71 citations · 186 across the 38 of their papers we have counts for
4 papers · 1 filter
Closing the Train-Test Gap in World Models for Gradient-Based Planning
Arjun Parthasarathy, Nimit Kalra, Rohun Agrawal +4
World models paired with model predictive control (MPC) can be trained offline on large-scale datasets of expert trajectories and enable generalization to a wide range of planning…
Preserving Cross-Modal Consistency for CLIP-based Class-Incremental Learning
Haoran Chen, Houze Xu, Micah Goldblum +2
Class-incremental learning (CIL) enables models to continuously learn new categories from sequential tasks without forgetting previously acquired knowledge. While recent advances i…
Knowing What You Know Is Not Enough: Large Language Model Confidences Don't Align With Their Actions
Arka Pal, Teo Kitanovski, Arthur Liang +2
Large language models (LLMs) are increasingly deployed in agentic and multi-turn workflows where they are tasked to perform actions of significant consequence. In order to deploy t…
An Attack to Break Permutation-Based Private Third-Party Inference Schemes for LLMs
Rahul Thomas, Louai Zahran, Erica Choi +3
Recent advances in Large Language Models (LLMs) have led to the widespread adoption of third-party inference services, raising critical privacy concerns. Existing methods of perfor…