most citedStep-Audio: Unified Understanding and Generation in Intelligent Speech Interaction

1 citations · 1 across the 6 of their papers we have counts for

collaborators

7 papers

cs.AI2026

Learner-Tailored Program Repair: A Solution Generator with Iterative Edit-Driven Retrieval Enhancement

Zhenlong Dai, Zhuoluo Zhao, Hengning Wang +5

With the development of large language models (LLMs) in the field of programming, intelligent programming coaching systems have gained widespread attention. However, most research…

cs.AI2026

Thinking Traps in Long Chain-of-Thought: A Measurable Study and Trap-Aware Adaptive Restart

Kang Chen, Fan Yu, Junjie Nian +6

Scaling test-time compute via Long Chain-of-Thought (Long-CoT) significantly enhances reasoning capabilities, yet extended generation does not guarantee correctness: after an early…

cs.CL2025

Step-DeepResearch Technical Report

Chen Hu, Haikuo Du, Heng Wang +64

As LLMs shift toward autonomous agents, Deep Research has emerged as a pivotal metric. However, existing academic benchmarks like BrowseComp often fail to meet real-world demands f…

cs.LG2025

Step-3 is Large yet Affordable: Model-system Co-design for Cost-effective Decoding

StepFun, :, Bin Wang +195

Large language models (LLMs) face low hardware efficiency during decoding, especially for long-context reasoning tasks. This paper introduces Step-3, a 321B-parameter VLM with hard…

cs.SD2025

Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Model

Ailin Huang, Bingxin Li, Bruce Wang +73

Large Audio-Language Models (LALMs) have significantly advanced intelligent human-computer interaction, yet their reliance on text-based outputs limits their ability to generate na…

cs.CL20251 cited

Step-Audio: Unified Understanding and Generation in Intelligent Speech Interaction

Ailin Huang, Boyong Wu, Bruce Wang +142

Real-time speech interaction, serving as a fundamental interface for human-machine collaboration, holds immense potential. However, current open-source models face limitations such…