23 citations · 156 across the 51 of their papers we have counts for
6 papers · 1 filter
Before Agent Tells The Lie: Has Deception Already Been Represented?
Xinling Li, Dadi Guo, Qingyu Liu +5
Large language model (LLM)-based agents can exhibit deceptive behavior during task execution, including hiding failures, fabricating results, or falsely signaling task completion.…
Faithful Activation Verbalization: Reducing Hallucinations in LLM Representation Interpretation
Haiyan Zhao, Zirui Hei, Wei Shi +3
Activation verbalization methods such as Activation Oracle and Natural Language Autoencoders decode hidden representations of large language models into human-readable natural lang…
Cleansing the Artificial Mind: A Self-Reflective Detoxification Framework for Large Language Models
Kaituo Zhang, Zhimeng Jiang, Na Zou
Recent breakthroughs in Large Language Models (LLMs) have revealed remarkable generative capabilities and emerging self-regulatory mechanisms, including self-correction and self-re…
Rethinking the Understanding Ability across LLMs through Mutual Information
Shaojie Wang, Sirui Ding, Na Zou
Recent advances in large language models (LLMs) have revolutionized natural language processing, yet evaluating their intrinsic linguistic understanding remains challenging. Moving…
MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation
Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh +8
Large Language Models (LLMs) are becoming essential tools for various natural language processing tasks but often suffer from generating outdated or incorrect information. Retrieva…
Shortcut Learning of Large Language Models in Natural Language Understanding
Mengnan Du, Fengxiang He, Na Zou +2
Large language models (LLMs) have achieved state-of-the-art performance on a series of natural language understanding tasks. However, these LLMs might rely on dataset bias and arti…