activity
20242026
most citedVersatile Behavior Diffusion for Generalized Traffic Agent Simulation

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

cs.LG2026

Human-like autonomy emerges from self-play and a pinch of human data

Daphne Cornelisse, Julian Hunt, Zixu Zhang +4

Self-play reinforcement learning has recently emerged as a way to train driving policies without any human data. It uses cheap, large-scale simulations to substitute expensive, lar…

cs.RO20261 cited

Versatile Behavior Diffusion for Generalized Traffic Agent Simulation

Zhiyu Huang, Zixu Zhang, Ameya Vaidya +3

Existing traffic simulation models often fall short in capturing the intricacies of real-world scenarios, particularly the interactive behaviors among multiple traffic participants…

cs.AI2025

Introspective Planning: Aligning Robots' Uncertainty with Inherent Task Ambiguity

Kaiqu Liang, Zixu Zhang, Jaime Fernández Fisac

Large language models (LLMs) exhibit advanced reasoning skills, enabling robots to comprehend natural language instructions and strategically plan high-level actions through proper…

cs.RO2024

Blending Data-Driven Priors in Dynamic Games

Justin Lidard, Haimin Hu, Asher Hancock +9

As intelligent robots like autonomous vehicles become increasingly deployed in the presence of people, the extent to which these systems should leverage model-based game-theoretic…

cs.RO2024

Who Plays First? Optimizing the Order of Play in Stackelberg Games with Many Robots

Haimin Hu, Gabriele Dragotto, Zixu Zhang +3

We consider the multi-agent spatial navigation problem of computing the socially optimal order of play, i.e., the sequence in which the agents commit to their decisions, and its as…