6 citations · 17 across the 24 of their papers we have counts for
6 papers · 1 filter
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…
Whisper-UT: A Unified Translation Framework for Speech and Text
Cihan Xiao, Matthew Wiesner, Debashish Chakraborty +7
Encoder-decoder models have achieved remarkable success in speech and text tasks, yet efficiently adapting these models to diverse uni/multi-modal scenarios remains an open challen…
WikiVideo: Article Generation from Multiple Videos
Alexander Martin, Reno Kriz, William Gantt Walden +5
We introduce the task of grounded article generation with the goal of creating a Wikipedia-style article from multiple diverse videos about real-world events -- from natural disast…
Video-ColBERT: Contextualized Late Interaction for Text-to-Video Retrieval
Arun Reddy, Alexander Martin, Eugene Yang +7
In this work, we tackle the problem of text-to-video retrieval (T2VR). Inspired by the success of late interaction techniques in text-document, text-image, and text-video retrieval…
MMMORRF: Multimodal Multilingual Modularized Reciprocal Rank Fusion
Saron Samuel, Dan DeGenaro, Jimena Guallar-Blasco +13
Videos inherently contain multiple modalities, including visual events, text overlays, sounds, and speech, all of which are important for retrieval. However, state-of-the-art multi…