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Dongzhan Zhou

32 papers hereh-index 6151 citations29 works total

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

author position
  • middle author20
  • last author6

Across the 26 of 32 papers where every author was matched, so the position is known.

fields
  • cs.RO11
  • cs.AI10
  • cs.LG4
  • cs.CL2
  • cs.CV2
  • cs.DB1
same name
  • Dongzhan Zhou — 46 papers, h 18
  • Dongzhan Zhou — 6 papers, h 4
  • Dongzhan Zhou — 6 papers, h 2
  • Dongzhan Zhou — 5 papers, h 4
  • Dongzhan Zhou — 3 papers
  • Dongzhan Zhou — 3 papers, h 2

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

most citedPosition: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI

2 citations · 3 across the 26 of their papers we have counts for

collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

ResearchClawBench: A Benchmark for End-to-End Autonomous Scientific Research

Wanghan Xu, Shuo Li, Tianlin Ye +48

AI coding agents are increasingly used for scientific work, but their end-to-end autonomous research capability remains difficult to verify. We present ResearchClawBench, a benchma…

cs.LG2025

P1: Mastering Physics Olympiads with Reinforcement Learning

Jiacheng Chen, Qianjia Cheng, Fangchen Yu +25

Recent progress in large language models (LLMs) has moved the frontier from puzzle-solving to science-grade reasoning-the kind needed to tackle problems whose answers must stand ag…

cs.LG2025

Intern-S1: A Scientific Multimodal Foundation Model

Lei Bai, Zhongrui Cai, Yuhang Cao +173

In recent years, a plethora of open-source foundation models have emerged, achieving remarkable progress in some widely attended fields, with performance being quite close to that…

cs.LG2025

When Dynamic Data Selection Meets Data Augmentation

Suorong Yang, Peng Ye, Furao Shen +1

Dynamic data selection aims to accelerate training with lossless performance. However, reducing training data inherently limits data diversity, potentially hindering generalization…

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