collaborators

10 papers

cs.AI2026

Confidence-Aware Alignment Makes Reasoning LLMs More Reliable

Kejia Chen, Jiawen Zhang, Yihong Wu +5

Large reasoning models often reach correct answers through flawed intermediate steps, creating a gap between final accuracy and reasoning reliability. Existing alignment strategies…

cs.LG2025

Non-stationary Delayed Online Convex Optimization: From Full-information to Bandit Setting

Yuanyu Wan, Chang Yao, Yitao Ma +2

Although online convex optimization (OCO) under arbitrary delays has received increasing attention recently, previous studies focus on stationary environments with the goal of mini…

cs.CV2025

Token-Level Inference-Time Alignment for Vision-Language Models

Kejia Chen, Jiawen Zhang, Jiacong Hu +4

Vision-Language Models (VLMs) have become essential backbones of modern multimodal intelligence, yet their outputs remain prone to hallucination-plausible text misaligned with visu…

cs.CV2025

RS3DBench: A Comprehensive Benchmark for 3D Spatial Perception in Remote Sensing

Jiayu Wang, Ruizhi Wang, Jie Song +4

In this paper, we introduce a novel benchmark designed to propel the advancement of general-purpose, large-scale 3D vision models for remote sensing imagery. While several datasets…

cs.LG2025

Q-resafe: Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models

Kejia Chen, Jiawen Zhang, Jiacong Hu +4

Quantized large language models (LLMs) have gained increasing attention and significance for enabling deployment in resource-constrained environments. However, emerging studies on…

cs.CR2025

Activation Approximations Can Incur Safety Vulnerabilities Even in Aligned LLMs: Comprehensive Analysis and Defense

Jiawen Zhang, Kejia Chen, Lipeng He +7

Large Language Models (LLMs) have showcased remarkable capabilities across various domains. Accompanying the evolving capabilities and expanding deployment scenarios of LLMs, their…