1 citations · 1 across the 9 of their papers we have counts for
10 papers
Escaping Confidence Trap: Evolutionary Decoding for Mathematical Reasoning in Diffusion LLMs
Zhenhong Sun, Hanqing Zhao, Yatao Bian +7
Diffusion large language models (dLLMs) have emerged as a promising alternative to autoregressive LLMs, offering efficient generation through block-wise progressive unmasking. Howe…
BiT-MCTS: A Theme-based Bidirectional MCTS Approach to Chinese Fiction Generation
Zhaoyi Li, Xu Zhang, Xiaojun Wan
Generating long-form linear fiction from open-ended themes remains a major challenge for large language models, which frequently fail to guarantee global structure and narrative di…
MM-ReCoder: Advancing Chart-to-Code Generation with Reinforcement Learning and Self-Correction
Zitian Tang, Xu Zhang, Jianbo Yuan +4
Multimodal Large Language Models (MLLMs) have recently demonstrated promising capabilities in multimodal coding tasks such as chart-to-code generation. However, existing methods pr…
HAD: HAllucination Detection Language Models Based on a Comprehensive Hallucination Taxonomy
Fan Xu, Xinyu Hu, Zhenghan Yu +6
The increasing reliance on natural language generation (NLG) models, particularly large language models, has raised concerns about the reliability and accuracy of their outputs. A…
C-FAITH: A Chinese Fine-Grained Benchmark for Automated Hallucination Evaluation
Xu Zhang, Zhifei Liu, Jiahao Wang +4
Despite the rapid advancement of large language models, they remain highly susceptible to generating hallucinations, which significantly hinders their widespread application. Hallu…
ContraSolver: Self-Alignment of Language Models by Resolving Internal Preference Contradictions
Xu Zhang, Xunjian Yin, Xiaojun Wan
While substantial advancements have been made in developing large language models (LLMs), achieving control over their behavior can be difficult. Direct preference optimization (DP…
MC-MKE: A Fine-Grained Multimodal Knowledge Editing Benchmark Emphasizing Modality Consistency
Junzhe Zhang, Huixuan Zhang, Xunjian Yin +4
Multimodal large language models (MLLMs) are prone to non-factual or outdated knowledge issues, which can manifest as misreading and misrecognition errors due to the complexity of…
Enhancing Jailbreak Attacks with Diversity Guidance
Xu Zhang, Dinghao Jing, Xiaojun Wan
As large language models(LLMs) become commonplace in practical applications, the security issues of LLMs have attracted societal concerns. Although extensive efforts have been made…
Benchmarking Knowledge Boundary for Large Language Models: A Different Perspective on Model Evaluation
Xunjian Yin, Xu Zhang, Jie Ruan +1
In recent years, substantial advancements have been made in the development of large language models, achieving remarkable performance across diverse tasks. To evaluate the knowled…
An Empirical Study of Automatic Post-Editing
Xu Zhang, Xiaojun Wan
Automatic post-editing (APE) aims to reduce manual post-editing efforts by automatically correcting errors in machine-translated output. Due to the limited amount of human-annotate…