1 citations · 2 across the 25 of their papers we have counts for
8 papers · 1 filter
On Learning Closed-Loop Probabilistic Multi-Agent Simulator
Juanwu Lu, Rohit Gupta, Ahmadreza Moradipari +3
The rapid iteration of autonomous vehicle (AV) deployments leads to increasing needs for building realistic and scalable multi-agent traffic simulators for efficient evaluation. Re…
Entropy-Guided Sampling of Flat Modes in Discrete Spaces
Pinaki Mohanty, Riddhiman Bhattacharya, Ruqi Zhang
Sampling from flat modes in discrete spaces is a crucial yet underexplored problem. Flat modes represent robust solutions and have broad applications in combinatorial optimization…
Energy-Based Reward Models for Robust Language Model Alignment
Anamika Lochab, Ruqi Zhang
Reward models (RMs) are essential for aligning Large Language Models (LLMs) with human preferences. However, they often struggle with capturing complex human preferences and genera…
Reheated Gradient-based Discrete Sampling for Combinatorial Optimization
Muheng Li, Ruqi Zhang
Recently, gradient-based discrete sampling has emerged as a highly efficient, general-purpose solver for various combinatorial optimization (CO) problems, achieving performance com…
Optimal Stochastic Trace Estimation in Generative Modeling
Xinyang Liu, Hengrong Du, Wei Deng +1
Hutchinson estimators are widely employed in training divergence-based likelihoods for diffusion models to ensure optimal transport (OT) properties. However, this estimator often s…
Single-Step Consistent Diffusion Samplers
Pascal Jutras-Dubé, Patrick Pynadath, Ruqi Zhang
Sampling from unnormalized target distributions is a fundamental yet challenging task in machine learning and statistics. Existing sampling algorithms typically require many iterat…