
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…
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…
Laguna M.1/XS.2 Technical Report
Julien Abadji, Marah Abdin, Connor Adams +93
We present Laguna M.1 and Laguna XS.2, two Mixture-of-Experts foundation models built for long-horizon, agentic coding: M.1 has B total parameters (B activated per tok…
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…
Prompt-Induced Score Variance in Zero-Shot Binary Vision-Language Safety Classification
Charles Weng, Dingwen Li, Alexander Martin
Safety pipelines often block content by thresholding a model's first-token unsafe score. We show that a single prompt's score is not a reliable probability and compare two repairs:…
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…
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…
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…
HLTCOE Evaluation Team at TREC 2025: VQA Track
Dengjia Zhang, Charles Weng, Katherine Guerrerio +5
The HLTCOE Evaluation team participated in TREC VQA's Answer Generation (AG) task, for which we developed a listwise learning framework that aims to improve semantic precision and…
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 more prevalent source of information o…