9 citations · 16 across the 14 of their papers we have counts for
6 papers · 1 filter
Skywork-Reward-V2: Scaling Preference Data Curation via Human-AI Synergy
Chris Yuhao Liu, Liang Zeng, Yuzhen Xiao +9
Despite the critical role of reward models (RMs) in Reinforcement Learning from Human Feedback (RLHF), current state-of-the-art open RMs perform poorly on most existing evaluation…
Skywork-SWE: Unveiling Data Scaling Laws for Software Engineering in LLMs
Liang Zeng, Yongcong Li, Yuzhen Xiao +8
Software engineering (SWE) has recently emerged as a crucial testbed for next-generation LLM agents, demanding inherent capabilities in two critical dimensions: sustained iterative…
AgentOrchestra: Orchestrating Multi-Agent Intelligence with the Tool-Environment-Agent(TEA) Protocol
Wentao Zhang, Liang Zeng, Yuzhen Xiao +7
Recent advances in LLM-based agent systems have shown promise on complex, long-horizon tasks, but existing agent protocols (e.g., A2A and MCP) do not adequately support lifecycle-a…
Skywork Open Reasoner 1 Technical Report
Jujie He, Jiacai Liu, Chris Yuhao Liu +14
The success of DeepSeek-R1 underscores the significant role of reinforcement learning (RL) in enhancing the reasoning capabilities of large language models (LLMs). In this work, we…
SAT-LDM: Provably Generalizable Image Watermarking for Latent Diffusion Models with Self-Augmented Training
Lu Zhang, Liang Zeng
The rapid proliferation of AI-generated images necessitates effective watermarking techniques to protect intellectual property and detect fraudulent content. While existing trainin…
Translate Policy to Language: Flow Matching Generated Rewards for LLM Explanations
Xinyi Yang, Liang Zeng, Heng Dong +6
As humans increasingly share environments with diverse agents powered by RL, LLMs, and beyond, the ability to explain agent policies in natural language is vital for reliable coexi…