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Chengcheng Han

7 accepted papers

2025

MUSE: MCTS-Driven Red Teaming Framework for Enhanced Multi-Turn Dialogue Safety in Large Language Models

EMNLP 2025

As large language models (LLMs) become widely adopted, ensuring their alignment with human values is crucial to prevent jailbreaks where adversaries manipulate models to produce harmful content. While most defenses target single-turn attacks, real-world usage often involves multi-turn dialogues, exp

2025

RMoA: Optimizing Mixture-of-Agents through Diversity Maximization and Residual Compensation

ACL 2025finding

Although multi-agent systems based on large language models show strong capabilities on multiple tasks, they are still limited by high computational overhead, information loss, and robustness. Inspired by ResNet’s residual learning, we propose Residual Mixture-of-Agents (RMoA), integrating residual…

2024

Automated Peer Reviewing in Paper SEA: Standardization, Evaluation, and Analysis

EMNLP 2024finding

In recent years, the rapid increase in scientific papers has overwhelmed traditional review mechanisms, resulting in varying quality of publications. Although existing methods have explored the capabilities of Large Language Models (LLMs) for automated scientific reviewing, their generated contents…

2024

Conjoin after Decompose: Improving Few-Shot Performance of Named Entity Recognition

COLING 2024main

Prompt-based methods have been widely used in few-shot named entity recognition (NER). In this paper, we first conduct a preliminary experiment and observe that the key to affecting the performance of prompt-based NER models is the capability to detect entity boundaries. However, most existing model…

2024

Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives

COLING 2024main

Large language models (LLMs) have shown increasing power on various natural language processing (NLP) tasks. However, tuning these models for downstream tasks usually needs exorbitant costs or is unavailable due to commercial considerations. Recently, black-box tuning has been proposed to address th…

2023

DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models

EMNLP 2023long main

Chain-of-Thought (CoT) prompting has successfully enhanced the reasoning capabilities of Large Language Models~(LLMs) with at least 100 billion parameters. However, it is ineffective, or even detrimental, to the performance on reasoning tasks in Smaller Language Models (SLMs) with less than 10 billi…

Cited by 0SourcecodeScholar
2023

When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario

ACL 2023findings

Large pre-trained language models (PLMs) have garnered significant attention for their versatility and potential for solving a wide spectrum of natural language processing (NLP) tasks. However, the cost of running these PLMs may be prohibitive. Furthermore, PLMs may not be open-sourced due to commer…

Cited by 8SourcePDFScholar