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researcher

Jun Jiang

4 papers hereh-index 272.5k citations120 works total

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

author position
  • middle author2
  • last author1

Across the 3 of 4 papers where every author was matched, so the position is known.

fields
  • cs.AI2
  • physics.chem-ph2
same name
  • Jun Jiang — 11 papers, h 4
  • Jun Jiang — 10 papers, h 12
  • Jun Jiang — 9 papers, h 11
  • Jun Jiang — 6 papers
  • Jun Jiang — 5 papers, h 23
  • Jun Jiang — 5 papers, h 6

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
20202026
most citedStress-testing large language model agents in a robotic chemistry laboratory

1 citations · 1 across the 2 of their papers we have counts for

collaborators

4 papers

cs.AI2026★ 1 cited

Stress-testing large language model agents in a robotic chemistry laboratory

Lulu Guo, Yingkai Sun, Xiaobo Li +13

AI is evaluated through knowledge, reasoning and plan generation, yet scientific agency requires reliable physical action and adaptation to evidence. Here, we use a robotic chemist…

cs.AI2026

Language models guide symbolic equation discovery by controlling search

Zikai Xie, Wenmei Li, Man Luo +2

Scientific equation discovery must combine broad domain priors with strict numerical testing. Symbolic regression supplies numerical grounding but faces a combinatorial search spac…

physics.chem-ph2021

Learning Dipole Moments and Polarizabilities

Yaolong Zhang, Jun Jiang, Bin Jiang

Machine learning of scalar molecular properties such as potential energy has enabled widespread applications. However, there are relatively few machine learning models targeting di…

physics.chem-ph2020

Efficient and Accurate Simulations of Vibrational and Electronic Spectra with Symmetry-Preserving Neural Network Models for Tensorial Properties

Yaolong Zhang, Sheng Ye, Jinxiao Zhang +3

Machine learning has revolutionized the high-dimensional representations for molecular properties such as potential energy. However, there are scarce machine learning models target…

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