---
title: "Who cites Laurent Charlin"
description: "794 papers of the Elamur Research library cite the works of Laurent Charlin, found in their bibliographies; the most cited first."
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---
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# Who cites Laurent Charlin

894 citations of their works from 794 papers of our library (of the 140,884 whose bibliographies we read) · 54 with a page here, the most cited first · [← Laurent Charlin](https://md.research.elamur.ai/free/en/authors/laurent-charlin/)

1. [**SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems**Alex Wang, Yada Pruksachatkun, Nikita Nangia, et al.*2019 · 2,187 citations*](https://md.research.elamur.ai/free/en/papers/wang-2019-superglue-stickier-benchmark-general-purpose/)
2. [**Personalizing Dialogue Agents: I have a dog, do you have pets too?**Saizheng Zhang, Emily Dinan, Jack Urbanek, et al.*2018 · 1,839 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2018-personalizing-dialogue-agents-i-have/)
3. [**MELD: A Multimodal Multi-Party Dataset for Emotion Recognition in Conversations**Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, et al.*2018 · 1,668 citations*](https://md.research.elamur.ai/free/en/papers/poria-2018-meld-multimodal-multi-party-dataset/)
4. [**A Deep Reinforced Model for Abstractive Summarization**Romain Paulus, Caiming Xiong, Richard Socher*2017 · 1,626 citations*](https://md.research.elamur.ai/free/en/papers/paulus-2017-deep-reinforced-model-abstractive-summarization/)
5. [**Deep Reinforcement Learning for Dialogue Generation**Jiwei Li, Will Monroe, Alan Ritter, et al.*2016 · 1,479 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-deep-reinforcement-learning-dialogue-generation/)
6. [**LaMDA: Language Models for Dialog Applications**Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.*2022 · 1,314 citations*](https://md.research.elamur.ai/free/en/papers/thoppilan-2022-lamda-language-models-dialog-applications/)
7. [**DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset**Yanran Li, Hui Su, Xiaoyu Shen, et al.*2017 · 1,195 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-dailydialog-manually-labelled-multi-turn/)
8. [**Adversarial Learning for Neural Dialogue Generation**Jiwei Li, Will Monroe, Tianlin Shi, et al.*2017 · 1,044 citations*](https://md.research.elamur.ai/free/en/papers/li-2017-adversarial-learning-neural-dialogue-generation/)
9. [**Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders**Tiancheng Zhao, Ran Zhao, Maxine Eskenazi*2017 · 986 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2017-learning-discourse-level-diversity-neural/)
10. [**Challenges in Data-to-Document Generation**Sam Wiseman, Stuart M. Shieber, Alexander M. Rush*2017 · 846 citations*](https://md.research.elamur.ai/free/en/papers/wiseman-2017-challenges-data-document-generation/)
11. [**MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance**Wei Zhao, Maxime Peyrard, Fei Liu, et al.*2019 · 822 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2019-moverscore-text-generation-evaluating-contextualized/)
12. [**Scaling Neural Machine Translation**Myle Ott, Sergey Edunov, David Grangier, et al.*2018 · 813 citations*](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/)
13. [**Can Large Language Models Transform Computational Social Science?**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 776 citations*](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/)
14. [**DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation**Yizhe Zhang, Siqi Sun, Michel Galley, et al.*2019 · 684 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2019-dialogpt-large-scale-generative-pre/)
15. [**Social Bias Frames: Reasoning about Social and Power Implications of Language**Maarten Sap, Saadia Gabriel, Lianhui Qin, et al.*2020 · 680 citations*](https://md.research.elamur.ai/free/en/papers/sap-2020-social-bias-frames-reasoning-about/)
16. [**Red Teaming Language Models with Language Models**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 665 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/)
17. [**Towards a Human-like Open-Domain Chatbot**Daniel Adiwardana, Minh-Thang Luong, David R. So, et al.*2020 · 573 citations*](https://md.research.elamur.ai/free/en/papers/adiwardana-2020-towards-human-like-open-domain/)
18. [**Plug and Play Language Models: A Simple Approach to Controlled Text Generation**Sumanth Dathathri, Andrea Madotto, Janice Lan, et al.*2019 · 562 citations*](https://md.research.elamur.ai/free/en/papers/dathathri-2019-plug-play-language-models-simple/)
19. [**The Second Conversational Intelligence Challenge (ConvAI2)**Emily Dinan, Varvara Logacheva, Valentin Malykh, et al.*2019 · 525 citations*](https://md.research.elamur.ai/free/en/papers/dinan-2019-second-conversational-intelligence-challenge-convai2/)
20. [**A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues**Iulian Vlad Serban, Alessandro Sordoni, Ryan Lowe, et al.*2016 · 518 citations*](https://md.research.elamur.ai/free/en/papers/serban-2016-hierarchical-latent-variable-encoder-decoder/)
21. [**How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation**Chia-Wei Liu, Ryan Lowe, Iulian Serban, et al.*2016 · 500 citations*](https://md.research.elamur.ai/free/en/papers/liu-2016-how-not-evaluate-your-dialogue/)
22. [**Towards an Automatic Turing Test: Learning to Evaluate Dialogue Responses**Ryan Lowe, Michael Noseworthy, Iulian V. Serban, et al.*2017 · 486 citations*](https://md.research.elamur.ai/free/en/papers/lowe-2017-towards-automatic-turing-test-learning/)
23. [**Experience Grounds Language**Yonatan Bisk, Ari Holtzman, Jesse Thomason, et al.*2020 · 429 citations*](https://md.research.elamur.ai/free/en/papers/bisk-2020-experience-grounds-language/)
24. [**Deal or No Deal? End-to-End Learning of Negotiation Dialogues**Mike Lewis, Denis Yarats, Yann Dauphin, et al.*2017 · 418 citations*](https://md.research.elamur.ai/free/en/papers/lewis-2017-deal-or-no-deal-end/)
25. [**Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems**Andrea Madotto, Chien-Sheng Wu, Pascale Fung*2018 · 401 citations*](https://md.research.elamur.ai/free/en/papers/madotto-2018-mem2seq-effectively-incorporating-knowledge-bases/)
26. [**Towards Emotional Support Dialog Systems**Siyang Liu, Chujie Zheng, Orianna Demasi, et al.*2021 · 391 citations*](https://md.research.elamur.ai/free/en/papers/liu-2021-emotional-support-dialog-systems/)
27. [**Retrieval Augmentation Reduces Hallucination in Conversation**Kurt Shuster, Spencer Poff, Moya Chen, et al.*2021 · 382 citations*](https://md.research.elamur.ai/free/en/papers/shuster-2021-retrieval-augmentation-reduces-hallucination-conversation/)
28. [**What makes a good conversation? How controllable attributes affect human judgments**Abigail See, Stephen Roller, Douwe Kiela, et al.*2019 · 369 citations*](https://md.research.elamur.ai/free/en/papers/see-2019-what-makes-good-conversation-how/)
29. [**FEQA: A Question Answering Evaluation Framework for Faithfulness Assessment in Abstractive Summarization**Esin Durmus, He He, Mona Diab*2020 · 350 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2020-feqa-question-answering-evaluation-framework/)
30. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 348 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
31. [**MoEL: Mixture of Empathetic Listeners**Zhaojiang Lin, Andrea Madotto, Jamin Shin, et al.*2019 · 301 citations*](https://md.research.elamur.ai/free/en/papers/lin-2019-moel-mixture-empathetic-listeners/)
32. [**Learning to Write with Cooperative Discriminators**Ari Holtzman, Jan Buys, Maxwell Forbes, et al.*2018 · 301 citations*](https://md.research.elamur.ai/free/en/papers/holtzman-2018-learning-write-cooperative-discriminators/)
33. [**Why We Need New Evaluation Metrics for NLG**Jekaterina Novikova, Ondřej Dušek, Amanda Cercas Curry, et al.*2017 · 287 citations*](https://md.research.elamur.ai/free/en/papers/novikova-2017-why-we-need-new-evaluation/)
34. [**USR: An Unsupervised and Reference Free Evaluation Metric for Dialog Generation**Shikib Mehri, Maxine Eskenazi*2020 · 283 citations*](https://md.research.elamur.ai/free/en/papers/mehri-2020-usr-unsupervised-reference-free-evaluation/)
35. [**MIME: MIMicking Emotions for Empathetic Response Generation**Navonil Majumder, Pengfei Hong, Shanshan Peng, et al.*2020 · 277 citations*](https://md.research.elamur.ai/free/en/papers/majumder-2020-mime-mimicking-emotions-empathetic-response/)
36. [**Hallucination-Free? Assessing the Reliability of Leading AI Legal Research Tools**Varun Magesh, Faiz Surani, Matthew Dahl, et al.*2024 · 267 citations*](https://md.research.elamur.ai/free/en/papers/magesh-2024-hallucination-free-assessing-reliability-leading/)
37. [**Handling Divergent Reference Texts when Evaluating Table-to-Text Generation**Bhuwan Dhingra, Manaal Faruqui, Ankur Parikh, et al.*2019 · 266 citations*](https://md.research.elamur.ai/free/en/papers/dhingra-2019-handling-divergent-reference-texts-when/)
38. [**Retrieve and Refine: Improved Sequence Generation Models For Dialogue**Jason Weston, Emily Dinan, Alexander Miller*2018 · 254 citations*](https://md.research.elamur.ai/free/en/papers/weston-2018-retrieve-refine-improved-sequence-generation/)
39. [**Knowledge-Grounded Dialogue Generation with Pre-trained Language Models**Xueliang Zhao, Wei Wu, Can Xu, et al.*2020 · 244 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2020-knowledge-grounded-dialogue-generation-pre/)
40. [**Towards Exploiting Background Knowledge for Building Conversation Systems**Nikita Moghe, Siddhartha Arora, Suman Banerjee, et al.*2018 · 238 citations*](https://md.research.elamur.ai/free/en/papers/moghe-2018-exploiting-background-knowledge-building-conversation/)
41. [**Unsupervised Evaluation of Interactive Dialog with DialoGPT**Shikib Mehri, Maxine Eskenazi*2020 · 223 citations*](https://md.research.elamur.ai/free/en/papers/mehri-2020-unsupervised-evaluation-interactive-dialog-dialogpt/)
42. [**Answers Unite! Unsupervised Metrics for Reinforced Summarization Models**Thomas Scialom, Sylvain Lamprier, Benjamin Piwowarski, et al.*2019 · 210 citations*](https://md.research.elamur.ai/free/en/papers/scialom-2019-answers-unite-unsupervised-metrics-reinforced/)
43. [**LLM-Eval: Unified Multi-Dimensional Automatic Evaluation for Open-Domain Conversations with Large Language Models**Yen-Ting Lin, Yun-Nung Chen*2023 · 206 citations*](https://md.research.elamur.ai/free/en/papers/lin-2023-llm-eval-unified-multi-dimensional/)
44. [**PRIMERA: Pyramid-based Masked Sentence Pre-training for Multi-document Summarization**Wen Xiao, Iz Beltagy, Giuseppe Carenini, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2022-primera-pyramid-based-masked-sentence/)
45. [**A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets**Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, et al.*2023 · 198 citations*](https://md.research.elamur.ai/free/en/papers/laskar-2023-systematic-study-comprehensive-evaluation-chatgpt/)
46. [**Q²: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering**Or Honovich, Leshem Choshen, Roee Aharoni, et al.*2021 · 195 citations*](https://md.research.elamur.ai/free/en/papers/honovich-2021-q-2-evaluating-factual-consistency/)
47. [**GLUCOSE: GeneraLized and COntextualized Story Explanations**Nasrin Mostafazadeh, Aditya Kalyanpur, Lori Moon, et al.*2020 · 144 citations*](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2020-glucose-generalized-contextualized-story-explanations/)
48. [**Dialogue Act Sequence Labeling using Hierarchical encoder with CRF**Harshit Kumar, Arvind Agarwal, Riddhiman Dasgupta, et al.*2017 · 75 citations*](https://md.research.elamur.ai/free/en/papers/kumar-2017-dialogue-act-sequence-labeling-using/)
49. [**Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality**Pei Zhou, Hyundong Cho, Pegah Jandaghi, et al.*2022 · 34 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2022-reflect-not-reflex-inference-based/)
50. [**Exemplification Modeling: Can You Give Me an Example, Please?**Edoardo Barba, Luigi Procopio, Caterina Lacerra*2021 · 23 citations*](https://md.research.elamur.ai/free/en/papers/barba-2021-exemplification-modeling/)
51. [**Disentangling Indirect Answers to Yes-No Questions in Real Conversations**Krishna Sanagavarapu, Jathin Singaraju, Anusha Kakileti, et al.*2022 · 11 citations*](https://md.research.elamur.ai/free/en/papers/sanagavarapu-2022-disentangling-indirect-answers-yes-no/)
52. [**Automatic Evaluate Dialogue Appropriateness by Using Dialogue Act**Bao Chen, Yuanjie Wang, Zeming Liu, et al.*2023 · 6 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-automatic-evaluate-dialogue-appropriateness-dialogue/)
53. [**Faithful Medical Dialogue Generation Using Homo-Heterogeneous Exemplar-based In-Context Knowledge Grounding**Priyanshu Priya, Hardik Goyal, Asif Ekbal*2026*](https://md.research.elamur.ai/free/en/papers/priya-2026-faithful-medical-dialogue-generation-homo/)
54. [**Rethinking Evaluation in Retrieval-Augmented Personalized Dialogue: A Cognitive and Linguistic Perspective**Tianyi Zhang, David Traum*2026*](https://md.research.elamur.ai/free/en/papers/zhang-2026-rethinking-evaluation-retrieval-augmented-personalized/)

740 more citing papers of our library have no page here yet.

- [← back to](https://md.research.elamur.ai/free/en/authors/laurent-charlin/) — Laurent Charlin