3 papers
cs.LG2026
Beyond Activation Patterns: A Weight-Based Out-of-Context Explanation of Sparse Autoencoder Features
Yiting Liu, Zhi-Hong Deng
Sparse autoencoders (SAEs) have emerged as a powerful technique for decomposing language model representations into interpretable features. Current interpretation methods infer fea…
cs.LG2025
FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
Yunbo Li, Jiaping Gui, Zhihang Deng +2
Federated learning (FL) enables collaborative model training across multiple parties without sharing raw data, with semi-asynchronous FL (SAFL) emerging as a balanced approach betw…
cs.CL2025
SDA: Steering-Driven Distribution Alignment for Open LLMs without Fine-Tuning
Wei Xia, Zhi-Hong Deng
With the rapid advancement of large language models (LLMs), their deployment in real-world applications has become increasingly widespread. LLMs are expected to deliver robust perf…