---
title: "Université de Montréal — works"
description: "42 works by researchers of Université de Montréal in our library, the most cited first."
canonical: "https://research.elamur.ai/free/en/universities/universite-de-montreal/works/"
---
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# Works of Université de Montréal

42 works · the most cited first · [← Université de Montréal](https://md.research.elamur.ai/free/en/universities/universite-de-montreal/)

1. [**Neural Machine Translation by Jointly Learning to Align and Translate**Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio*2014 · 18,908 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2014-neural-machine-translation-jointly-learning/)
2. [**Graph Attention Networks**Petar Veličkovic, Guillem Cucurull, Arantxa Casanova, et al.*2017 · 8,996 citations*](https://md.research.elamur.ai/free/en/papers/veli-vckovic-2017-graph-attention-networks/)
3. [**On the Properties of Neural Machine Translation: Encoder-Decoder Approaches**Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, et al.*2014 · 7,734 citations*](https://md.research.elamur.ai/free/en/papers/cho-2014-properties-neural-machine-translation-encoder/)
4. [**Show, Attend and Tell: Neural Image Caption Generation with Visual Attention**Kelvin Xu, Jimmy Ba, Ryan Kiros, et al.*2015 · 7,483 citations*](https://md.research.elamur.ai/free/en/papers/xu-2015-show-attend-tell-neural-image/)
5. [**Intriguing properties of neural networks**Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, et al.*2013 · 5,870 citations*](https://md.research.elamur.ai/free/en/papers/szegedy-2013-intriguing-properties-neural-networks/)
6. [**HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering**Zhilin Yang, Peng Qi, Saizheng Zhang, et al.*2018 · 3,489 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-hotpotqa-dataset-diverse-explainable-multi/)
7. [**A Survey of Large Language Models**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,847 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/)
8. [**Word Representations: A Simple and General Method for Semi-Supervised Learning**Joseph Turian, Lev-Arie Ratinov, Yoshua Bengio*2010 · 2,421 citations*](https://md.research.elamur.ai/free/en/papers/turian-2010-word-representations-simple-general-method/)
9. [**Attention-Based Models for Speech Recognition**Jan Chorowski, Dzmitry Bahdanau, Dmitriy Serdyuk, et al.*2015 · 1,776 citations*](https://md.research.elamur.ai/free/en/papers/chorowski-2015-attention-based-models-speech-recognition/)
10. [**A Structured Self-attentive Sentence Embedding**Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, et al.*2017 · 1,773 citations*](https://md.research.elamur.ai/free/en/papers/lin-2017-structured-self-attentive-sentence-embedding/)
11. [**On Using Very Large Target Vocabulary for Neural Machine Translation**Sébastien Jean, Kyunghyun Cho, Roland Memisevic, et al.*2015 · 999 citations*](https://md.research.elamur.ai/free/en/papers/jean-2015-very-large-target-vocabulary-neural/)
12. [**C-Pack: Packed Resources For General Chinese Embeddings**Shitao Xiao, Zheng Liu, Peitian Zhang, et al.*2023 · 920 citations*](https://md.research.elamur.ai/free/en/papers/xiao-2023-c-pack-packed-resources/)
13. [**Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism**Orhan Firat, Kyunghyun Cho, Yoshua Bengio*2016 · 821 citations*](https://md.research.elamur.ai/free/en/papers/firat-2016-multi-way-multilingual-neural-machine/)
14. [**HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models**Junyi Li, Xiaoxue Cheng, Wayne Xin Zhao, et al.*2023 · 646 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-halueval-large-scale-hallucination-evaluation/)
15. [**Pointing the Unknown Words**Caglar Gulcehre, Sungjin Ahn, Ramesh Nallapati, et al.*2016 · 642 citations*](https://md.research.elamur.ai/free/en/papers/gulcehre-2016-pointing-unknown-words/)
16. [**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/)
17. [**Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models**Iulian V. Serban, Alessandro Sordoni, Yoshua Bengio, et al.*2015 · 524 citations*](https://md.research.elamur.ai/free/en/papers/serban-2015-building-end-end-dialogue-systems/)
18. [**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/)
19. [**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/)
20. [**The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems**Ryan Lowe, Nissan Pow, Iulian Serban, et al.*2015 · 474 citations*](https://md.research.elamur.ai/free/en/papers/lowe-2015-ubuntu-dialogue-corpus-large-dataset/)
21. [**A Character-level Decoder without Explicit Segmentation for Neural Machine Translation**Junyoung Chung, Kyunghyun Cho, Yoshua Bengio*2016 · 407 citations*](https://md.research.elamur.ai/free/en/papers/chung-2016-character-level-decoder-without-explicit/)
22. [**Long Range Arena: A Benchmark for Efficient Transformers**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2020 · 396 citations*](https://md.research.elamur.ai/free/en/papers/tay-2020-long-range-arena-benchmark-efficient/)
23. [**FiLM: Visual Reasoning with a General Conditioning Layer**Ethan Perez, Florian Strub, Harm de Vries, et al.*2017 · 348 citations*](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/)
24. [**An Actor-Critic Algorithm for Sequence Prediction**Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, et al.*2016 · 320 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2016-actor-critic-algorithm-sequence-prediction/)
25. [**Representation Learning: A Review and New Perspectives**Yoshua Bengio, Aaron Courville, Pascal Vincent*2012 · 316 citations*](https://md.research.elamur.ai/free/en/papers/bengio-2012-representation-learning-review-new-perspectives/)
26. [**A Neural Network Approach to Context-Sensitive Generation of Conversational Responses**Alessandro Sordoni, Michel Galley, Michael Auli, et al.*2015 · 307 citations*](https://md.research.elamur.ai/free/en/papers/sordoni-2015-neural-network-approach-context-sensitive/)
27. [**On Extractive and Abstractive Neural Document Summarization with Transformer Language Models**Jonathan Pilault, Raymond Li, Sandeep Subramanian, et al.*2020 · 259 citations*](https://md.research.elamur.ai/free/en/papers/pilault-2020-extractive-abstractive-neural-document-summarization/)
28. [**Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset**Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, et al.*2019 · 244 citations*](https://md.research.elamur.ai/free/en/papers/byrne-2019-taskmaster-1-realistic-diverse-dialog/)
29. [**Humanity's Last Exam**Long Phan, Alice Gatti, Ziwen Han, et al.*2025 · 235 citations*](https://md.research.elamur.ai/free/en/papers/phan-2025-humanity-s-last-exam/)
30. [**Learning to Understand Phrases by Embedding the Dictionary**Felix Hill, Kyunghyun Cho, Anna Korhonen, et al.*2016 · 234 citations*](https://md.research.elamur.ai/free/en/papers/hill-2016-learning-understand-phrases-embedding-dictionary/)
31. [**The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models**Junyi Li, Jie Chen, Ruiyang Ren, et al.*2024 · 150 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-dawn-after-dark-empirical-study/)
32. [**Transformer-Patcher: One Mistake worth One Neuron**Zeyu Huang, Yikang Shen, Xiaofeng Zhang, et al.*2023 · 120 citations*](https://md.research.elamur.ai/free/en/papers/huang-2023-transformer-patcher-one-mistake-worth/)
33. [**WikiCoref: An English Coreference-annotated Corpus of Wikipedia Articles**Abbas Ghaddar, Phillippe Langlais*2016 · 116 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2016-wikicoref-english-coreference-annotated-corpus/)
34. [**V-STaR: Training Verifiers for Self-Taught Reasoners**Arian Hosseini, Xingdi Yuan, Nikolay Malkin, et al.*2024 · 111 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2024-v-star-training-verifiers-self/)
35. [**Olmo 3**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
36. [**JABER and SABER: Junior and Senior Arabic BERt**Abbas Ghaddar, Yimeng Wu, Ahmad Rashid, et al.*2021 · 16 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2021-jaber-saber-junior-senior-arabic/)
37. [**Revisiting Pre-trained Language Models and their Evaluation for Arabic Natural Language Understanding**Abbas Ghaddar, Yimeng Wu, Sunyam Bagga, et al.*2022 · 9 citations*](https://md.research.elamur.ai/free/en/papers/ghaddar-2022-revisiting-pre-trained-language-models-their/)
38. [**GenDR: A Generic Deep Realizer with Complex Lexicalization**François Lareau, Florie Lambrey, Ieva Dubinskaite, et al.*2018 · 9 citations*](https://md.research.elamur.ai/free/en/papers/lareau-2018-gendr-generic-deep-realizer-complex/)
39. [**pyrealb at the GEM'24 Data-to-text Task: Symbolic English Text Generation from RDF Triples**Guy Lapalme*2024 · 1 citation*](https://md.research.elamur.ai/free/en/papers/lapalme-2024-pyrealb-gem-24-data-text/)
40. [**Complexity factors of language models in reading comprehension: a controlled experiment (Étude des facteurs de complexité des modèles de langage dans une tâche de compréhension de lecture à l'aide d'une expérience contrôlée sémantiquement)**Elie Antoine, Frederic Bechet, Géraldine Damnati, et al.*2024*](https://md.research.elamur.ai/free/en/papers/antoine-2024-etude-des-facteurs-de-complexite/)
41. [**On the importance of Data Scale in Pretraining Arabic Language Models**Abbas Ghaddar, Philippe Langlais, Mehdi Rezagholizadeh, et al.*2024*](https://md.research.elamur.ai/free/en/papers/ghaddar-2024-importance-data-scale-pretraining-arabic/)
42. [**Generic Oracles for Structured Prediction**Christoph Teichmann, Antoine Venant*2021*](https://md.research.elamur.ai/free/en/papers/teichmann-2021-generic-oracles-structured-prediction/)
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