Guillaume Lample

16.3k total citations · 3 hit papers
13 papers, 4.2k citations indexed

About

Guillaume Lample is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Sociology and Political Science. According to data from OpenAlex, Guillaume Lample has authored 13 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Artificial Intelligence, 3 papers in Computer Vision and Pattern Recognition and 1 paper in Sociology and Political Science. Recurrent topics in Guillaume Lample's work include Natural Language Processing Techniques (8 papers), Topic Modeling (7 papers) and Reinforcement Learning in Robotics (3 papers). Guillaume Lample is often cited by papers focused on Natural Language Processing Techniques (8 papers), Topic Modeling (7 papers) and Reinforcement Learning in Robotics (3 papers). Guillaume Lample collaborates with scholars based in Israel, United States and France. Guillaume Lample's co-authors include Sandeep Subramanian, Chris Dyer, Miguel Ballesteros, Kazuya Kawakami, Alexis Conneau, Devendra Singh Chaplot, Marc’Aurelio Ranzato, Ludovic Denoyer, Ruty Rinott and Adina Williams and has published in prestigious journals such as HAL (Le Centre pour la Communication Scientifique Directe), arXiv (Cornell University) and Neural Information Processing Systems.

In The Last Decade

Guillaume Lample

13 papers receiving 3.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Neural Architectures for Named Entity Recognition

2016 2.5k citations Guillaume Lample, Miguel Ballesteros et al. profile →
XNLI: Evaluating Cross-lingual Sentence Representations

2018 499 citations Alexis Conneau, Ruty Rinott et al. profile →
Word translation without parallel data

2018 306 citations Guillaume Lample, Alexis Conneau et al. International Conference on Learning Representations profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Guillaume Lample Israel	10	3.8k	713	418	379	314	13	4.2k
Gerard de Melo Germany	28	2.6k 0.7×	651 0.9×	316 0.8×	601 1.6×	323 1.0×	176	3.4k
Yue Zhang China	43	5.7k 1.5×	938 1.3×	381 0.9×	721 1.9×	408 1.3×	220	6.7k
Miguel Ballesteros Spain	19	3.4k 0.9×	455 0.6×	452 1.1×	399 1.1×	289 0.9×	58	3.9k
Praveen Paritosh United States	12	2.9k 0.8×	417 0.6×	207 0.5×	605 1.6×	641 2.0×	32	3.5k
Tianyu Gao China	13	2.9k 0.8×	759 1.1×	155 0.4×	397 1.0×	147 0.5×	19	3.3k
Dipanjan Das United States	26	4.0k 1.1×	726 1.0×	243 0.6×	654 1.7×	146 0.5×	68	4.8k
Xu Sun China	33	2.7k 0.7×	934 1.3×	169 0.4×	443 1.2×	187 0.6×	116	3.3k
Pontus Stenetorp United Kingdom	18	3.0k 0.8×	509 0.7×	426 1.0×	339 0.9×	407 1.3×	49	3.4k
Nanyun Peng United States	29	2.9k 0.8×	826 1.2×	215 0.5×	276 0.7×	159 0.5×	152	3.5k
Hannaneh Hajishirzi United States	31	3.5k 0.9×	1.1k 1.6×	139 0.3×	556 1.5×	190 0.6×	114	4.1k

Countries citing papers authored by Guillaume Lample

Since Specialization

Citations

This map shows the geographic impact of Guillaume Lample'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 Guillaume Lample with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guillaume Lample more than expected).

Fields of papers citing papers by Guillaume Lample

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Guillaume Lample. 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 Guillaume Lample. The network helps show where Guillaume Lample may publish in the future.

Co-authorship network of co-authors of Guillaume Lample

This figure shows the co-authorship network connecting the top 25 collaborators of Guillaume Lample. A scholar is included among the top collaborators of Guillaume Lample based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Guillaume Lample. Guillaume Lample is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

13 of 13 papers shown

1.

Lachaux, Marie-Anne, et al.. (2021). DOBF: A Deobfuscation Pre-Training Objective for Programming Languages. Neural Information Processing Systems. 34. 9 indexed citations

2.

Hayat, Amaury, et al.. (2020). Learning advanced mathematical computations from examples. arXiv (Cornell University). 4 indexed citations

3.

Conneau, Alexis & Guillaume Lample. (2019). Cross-lingual Language Model Pretraining. Neural Information Processing Systems. 32. 7057–7067. 94 indexed citations

4.

Lample, Guillaume, Alexandre Sablayrolles, Marc’Aurelio Ranzato, Ludovic Denoyer, & Hervé Jeǵou. (2019). Large Memory Layers with Product Keys. HAL (Le Centre pour la Communication Scientifique Directe). 32. 8548–8559. 15 indexed citations

5.

Lample, Guillaume, Sandeep Subramanian, Eric M. Smith, et al.. (2018). Multiple-Attribute Text Rewriting.. International Conference on Learning Representations. 101 indexed citations

6.

Lample, Guillaume, Alexis Conneau, Marc’Aurelio Ranzato, Ludovic Denoyer, & Hervé Jeǵou. (2018). Word translation without parallel data. International Conference on Learning Representations. 306 indexed citations breakdown →

7.

Lample, Guillaume, Myle Ott, Alexis Conneau, Ludovic Denoyer, & Marc’Aurelio Ranzato. (2018). Phrase-Based & Neural Unsupervised Machine Translation. 5039–5049. 252 indexed citations

8.

Conneau, Alexis, Ruty Rinott, Guillaume Lample, et al.. (2018). XNLI: Evaluating Cross-lingual Sentence Representations. 2475–2485. 499 indexed citations breakdown →

9.

Chaplot, Devendra Singh & Guillaume Lample. (2017). Arnold: An Autonomous Agent to Play FPS Games. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 9 indexed citations

10.

Lample, Guillaume & Devendra Singh Chaplot. (2017). Playing FPS Games with Deep Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 279 indexed citations

11.

Lample, Guillaume & Devendra Singh Chaplot. (2016). Playing FPS Games with Deep Reinforcement Learning. arXiv (Cornell University). 31(1). 2140–2146. 54 indexed citations

12.

Lample, Guillaume, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, & Chris Dyer. (2016). Neural Architectures for Named Entity Recognition. 260–270. 2494 indexed citations breakdown →

13.

Tsvetkov, Yulia, Manaal Faruqui, Ling Wang, Guillaume Lample, & Chris Dyer. (2015). Evaluation of Word Vector Representations by Subspace Alignment. 2049–2054. 68 indexed citations

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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