Laurent Charlin

2.1k total citations · 1 hit paper
14 papers, 901 citations indexed

About

Laurent Charlin is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Laurent Charlin has authored 14 papers receiving a total of 901 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 4 papers in Control and Systems Engineering. Recurrent topics in Laurent Charlin's work include Traffic control and management (3 papers), Topic Modeling (3 papers) and Multimodal Machine Learning Applications (3 papers). Laurent Charlin is often cited by papers focused on Traffic control and management (3 papers), Topic Modeling (3 papers) and Multimodal Machine Learning Applications (3 papers). Laurent Charlin collaborates with scholars based in Canada, Italy and United States. Laurent Charlin's co-authors include Joëlle Pineau, Ryan Lowe, Iulian Vlad Serban, Chia‐Wei Liu, M. Caccia, Denis Larocque, Min Lin, Eugene Belilovsky, Tinne Tuytelaars and Rahaf Aljundi and has published in prestigious journals such as Energy and Buildings, IEEE Transactions on Intelligent Transportation Systems and IEEE Open Journal of Intelligent Transportation Systems.

In The Last Decade

Laurent Charlin

13 papers receiving 877 citations

Hit Papers

How NOT To Evaluate Your Dialogue System: An Empirical St... 2016 2026 2019 2022 2016 100 200 300 400 500
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.

  1. How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation
    2016 588 citations Chia‐Wei Liu, Ryan Lowe et al. profile →

Peers

Laurent Charlin
Heriberto Cuayáhuitl United Kingdom
Muzamil Ahmed Pakistan
Pei-Hao Su United Kingdom
Baolin Peng United States
Tsung-Hsien Wen United Kingdom
Milica Gašić United Kingdom
Yihong Dong China
James Wexler United States
Nikola Mrkšić United Kingdom
Yihao Zhang China
Heriberto Cuayáhuitl United Kingdom
Laurent Charlin
Citations per year, relative to Laurent Charlin Laurent Charlin (= 1×) peers Heriberto Cuayáhuitl

Countries citing papers authored by Laurent Charlin

Since Specialization
Citations

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

Fields of papers citing papers by Laurent Charlin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laurent Charlin

This figure shows the co-authorship network connecting the top 25 collaborators of Laurent Charlin. A scholar is included among the top collaborators of Laurent Charlin 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 Laurent Charlin. Laurent Charlin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
1.
Pineau, Pierre‐Olivier, et al.. (2025). Towards sustainable energy use: Reinforcement learning for demand response in commercial buildings. Energy and Buildings. 342. 115721–115721. 1 indexed citations
2.
Charlin, Laurent, et al.. (2025). TEARS: Text Representations for Scrutable Recommendations. 4949–4968.
3.
Larocque, Denis, et al.. (2024). Model-Based Graph Reinforcement Learning for Inductive Traffic Signal Control. IEEE Open Journal of Intelligent Transportation Systems. 5. 238–250. 7 indexed citations
4.
Shi, Tianyu, et al.. (2023). Improving the Generalizability and Robustness of Large-Scale Traffic Signal Control. IEEE Open Journal of Intelligent Transportation Systems. 5. 2–15. 9 indexed citations
5.
Larocque, Denis, et al.. (2021). IG-RL: Inductive Graph Reinforcement Learning for Massive-Scale Traffic Signal Control. IEEE Transactions on Intelligent Transportation Systems. 23(7). 7496–7507. 68 indexed citations
6.
Rodríguez, Pau, et al.. (2021). Continual Learning via Local Module Composition. arXiv (Cornell University). 34. 4 indexed citations
7.
Rodríguez, Pau, M. Caccia, Alexandre Lacoste, et al.. (2021). Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 1036–1045. 19 indexed citations
8.
Caccia, M., Pau Rodríguez, Min Lin, et al.. (2020). Online Fast Adaptation and Knowledge Accumulation (OSAKA): a New Approach to Continual Learning. Neural Information Processing Systems. 33. 16532–16545. 23 indexed citations
9.
Caccia, M., Lucas Caccia, William Fedus, et al.. (2020). Language GANs Falling Short. International Conference on Learning Representations. 34 indexed citations
10.
Aljundi, Rahaf, Eugene Belilovsky, Tinne Tuytelaars, et al.. (2019). Online Continual Learning with Maximal Interfered Retrieval. arXiv (Cornell University). 32. 11849–11860. 109 indexed citations
11.
Liu, Chia‐Wei, et al.. (2016). How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation. 2122–2132. 588 indexed citations breakdown →
12.
Tarlow, Daniel, Kevin Swersky, Laurent Charlin, Ilya Sutskever, & Rich Zemel. (2013). Stochastic k-Neighborhood Selection for Supervised and Unsupervised Learning. International Conference on Machine Learning. 199–207. 20 indexed citations
13.
Charlin, Laurent, et al.. (2012). Active Learning for Matching Problems. arXiv (Cornell University). 139–146. 2 indexed citations
14.
Toussaint, Marc, Laurent Charlin, & Pascal Poupart. (2012). Hierarchical POMDP Controller Optimization by Likelihood Maximization. arXiv (Cornell University). 562–570. 17 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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Rankless by CCL
2026