Dzmitry Bahdanau

53.6k total citations
17 papers, 199 citations indexed

About

Dzmitry Bahdanau is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Dzmitry Bahdanau has authored 17 papers receiving a total of 199 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 1 paper in Control and Systems Engineering. Recurrent topics in Dzmitry Bahdanau's work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (6 papers). Dzmitry Bahdanau is often cited by papers focused on Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Multimodal Machine Learning Applications (6 papers). Dzmitry Bahdanau collaborates with scholars based in Canada, Israel and United States. Dzmitry Bahdanau's co-authors include Siva Reddy, Richard E. Turner, Yoshua Bengio, Chitwan Saharia, José Miguel Hernández-Lobato, Maxime Chevalier-Boisvert, Douglas Eck, Thien Huu Nguyen, Shixiang Gu and Natasha Jaques and has published in prestigious journals such as Apollo (University of Cambridge), arXiv (Cornell University) and Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

In The Last Decade

Dzmitry Bahdanau

16 papers receiving 185 citations

Peers

Countries citing papers authored by Dzmitry Bahdanau

Since Specialization

Citations

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

Fields of papers citing papers by Dzmitry Bahdanau

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dzmitry Bahdanau

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

All Works

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17 of 17 papers shown

#	Work	Indexed citations
1	Evaluating In-Context Learning of Libraries for Code Generation 2024 ·(unknown), Siva Reddy, Dzmitry Bahdanau, Pradeep Dasigi	3
2	In-Context Learning for Text Classification with Many Labels 2023 ·(unknown), Siva Reddy, Dzmitry Bahdanau	8
3	PromptMix: A Class Boundary Augmentation Method for Large Language Model Distillation 2023 ·(unknown), Olga Vechtomova, Dzmitry Bahdanau, Issam Laradji	3
4	MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretations 2023 ·(unknown), (unknown), Siva Reddy, Dzmitry Bahdanau	2
5	On the Compositional Generalization Gap of In-Context Learning 2022 ·(unknown), (unknown), Dzmitry Bahdanau, Alessandro Sordoni, Aaron Courville	6
6	Compositional Generalization in Dependency Parsing 2022 ·Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ·Emily J. Goodwin, Siva Reddy, Timothy J. O’Donnell, Dzmitry Bahdanau	3
7	Data Augmentation for Intent Classification with Off-the-shelf Large Language Models 2022 ·(unknown), Pau Rodríguez, Issam Laradji, Parmida Atighehchian, David Vázquez, Dzmitry Bahdanau	32
8	LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic Parsing 2022 ·Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) ·(unknown), Dzmitry Bahdanau	2
9	Understanding by Understanding Not: Modeling Negation in Language Models 2021 ·(unknown), Siva Reddy, Dzmitry Bahdanau, R Devon Hjelm, Alessandro Sordoni, Aaron Courville	30
10	Learning to Follow Language Instructions with Adversarial Reward Induction 2018 ·arXiv (Cornell University) ·Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, Edward Grefenstette	4
11	BabyAI: First Steps Towards Grounded Language Learning With a Human In the Loop. 2018 ·arXiv (Cornell University) ·Maxime Chevalier-Boisvert, Dzmitry Bahdanau, (unknown), (unknown), Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio	25
12	Jointly Learning "What" and "How" from Instructions and Goal-States. 2018 ·International Conference on Learning Representations ·Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, Pushmeet Kohli, Edward Grefenstette	2
13	Learning to Understand Goal Specifications by Modelling Reward 2018 ·arXiv (Cornell University) ·Dzmitry Bahdanau, Felix Hill, Jan Leike, Edward Hughes, (unknown), Pushmeet Kohli, Edward Grefenstette	16
14	BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning 2018 ·arXiv (Cornell University) ·Maxime Chevalier-Boisvert, Dzmitry Bahdanau, (unknown), (unknown), Chitwan Saharia, Thien Huu Nguyen, Yoshua Bengio	22
15	Sequence Tutor: Conservative Fine-Tuning of Sequence Generation Models with KL-control 2017 ·Apollo (University of Cambridge) ·Natasha Jaques, Shixiang Gu, Dzmitry Bahdanau, José Miguel Hernández-Lobato, Richard E. Turner, Douglas Eck	39
16	An Actor-Critic Algorithm for Structured Prediction 2016 ·arXiv (Cornell University) ·Dzmitry Bahdanau, Philémon Brakel, Kelvin Xu, Anirudh Goyal, Ryan Lowe, Joëlle Pineau, (unknown), Yoshua Bengio	1
17	Task Loss Estimation for Structured Prediction 2016 ·Dzmitry Bahdanau, (unknown), Philémon Brakel, Nan Rosemary Ke, Jan Chorowski, Aaron Courville, Yoshua Bengio	1

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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