James Lee-Thorp

999 citations
14 papers · 332 indexed · 1 hit paper · h-index 8

Impact in

Papers in

James Lee-Thorp

14 papers receiving 309 citations

Hit Papers

GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints 2023 · 124 citations
12420232026202420254080120

Peers

James Lee-Thorp
Comparison fields: 5 of 72
  • Health Informatics 13
  • Atomic and Molecular Physics, and Optics 148
  • Mathematical Physics 41
  • Statistical and Nonlinear Physics 38
  • Artificial Intelligence 90
Replace Larry Chen with:
Larry Chen United States
Christopher L. Baldwin United States
Jan Muhammad China
Jacob van den Berg Netherlands
Nick Wright United Kingdom
Yichen Ye China
Valter Moretti Italy
E. Novais Brazil
S. Xian China
Qiming Li China
James Lee-Thorp relative to Larry Chen United States Larry Chen's profile →
Citations per field
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Larry Chen · 1×
Citations per year

Countries citing papers authored by James Lee-Thorp

Since Specialization
Citations

This map shows the geographic impact of James Lee-Thorp's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by James Lee-Thorp with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James Lee-Thorp more than expected).

Fields of papers citing papers by James Lee-Thorp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James Lee-Thorp. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by James Lee-Thorp. The network helps show where James Lee-Thorp may publish in the future.

Co-authorship network

The 25 scholars most cited alongside James Lee-Thorp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with James Lee-Thorp Line = papers co-authored together James Lee-Thorp links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 20242
2
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints
Hit paper breakdown →
2023124
3 202318
4 20222
5 20206
6 201840
7 201713
8 201745
9 20163
10 20162
11 201613
12 20161
13 201613
14 201450

About James Lee-Thorp

James Lee-Thorp is a scholar working on Atomic and Molecular Physics, and Optics, Artificial Intelligence, Materials Chemistry, Geometry and Topology and Atmospheric Science, having authored 14 papers that have together received 332 indexed citations. Recurring topics across this work include Topological Materials and Phenomena (6 papers), Graphene research and applications (4 papers), Photonic and Optical Devices (3 papers), Photonic Crystals and Applications (3 papers), Topic Modeling (3 papers), Natural Language Processing Techniques (3 papers), Crystallization and Solubility Studies (2 papers) and nanoparticles nucleation surface interactions (2 papers). The work is most often cited by research in Health Informatics (13 citations), Atomic and Molecular Physics, and Optics (148 citations), Mathematical Physics (41 citations), Statistical and Nonlinear Physics (38 citations) and Artificial Intelligence (90 citations). James Lee-Thorp has collaborated with scholars based in United States and China. Frequent co-authors include Michael I. Weinstein, Charles Fefferman, Joshua Ainslie, Yury Zemlyanskiy, Michiel de Jong, Yi Zhu, Robert V. Kohn, Alexander G. Shtukenberg, Jun Yang and Yun-Hsuan Sung. Their work appears in journals such as Crystal Growth & Design, Communications on Pure and Applied Mathematics, Archive for Rational Mechanics and Analysis, Physical review. A and Proceedings of the National Academy of Sciences.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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