activity
20222025
most citedOn the Evaluation of Machine-Generated Reports

25 citations · 27 across the 16 of their papers we have counts for

collaborators
Showing cs.CVShow all

6 papers · 1 filter

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

MultiVENT 2.0: A Massive Multilingual Benchmark for Event-Centric Video Retrieval

Reno Kriz, Kate Sanders, David Etter +10

Efficiently retrieving and synthesizing information from large-scale multimodal collections has become a critical challenge. However, existing video retrieval datasets suffer from…

cs.CV2024

A Survey of Video Datasets for Grounded Event Understanding

Kate Sanders, Benjamin Van Durme

While existing video benchmarks largely consider specialized downstream tasks like retrieval or question-answering (QA), contemporary multimodal AI systems must be capable of well-…

cs.CV2022

Ambiguous Images With Human Judgments for Robust Visual Event Classification

Kate Sanders, Reno Kriz, Anqi Liu +1

Contemporary vision benchmarks predominantly consider tasks on which humans can achieve near-perfect performance. However, humans are frequently presented with visual data that the…