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Linfeng Zhang

8 papers hereh-index 324 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author6

Across the 7 of 8 papers where every author was matched, so the position is known.

fields
  • cs.AI4
  • cs.LG2
  • hep-lat1
  • quant-ph1
same name
  • Linfeng Zhang — 25 papers, h 15
  • Linfeng Zhang — 21 papers, h 5
  • Linfeng Zhang — 21 papers, h 10
  • Linfeng Zhang — 17 papers, h 8
  • Linfeng Zhang — 15 papers, h 7
  • Linfeng Zhang — 15 papers, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators
Showing cs.AIShow all

4 papers · 1 filter

cs.AI2026

Emergent Slow Thinking in LLMs as Inverse Tree Freezing

Sihan Hu, Xiansheng Cai, Yuan Huang +5

Reinforcement learning with verifiable rewards (RLVR) enables large language models to acquire slow, multi-step reasoning from sparse final-answer signals. We provide a statistical…

cs.AI2026

Inverse Knowledge Search over Verifiable Reasoning: Synthesizing a Scientific Encyclopedia from a Long Chains-of-Thought Knowledge Base

Yu Li, Yuan Huang, Tao Wang +19

Most scientific materials compress reasoning, presenting conclusions while omitting the derivational chains that justify them. This compression hinders verification by lacking expl…

cs.AI2025

Bohrium + SciMaster: Building the Infrastructure and Ecosystem for Agentic Science at Scale

Linfeng Zhang, Siheng Chen, Yuzhu Cai +46

AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning with tool use and verification, pointing to a shift from isolated AI-assi…

cs.AI2025

PhysMaster: Building an Autonomous AI Physicist for Theoretical and Computational Physics Research

Tingjia Miao, Jiawen Dai, Jingkun Liu +23

Advances in LLM reasoning and tool use have enabled agentic science, yet frontier theoretical and computational physics remains challenging because research requires deep domain ex…

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