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.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…

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…