12 papers
Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs
Yang Yang, Jiawei Chen, Tairan Chen +1
Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inconsistent with the input image…
Exploring the Secondary Risks of Large Language Models
Jiawei Chen, Zhengwei Fang, Yu Tian +4
Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical applications and societal functions. While prior…
ShredBench: Evaluating the Semantic Reasoning Capabilities of Multimodal LLMs in Document Reconstruction
Zichun Guo, Yuling Shi, Wenhao Zeng +6
Multimodal Large Language Models (MLLMs) have achieved remarkable performance in Visually Rich Document Understanding (VRDU) tasks, but their capabilities are mainly evaluated on p…
CLASP: Training-Free LLM-Assisted Source Code Watermarking via Semantic-Preserving Transformations
Rui Xu, Jiawei Chen, Weizhi Liu +3
The proliferation of open-source code and large language models (LLMs) for code generation has amplified the risks of unauthorized reuse and intellectual property infringement. Sou…
DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models
JiYang Wang, Jiawei Chen, Mengqi Xiao +3
Object level hallucination remains a central reliability challenge for vision language models (VLMs), particularly in binary object existence verification. Existing benchmarks emph…
Red Teaming Large Reasoning Models
Jiawei Chen, Yang Yang, Chao Yu +6
Large Reasoning Models (LRMs) have emerged as a powerful advancement in multi-step reasoning tasks, offering enhanced transparency and logical consistency through explicit chains o…