4 citations · 4 across the 6 of their papers we have counts for
6 papers · 1 filter
Understanding Machine Taste: Aesthetic Agreement Across Foundation Models in K-pop
Kaishen Wang, Yucheng Pan, Xuehao Cui +2
As foundation models enter creative industries, understanding their aesthetic preferences becomes an important step toward AI-assisted creative decision making. In this work, we in…
InjecMEM: Memory Injection Attack on LLM Agent Memory Systems
Hanling Tian, Gengyu Zhang, Zeyang Sha +5
Memory is becoming a default subsystem in deployed LLM agents to provide persistent personalization and continuity. This naturally prompts a question: will memory system introduce…
CARE-LoRA: Compressed Activation REconstruction for Memory-Efficient LoRA
Gengyu Zhang, Haiyin Ran, Zhengbao He +4
As the scale of large pre-trained models continues to grow, fine-tuning them under limited memory budgets has become increasingly challenging. Low-Rank Adaptation (LoRA), currently…
Stochastic Optimal Control Sampling for Diffusion Inverse Problems
Jie Zhang, Youmei Qiu, Hanling Tian +3
Benefiting from the strong ability to capture data distributions, diffusion models have become powerful tools for solving image inverse problems. The key is to controllably steer t…
SAGE: Retain-Aware Post-Hoc Sanitization of Final Unlearning Vector
Jingyuan Zhang, Yucheng Bai, Peixi Wen +6
Large Language Model (LLM) unlearning aims to remove undesirable knowledge or behaviors while preserving retained capabilities. Current unlearning methods all involve a trade-off b…
RAIN-Merging: A Gradient-Free Method to Enhance Instruction Following in Large Reasoning Models with Preserved Thinking Format
Zhehao Huang, Yuhang Liu, Baijiong Lin +5
Large reasoning models (LRMs) excel at a long chain of reasoning but often fail to faithfully follow instructions regarding output format, constraints, or specific requirements. We…