3 papers
cs.CV2026
Training-Free Temporal Abstraction for General Video Understanding
Etienne Casanova, Sevan Brodjian, Pietro Perona
Videos are expensive to analyze frame by frame, yet many video understanding tasks depend on knowing where relevant moments occur. A system may need to find when an action changes,…
cs.CL2026
On the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance
Etienne Casanova, Rafal Kocielnik, R. Michael Alvarez
Large Language Models (LLMs) are increasingly used for zero-shot annotation and LLM-as-a-judge tasks, yet their reliability hinges on how model-internalized priors interact with us…
cs.AI2026
Beyond the "Truth": Investigating Election Rumors on Truth Social During the 2024 Election
Etienne Casanova, R. Michael Alvarez
Large language models (LLMs) offer unprecedented opportunities for analyzing social phenomena at scale. This paper demonstrates the value of LLMs in psychological measurement by (1…