Publications (9)
Precise Model Benchmarking with Only a Few Observations
Riccardo Fogliato, Pratik Patil, Nil-Jana Akpinar +1
How can we precisely estimate a large language model's (LLM) accuracy on questions belonging to a specific topic within a larger question-answering dataset? The standard direct est…
Moments in Time Dataset: one million videos for event understanding
Mathew Monfort, Alex Andonian, Bolei Zhou +8
We present the Moments in Time Dataset, a large-scale human-annotated collection of one million short videos corresponding to dynamic events unfolding within three seconds. Modelin…
Reasoning About Human-Object Interactions Through Dual Attention Networks
Tete Xiao, Quanfu Fan, Dan Gutfreund +3
Objects are entities we act upon, where the functionality of an object is determined by how we interact with it. In this work we propose a Dual Attention Network model which reason…
Multi-Agent Tensor Fusion for Contextual Trajectory Prediction
Tianyang Zhao, Yifei Xu, Mathew Monfort +5
Accurate prediction of others' trajectories is essential for autonomous driving. Trajectory prediction is challenging because it requires reasoning about agents' past movements, so…
We Have So Much In Common: Modeling Semantic Relational Set Abstractions in Videos
Alex Andonian, Camilo Fosco, Mathew Monfort +4
Identifying common patterns among events is a key ability in human and machine perception, as it underlies intelligent decision making. We propose an approach for learning semantic…
Spoken Moments: Learning Joint Audio-Visual Representations from Video Descriptions
Mathew Monfort, SouYoung Jin, Alexander Liu +4
When people observe events, they are able to abstract key information and build concise summaries of what is happening. These summaries include contextual and semantic information…