most citedMind-Paced Speaking: A Dual-Brain Approach to Real-Time Reasoning in Spoken Language Models

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cs.CL2026

Self-Guided Test-Time Training for Long-Context LLMs

Xinyu Zhu, Zhe Xu, Xiaohan Wei +10

Long-context processing has become increasingly important for large language models (LLMs), but simply extending the context window does not guarantee effective utilization of long…

cs.CL20261 cited

Chronological Thinking in Full-Duplex Spoken Dialogue Language Models

Donghang Wu, Haoyang Zhang, Chen Chen +8

Recent advances in spoken dialogue language models (SDLMs) reflect growing interest in shifting from turn-based to full-duplex systems, where the models continuously perceive user…

cs.CL2026

Learning Evidence Highlighting for Frozen LLMs

Shaoang Li, Yanhang Shi, Yufei Li +10

Large Language Models (LLMs) can reason well, yet often miss decisive evidence when it is buried in long, noisy contexts. We introduce HiLight, an Evidence Emphasis framework that…

cs.CL20261 cited

Mind-Paced Speaking: A Dual-Brain Approach to Real-Time Reasoning in Spoken Language Models

Donghang Wu, Haoyang Zhang, Jun Chen +9

Real-time Spoken Language Models (SLMs) struggle to leverage Chain-of-Thought (CoT) reasoning due to the prohibitive latency of generating the entire thought process sequentially.…

cs.CL2025

Step-Audio-EditX Technical Report

Chao Yan, Boyong Wu, Peng Yang +12

We present Step-Audio-EditX, the first open-source LLM-based audio model excelling at expressive and iterative audio editing encompassing emotion, speaking style, and paralinguisti…

cs.CL2025

Step-Audio 2 Technical Report

Boyong Wu, Chao Yan, Chen Hu +106

This paper presents Step-Audio 2, an end-to-end multi-modal large language model designed for industry-strength audio understanding and speech conversation. By integrating a latent…