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20232025
most citedCan Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations

21 citations · 22 across the 8 of their papers we have counts for

collaborators

9 papers

cs.CL2025

Can Large Language Models Master Complex Card Games?

Wei Wang, Fuqing Bie, Junzhe Chen +4

Complex games have long been an important benchmark for testing the progress of artificial intelligence algorithms. AlphaGo, AlphaZero, and MuZero have defeated top human players i…

cs.AI2025

OmniDPO: A Preference Optimization Framework to Address Omni-Modal Hallucination

Junzhe Chen, Tianshu Zhang, Shiyu Huang +6

Recently, Omni-modal large language models (OLLMs) have sparked a new wave of research, achieving impressive results in tasks such as audio-video understanding and real-time enviro…

cs.CL2025

A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models

Lingzhe Zhang, Liancheng Fang, Chiming Duan +8

As text generation has become a core capability of modern Large Language Models (LLMs), it underpins a wide range of downstream applications. However, most existing LLMs rely on au…

cs.CL2025

Omni-SafetyBench: A Benchmark for Safety Evaluation of Audio-Visual Large Language Models

Leyi Pan, Zheyu Fu, Yunpeng Zhai +9

Omni-modal Large Language Models (OLLMs) that integrate visual, auditory, and textual processing face severe safety risks. They exhibit fragile defenses against audio-visual joint…

cs.CL2025

SA-GCS: Semantic-Aware Gaussian Curriculum Scheduling for UAV Vision-Language Navigation

Hengxing Cai, Jinhan Dong, Yijie Rao +8

Unmanned Aerial Vehicle (UAV) Vision-Language Navigation (VLN) aims to enable agents to accurately localize targets and plan flight paths in complex environments based on natural l…

cs.CL2025

UCSC at SemEval-2025 Task 3: Context, Models and Prompt Optimization for Automated Hallucination Detection in LLM Output

Sicong Huang, Jincheng He, Shiyuan Huang +3

Hallucinations pose a significant challenge for large language models when answering knowledge-intensive queries. As LLMs become more widely adopted, it is crucial not only to dete…

cs.CL2025

Can LLM Watermarks Robustly Prevent Unauthorized Knowledge Distillation?

Leyi Pan, Aiwei Liu, Shiyu Huang +5

The radioactive nature of Large Language Model (LLM) watermarking enables the detection of watermarks inherited by student models when trained on the outputs of watermarked teacher…

cs.CV2024★ 1 cited

ICT: Image-Object Cross-Level Trusted Intervention for Mitigating Object Hallucination in Large Vision-Language Models

Junzhe Chen, Tianshu Zhang, Shiyu Huang +4

Despite the recent breakthroughs achieved by Large Vision Language Models (LVLMs) in understanding and responding to complex visual-textual contexts, their inherent hallucination t…

cs.CL2023★ 21 cited

Can Large Language Models Explain Themselves? A Study of LLM-Generated Self-Explanations

Shiyuan Huang, Siddarth Mamidanna, Shreedhar Jangam +2

Large language models (LLMs) such as ChatGPT have demonstrated superior performance on a variety of natural language processing (NLP) tasks including sentiment analysis, mathematic…