1k citations · 1.1k across the 35 of their papers we have counts for
10 papers · 1 filter
The Imitation Game: Using Large Language Models as Chatbots to Combat Chat-Based Cybercrimes
Yifan Yao, Baojuan Wang, Jinhao Duan +4
Chat-based cybercrime has emerged as a pervasive threat, with attackers leveraging real-time messaging platforms to conduct scams that rely on trust-building, deception, and psycho…
Conformal Lesion Segmentation for 3D Medical Images
Binyu Tan, Zhiyuan Wang, Jinhao Duan +4
Medical image segmentation serves as a critical component of precision medicine, enabling accurate localization and delineation of pathological regions, such as lesions. However, e…
Sparse Neurons Carry Strong Signals of Question Ambiguity in LLMs
Zhuoxuan Zhang, Jinhao Duan, Edward Kim +1
Ambiguity is pervasive in real-world questions, yet large language models (LLMs) often respond with confident answers rather than seeking clarification. In this work, we show that…
LRR-Bench: Left, Right or Rotate? Vision-Language models Still Struggle With Spatial Understanding Tasks
Fei Kong, Jinhao Duan, Kaidi Xu +3
Real-world applications, such as autonomous driving and humanoid robot manipulation, require precise spatial perception. However, it remains underexplored how Vision-Language Model…
COIN: Uncertainty-Guarding Selective Question Answering for Foundation Models with Provable Risk Guarantees
Zhiyuan Wang, Jinhao Duan, Qingni Wang +4
Uncertainty quantification (UQ) for foundation models is essential to identify and mitigate potential hallucinations in automatically generated text. However, heuristic UQ approach…
UProp: Investigating the Uncertainty Propagation of LLMs in Multi-Step Agentic Decision-Making
Jinhao Duan, James Diffenderfer, Sandeep Madireddy +3
As Large Language Models (LLMs) are integrated into safety-critical applications involving sequential decision-making in the real world, it is essential to know when to trust LLM d…
TruthPrInt: Mitigating Large Vision-Language Models Object Hallucination Via Latent Truthful-Guided Pre-Intervention
Jinhao Duan, Fei Kong, Hao Cheng +6
Object Hallucination (OH) has been acknowledged as one of the major trustworthy challenges in Large Vision-Language Models (LVLMs). Recent advancements in Large Language Models (LL…
DynaCode: A Dynamic Complexity-Aware Code Benchmark for Evaluating Large Language Models in Code Generation
Wenhao Hu, Jinhao Duan, Chunchen Wei +3
The rapid advancement of large language models (LLMs) has significantly improved their performance in code generation tasks. However, existing code benchmarks remain static, consis…
GuideLLM: Exploring LLM-Guided Conversation with Applications in Autobiography Interviewing
Jinhao Duan, Xinyu Zhao, Zhuoxuan Zhang +12
Although Large Language Models (LLMs) succeed in human-guided conversations such as instruction following and question answering, the potential of LLM-guided conversations-where LL…
Jailbreak-AudioBench: In-Depth Evaluation and Analysis of Jailbreak Threats for Large Audio Language Models
Hao Cheng, Erjia Xiao, Jing Shao +6
Large Language Models (LLMs) demonstrate impressive zero-shot performance across a wide range of natural language processing tasks. Integrating various modality encoders further ex…