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researcher

Wei He

Fudan University

21 papers hereh-index 162.7k citations29 works total

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

author position
  • first author3
  • middle author15

Across the 18 of 21 papers where every author was matched, so the position is known.

fields
  • cs.CL12
  • cs.AI6
  • cs.CV1
  • cs.LG1
  • cs.SE1
affiliations
  • Fudan University
HomepageORCID 0009-0002-9240-5330
same name
  • Wei He — 18 papers, h 13
  • Wei He — 16 papers, h 7
  • Wei He — 14 papers, h 8
  • Wei He — 13 papers, h 6
  • Wei He — 10 papers, h 27
  • Wei He — 9 papers, h 23

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

activity
20232026
most citedThe Rise and Potential of Large Language Model Based Agents: A Survey

256 citations · 274 across the 19 of their papers we have counts for

collaborators
Showing 2025 · cs.CLShow all

4 papers · 2 filters

cs.CL2025

VitaBench: Benchmarking LLM Agents with Versatile Interactive Tasks in Real-world Applications

Wei He, Yueqing Sun, Hongyan Hao +13

As LLM-based agents are increasingly deployed in real-life scenarios, existing benchmarks fail to capture their inherent complexity of handling extensive information, leveraging di…

cs.CL2025★ 1 cited

LongCat-Flash Technical Report

Meituan LongCat Team, Bayan, Bei Li +179

We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…

cs.CL2025

Better Process Supervision with Bi-directional Rewarding Signals

Wenxiang Chen, Wei He, Zhiheng Xi +9

Process supervision, i.e., evaluating each step, is critical for complex large language model (LLM) reasoning and test-time searching with increased inference compute. Existing app…

cs.CL2025

Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation

Songjun Tu, Jiahao Lin, Xiangyu Tian +8

Recent advancements in post-training methodologies for large language models (LLMs) have highlighted reinforcement learning (RL) as a critical component for enhancing reasoning. Ho…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.