activity
20232026
most citedAutoDefense: Multi-Agent LLM Defense against Jailbreak Attacks

11 citations · 20 across the 14 of their papers we have counts for

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Showing 2025Show all

9 papers · 1 filter

cs.CL2025

Entropy-Guided Token Dropout: Training Autoregressive Language Models with Limited Domain Data

Jiapeng Wang, Yiwen Hu, Yanzipeng Gao +7

As access to high-quality, domain-specific data grows increasingly scarce, multi-epoch training has become a practical strategy for adapting large language models (LLMs). However,…

cs.SE2025

When More Retrieval Hurts: Retrieval-Augmented Code Review Generation

Qianru Meng, Xiao Zhang, Zhaochen Ren +1

Code review generation can reduce developer effort by producing concise, reviewer-style feedback for a given code snippet or code change. However, generation-only models often prod…

cs.LG2025

Merge and Guide: Unifying Model Merging and Guided Decoding for Controllable Multi-Objective Generation

Guofu Xie, Chen Zhang, Xiao Zhang +3

Adapting to diverse user needs at test time is a key challenge in controllable multi-objective generation. Existing methods are insufficient: merging-based approaches provide indir…

cs.LG2025

CAPO: Towards Enhancing LLM Reasoning through Generative Credit Assignment

Guofu Xie, Yunsheng Shi, Hongtao Tian +2

Reinforcement Learning with Verifiable Rewards (RLVR) has improved the reasoning abilities of Large Language Models (LLMs) by using rule-based binary feedback. However, current RLV…

cs.AI2025

LightPROF: A Lightweight Reasoning Framework for Large Language Model on Knowledge Graph

Tu Ao, Yanhua Yu, Yuling Wang +7

Large Language Models (LLMs) have impressive capabilities in text understanding and zero-shot reasoning. However, delays in knowledge updates may cause them to reason incorrectly o…

cs.CL2025

DREAM: Disentangling Risks to Enhance Safety Alignment in Multimodal Large Language Models

Jianyu Liu, Hangyu Guo, Ranjie Duan +14

Multimodal Large Language Models (MLLMs) pose unique safety challenges due to their integration of visual and textual data, thereby introducing new dimensions of potential attacks…

cs.IR2025

VALUE: Value-Aware Large Language Model for Query Rewriting via Weighted Trie in Sponsored Search

Xiao Zhang, Guanyu Chen, Boyang Zuo +4

Query-to-bidword(i.e., bidding keyword) rewriting is fundamental to sponsored search, transforming noisy user queries into semantically relevant and commercially valuable keywords.…

cs.CL2025

Multidimensional Consistency Improves Reasoning in Language Models

Huiyuan Lai, Xiao Zhang, Malvina Nissim

While Large language models (LLMs) have proved able to address some complex reasoning tasks, we also know that they are highly sensitive to input variation, which can lead to diffe…

cs.LG2025

Bone Soups: A Seek-and-Soup Model Merging Approach for Controllable Multi-Objective Generation

Guofu Xie, Xiao Zhang, Ting Yao +1

User information needs are often highly diverse and varied. A key challenge in current research is how to achieve controllable multi-objective generation while enabling rapid adapt…