45 citations · 68 across the 28 of their papers we have counts for
29 papers
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…
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…
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…
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…
SHAPE : Self-Improved Visual Preference Alignment by Iteratively Generating Holistic Winner
Kejia Chen, Jiawen Zhang, Jiacong Hu +4
Large Visual Language Models (LVLMs) increasingly rely on preference alignment to ensure reliability, which steers the model behavior via preference fine-tuning on preference data…
SecPE: Secure Prompt Ensembling for Private and Robust Large Language Models
Jiawen Zhang, Kejia Chen, Zunlei Feng +4
With the growing popularity of LLMs among the general public users, privacy-preserving and adversarial robustness have become two pressing demands for LLM-based services, which hav…