7 papers
Breaking the Tie: A Cluster-Aware Routing Framework for Large Language Models
Yao Lu, Zhaiyuan Ji, Yaxin Gao +6
With the rapid development of artificial intelligence, the emergence of various Large Language Models (LLMs) has created a rich model ecosystem. However, this also brings a key cha…
Revisiting Diffusion Fine-Tuning for Unsupervised Domain Adaptation
Xuan Qi, Yi Wei, Daniele Berardini +2
Diffusion-based unsupervised domain adaptation (UDA) improves cross-domain transfer by generating target-specific synthetic data for downstream adaptation. Existing methods are lar…
CODEBLOCK: Learning to Supervise Code at the Right Granularity
Zhijie Deng, Ling Li, Jinlong Pang +5
Supervised fine-tuning of code LLMs typically applies uniform cross-entropy loss to all response tokens, implicitly assuming that every token provides equally useful learning signa…
Improving the Convergence Rate of Ray Search Optimization for Query-Efficient Hard-Label Attacks
Xinjie Xu, Shuyu Cheng, Dongwei Xu +2
In hard-label black-box adversarial attacks, where only the top-1 predicted label is accessible, the prohibitive query complexity poses a major obstacle to practical deployment. In…
Boosting Ray Search Procedure of Hard-label Attacks with Transfer-based Priors
Chen Ma, Xinjie Xu, Shuyu Cheng +1
One of the most practical and challenging types of black-box adversarial attacks is the hard-label attack, where only the top-1 predicted label is available. One effective approach…
Better Reasoning with Less Data: Enhancing VLMs Through Unified Modality Scoring
Mingjie Xu, Andrew Estornell, Hongzheng Yang +4
The application of visual instruction tuning and other post-training techniques has significantly enhanced the capabilities of Large Language Models (LLMs) in visual understanding,…
GUARD: Generation-time LLM Unlearning via Adaptive Restriction and Detection
Zhijie Deng, Chris Yuhao Liu, Zirui Pang +5
Large Language Models (LLMs) have demonstrated strong capabilities in memorizing vast amounts of knowledge across diverse domains. However, the ability to selectively forget specif…