Yao Tang

This paper proposes NF-CoT, a latent reasoning framework that preserves the advantages of chain-of-thought in large language models.

A cross-fused generative framework is proposed for low-overhead beam alignment in Uniform Planar Array systems using a decoupled channel sensing strategy and a bidirectional cross-attention encoder.

The paper proposes ECHO, a selective turn-memory framework for long-horizon language agents that addresses history collapse and traceable learning through source-indexed reconstruction.

This paper proposes BrainAgent, an agentic LLM framework for knowledge-enhanced brain network analysis, which improves performance and produces more comprehensive, multi-level, and verifiable explanations.