7 citations · 7 across the 5 of their papers we have counts for
7 papers
TeleTune: Evolving Agent Skills From Offline Telemetry
Justin Chih-Yao Chen, Elias Stengel-Eskin, Yan Chen +6
Computer-use agents need to capture procedural knowledge of how people use software. User telemetry offers a scalable source of this knowledge. However, learning reusable skills fr…
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…
ARIA: A Causal-Aware Framework for Rescuing LLM Reasoning in Trustworthy Materials Discovery
Yi Cao, Liaoyaqi Wang, Jieneng Chen +3
Generative models have revolutionized the process of materials discovery, yet they often fail to satisfy underlying physical causality. Through an analysis of Large Language Models…
Synthetic Function Demonstrations Improve Generation in Low-Resource Programming Languages
Nick McKenna, Xinnuo Xu, Jack Williams +3
A key consideration when training an LLM is whether the target language is more or less resourced, for example English compared to Welsh, or Python compared to Excel. Typical train…
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-…
NELLIE: A Neuro-Symbolic Inference Engine for Grounded, Compositional, and Explainable Reasoning
Nathaniel Weir, Peter Clark, Benjamin Van Durme
Our goal is a modern approach to answering questions via systematic reasoning where answers are supported by human interpretable proof trees grounded in an NL corpus of authoritati…
Collecting Diverse Natural Language Inference Problems for Sentence Representation Evaluation
Adam Poliak, Aparajita Haldar, Rachel Rudinger +4
We present a large-scale collection of diverse natural language inference (NLI) datasets that help provide insight into how well a sentence representation captures distinct types o…