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Researcher
Zifeng Wang
Research Scientist at Google Cloud AI Research at Google
Zifeng Wang is a Research Scientist at Google Cloud AI Research working on large language models, LLM agents and multi-agent systems, environment scaling, and agentic post-training.
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Nov 2025 — May 2026
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Most recent firstArticles Written
Zifeng Wang as author
Google Researchers Show SRL Gives 7B Models Better Structured Reasoning by Rewarding Partial Step Correctness
arXivresearchpositiveNov 3, 2025
Google researchers introduce Supervised Reinforcement Learning (SRL), a training framework that enables 7B parameter models to achieve better multi-step reasoning by providing step-wise reward signals based on expert action similarity rather than token-by-token imitation.
“Author of "Google Researchers Show SRL Gives 7B Models Better Structured Reasoning by Rewar" on arXiv”
AI ResearchReinforcement LearningLLMsFoundation Models
Also Mentioned In
Referenced in coverage
SkillOS: Learning Skill Curation for Self-Evolving Agents
UIUC, Google, and other institutionspositiveMay 10, 2026
“Co-author of SkillOS paper on learning skill curation for self-evolving LLM agents.”