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20242026
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cs.CL2026

Step 3.5 Flash: Open Frontier-Level Intelligence with 11B Active Parameters

Ailin Huang, Ang Li, Aobo Kong +213

We introduce Step 3.5 Flash, a sparse Mixture-of-Experts (MoE) model that bridges frontier-level agentic intelligence and computational efficiency. We focus on what matters most wh…

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.CL2025

Learning to Compress: Unlocking the Potential of Large Language Models for Text Representation

Yeqin Zhang, Yizheng Zhao, Chen Hu +4

Text representation plays a critical role in tasks like clustering, retrieval, and other downstream applications. With the emergence of large language models (LLMs), there is incre…

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…

cs.CL2025

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…

cs.CL2024

CFSafety: Comprehensive Fine-grained Safety Assessment for LLMs

Zhihao Liu, Chenhui Hu

As large language models (LLMs) rapidly evolve, they bring significant conveniences to our work and daily lives, but also introduce considerable safety risks. These models can gene…