5 citations · 6 across the 8 of their papers we have counts for
10 papers
RA: Retain-Anchored Attraction Preserves Forget-Adjacent Utility in LLM Unlearning
Zinan Ling, Yang Xiao, Ruimeng Ye +2
Large Language Model (LLM) unlearning is often evaluated primarily by target suppression and clean retain utility. These metrics can miss a local failure mode: a model may perform…
Compressed Video Aggregator: Content-driven Module for Efficient Micro-Video Recommendation
Yang Xiao, Huiyuan Chen, Kaiyuan Deng +6
We propose \textbf{Compressed Video Aggregator} (CVA), a lightweight micro-video recommendation module that decouples video information from preference learning. CVA first summariz…
Your Language Model Secretly Contains Personality Subnetworks
Ruimeng Ye, Zihan Wang, Zinan Ling +4
Humans shift between different personas depending on social context. Large Language Models (LLMs) demonstrate a similar flexibility in adopting different personas and behaviors. Ex…
Efficient Knowledge Graph Unlearning with Zeroth-order Information
Yang Xiao, Ruimeng Ye, Bohan Liu +2
Due to regulations like the Right to be Forgotten, there is growing demand for removing training data and its influence from models. Since full retraining is costly, various machin…
Weak-to-Strong Generalization with Failure Trajectories: A Tree-based Approach to Elicit Optimal Policy in Strong Models
Ruimeng Ye, Zihan Wang, Yang Xiao +3
Weak-to-Strong generalization (W2SG) is a new trend to elicit the full capabilities of a strong model with supervision from a weak model. While existing W2SG studies focus on simpl…
The Right to be Forgotten in Pruning: Unveil Machine Unlearning on Sparse Models
Yang Xiao, Gen Li, Jie Ji +3
Machine unlearning aims to efficiently eliminate the memory about deleted data from trained models and address the right to be forgotten. Despite the success of existing unlearning…
Optimal Transport for Brain-Image Alignment: Unveiling Redundancy and Synergy in Neural Information Processing
Yang Xiao, Wang Lu, Jie Ji +4
The design of artificial neural networks (ANNs) is inspired by the structure of the human brain, and in turn, ANNs offer a potential means to interpret and understand brain signals…
DBA-DFL: Towards Distributed Backdoor Attacks with Network Detection in Decentralized Federated Learning
Bohan Liu, Yang Xiao, Ruimeng Ye +3
Distributed backdoor attacks (DBA) have shown a higher attack success rate than centralized attacks in centralized federated learning (FL). However, it has not been investigated in…
Weak-to-Strong Generalization beyond Accuracy: a Pilot Study in Safety, Toxicity, and Legal Reasoning
Ruimeng Ye, Yang Xiao, Bo Hui
As large language models (LLMs) continue to advance, ensuring their alignment with human values becomes increasingly critical. Traditional alignment methods heavily rely on human f…
A Survey of Lottery Ticket Hypothesis
Bohan Liu, Zijie Zhang, Peixiong He +6
The Lottery Ticket Hypothesis (LTH) states that a dense neural network model contains a highly sparse subnetwork (i.e., winning tickets) that can achieve even better performance th…