Maxime Peyrard

1.3k total citations · 1 hit paper
27 papers, 597 citations indexed

About

Maxime Peyrard is a scholar working on Artificial Intelligence, Communication and Computer Vision and Pattern Recognition. According to data from OpenAlex, Maxime Peyrard has authored 27 papers receiving a total of 597 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Artificial Intelligence, 2 papers in Communication and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Maxime Peyrard's work include Topic Modeling (22 papers), Natural Language Processing Techniques (21 papers) and Advanced Text Analysis Techniques (10 papers). Maxime Peyrard is often cited by papers focused on Topic Modeling (22 papers), Natural Language Processing Techniques (21 papers) and Advanced Text Analysis Techniques (10 papers). Maxime Peyrard collaborates with scholars based in Germany, Switzerland and France. Maxime Peyrard's co-authors include Yang Gao, Steffen Eger, Wei Zhao, Christian M. Meyer, Fei Liu, Judith Eckle‐Kohler, Iryna Gurevych, Robert West, Martin Josifoski and Nicola De Cao and has published in prestigious journals such as Language Resources and Evaluation, Infoscience (Ecole Polytechnique Fédérale de Lausanne) and arXiv (Cornell University).

In The Last Decade

Maxime Peyrard

25 papers receiving 563 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.

MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance

2019 274 citations Wei Zhao, Maxime Peyrard et al. TUbilio (Technical University of Darmstadt) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Maxime Peyrard Germany	12	557	88	57	32	18	27	597
Vishrav Chaudhary United States	13	569 1.0×	163 1.9×	45 0.8×	20 0.6×	12 0.7×	29	603
Yitong Li China	9	267 0.5×	56 0.6×	51 0.9×	15 0.5×	16 0.9×	42	330
Yinhan Liu United States	4	530 1.0×	166 1.9×	34 0.6×	24 0.8×	8 0.4×	4	597
Leyang Cui China	11	588 1.1×	110 1.3×	57 1.0×	30 0.9×	29 1.6×	37	658
Stephan Gouws South Africa	8	449 0.8×	70 0.8×	44 0.8×	12 0.4×	6 0.3×	9	484
Timo Schick Germany	9	412 0.7×	95 1.1×	50 0.9×	9 0.3×	15 0.8×	13	466
Panupong Pasupat United States	16	545 1.0×	144 1.6×	79 1.4×	26 0.8×	25 1.4×	21	602
Ruidan He Singapore	13	814 1.5×	78 0.9×	91 1.6×	23 0.7×	34 1.9×	14	874
Arian Pasquali Portugal	2	296 0.5×	32 0.4×	90 1.6×	29 0.9×	21 1.2×	3	347
Ulrich Germann United Kingdom	15	659 1.2×	126 1.4×	51 0.9×	30 0.9×	8 0.4×	39	696

Countries citing papers authored by Maxime Peyrard

Since Specialization

Citations

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

Fields of papers citing papers by Maxime Peyrard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Maxime Peyrard

This figure shows the co-authorship network connecting the top 25 collaborators of Maxime Peyrard. A scholar is included among the top collaborators of Maxime Peyrard 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 Maxime Peyrard. Maxime Peyrard 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:

20 of 20 papers shown

Peyrard, Maxime, et al.. (2024). REFINER: Reasoning Feedback on Intermediate Representations. 1100–1126. 1 indexed citations

Peyrard, Maxime, Martin Josifoski, Vishrav Chaudhary, et al.. (2024). A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia. SPIRE - Sciences Po Institutional REpository. 6828–6844.

Josifoski, Martin, et al.. (2023). Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and the Case of Information Extraction. 1555–1574. 19 indexed citations

Colombo, Pierre, et al.. (2023). The Glass Ceiling of Automatic Evaluation in Natural Language Generation. SPIRE - Sciences Po Institutional REpository. 178–183. 5 indexed citations

Josifoski, Martin, et al.. (2023). Grammar-Constrained Decoding for Structured NLP Tasks without Finetuning. SPIRE - Sciences Po Institutional REpository. 10932–10952. 8 indexed citations

Josifoski, Martin, Maxime Peyrard, Barun Patra, et al.. (2023). Language Model Decoding as Likelihood–Utility Alignment. 1455–1470. 1 indexed citations

Josifoski, Martin, Nicola De Cao, Maxime Peyrard, Fabio Petroni, & Robert West. (2022). GenIE: Generative Information Extraction. Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 4626–4643. 25 indexed citations

Peyrard, Maxime, Martin Josifoski, Barun Patra, et al.. (2022). Invariant Language Modeling. 5728–5743. 3 indexed citations

Gligorić, Kristina, et al.. (2022). On the Context-Free Ambiguity of Emoji. Proceedings of the International AAAI Conference on Web and Social Media. 16. 1388–1392. 11 indexed citations

10.

Ribeiro, Manoel Horta, Kristina Gligorić, Maxime Peyrard, et al.. (2021). Sudden Attention Shifts on Wikipedia During the COVID-19 Crisis. Proceedings of the International AAAI Conference on Web and Social Media. 15. 208–219. 5 indexed citations

11.

Peyrard, Maxime & Robert West. (2021). A Ladder of Causal Distances. 2012–2018. 2 indexed citations

12.

Zhao, Wei, Goran Glavaš, Maxime Peyrard, et al.. (2020). On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation. MADOC (University of Mannheim). 1656–1671. 32 indexed citations

13.

Peyrard, Maxime. (2019). Studying Summarization Evaluation Metrics in the Appropriate Scoring Range. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 5093–5100. 32 indexed citations

14.

Zhao, Wei, Maxime Peyrard, Fei Liu, et al.. (2019). MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance. TUbilio (Technical University of Darmstadt). 563–578. 274 indexed citations breakdown →

15.

Peyrard, Maxime, et al.. (2018). Live Blog Corpus for Summarization. arXiv (Cornell University). 3 indexed citations

16.

Rücklé, Andreas, Judith Eckle‐Kohler, Eugenio Martínez‐Cámara, et al.. (2017). LSDSem 2017: Exploring Data Generation Methods for the Story Cloze Test. 56–61. 6 indexed citations

17.

Peyrard, Maxime & Judith Eckle‐Kohler. (2017). A Principled Framework for Evaluating Summarizers: Comparing Models of Summary Quality against Human Judgments. 26–31. 4 indexed citations

18.

Peyrard, Maxime, et al.. (2016). The Next Step for Multi-Document Summarization: A Heterogeneous Multi-Genre Corpus Built with a Novel Construction Approach. International Conference on Computational Linguistics. 1535–1545. 11 indexed citations

19.

Peyrard, Maxime & Judith Eckle‐Kohler. (2016). A General Optimization Framework for Multi-Document Summarization Using Genetic Algorithms and Swarm Intelligence. TUbilio (Technical University of Darmstadt). 247–257. 20 indexed citations

20.

Peyrard, Maxime & Judith Eckle‐Kohler. (2016). Optimizing an Approximation of ROUGE - a Problem-Reduction Approach to Extractive Multi-Document Summarization. TUbilio (Technical University of Darmstadt). 1825–1836. 13 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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