collaborators

5 papers

cs.AI2026

Deferred Exposure of Future Trajectories for Verifiable Reasoning in Autonomous Driving VLMs

Zixuan Huang, Yang Zhou, Kaixuan Wang +7

Recent Vision-Language-Action (VLA) models for autonomous driving (AD) increasingly utilize chain-of-thought (CoT) supervision to enhance the reasoning capabilities of their Vision…

cs.CL2026

Multi-Objective Exploration and Preference Optimization via Mutual Information

Hongyan Xie, Yikun Ban, Ruiyu Fang +4

Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicting preference dimensions. Cu…

cs.CL2026

UniARM: Towards a Unified Autoregressive Reward Model for Multi-Objective Test-Time Alignment

Hongyan Xie, Yikun Ban, Ruiyu Fang +6

Multi-objective alignment aims to align LLM responses with multiple human preference objectives. Among existing methods, guiding the generation of frozen LLMs through autoregressiv…

cs.AI2026

Does Your Reasoning Model Implicitly Know When to Stop Thinking?

Zixuan Huang, Xin Xia, Yuxi Ren +11

Recent advancements in large reasoning models (LRMs) have greatly improved their capabilities on complex reasoning tasks through Long Chains of Thought (CoTs). However, this approa…

cs.AI2026

Real-Time Aligned Reward Model beyond Semantics

Zixuan Huang, Xin Xia, Yuxi Ren +10

Reinforcement Learning from Human Feedback (RLHF) is a pivotal technique for aligning large language models (LLMs) with human preferences, yet it is susceptible to reward overoptim…