80 citations · 211 across the 42 of their papers we have counts for
6 papers · 1 filter
R^2-Mem: Reflective Experience for Memory Search
Xinyuan Wang, Wenyu Mao, Junkang Wu +2
Deep search has recently emerged as a promising paradigm for enabling agents to retrieve fine-grained historical information without heavy memory pre-managed. However, existing dee…
Contrastive Weak-to-strong Generalization
Houcheng Jiang, Junfeng Fang, Jiaxin Wu +5
Weak-to-strong generalization provides a promising paradigm for scaling large language models (LLMs) by training stronger models on samples from aligned weaker ones, without requir…
bi-GRPO: Bidirectional Optimization for Jailbreak Backdoor Injection on LLMs
Wence Ji, Jiancan Wu, Aiying Li +5
With the rapid advancement of large language models (LLMs), their robustness against adversarial manipulations, particularly jailbreak backdoor attacks, has become critically impor…
DualEdit: Mitigating Safety Fallback in LLM Backdoor Editing via Affirmation-Refusal Regulation
Houcheng Jiang, Zetong Zhao, Junfeng Fang +5
Safety-aligned large language models (LLMs) remain vulnerable to backdoor attacks. Recent model editing-based approaches enable efficient backdoor injection by directly modifying a…
AnyEdit: Edit Any Knowledge Encoded in Language Models
Houcheng Jiang, Junfeng Fang, Ningyu Zhang +5
Large language models (LLMs) often produce incorrect or outdated information, necessitating efficient and precise knowledge updates. Current model editing methods, however, struggl…
AlphaEdit: Null-Space Constrained Knowledge Editing for Language Models
Junfeng Fang, Houcheng Jiang, Kun Wang +5
Large language models (LLMs) often exhibit hallucinations due to incorrect or outdated knowledge. Hence, model editing methods have emerged to enable targeted knowledge updates. To…