2023

C.Y. Su, S. Zhou, E. Gonzalez-Kozlova, G. Butler-Laporte (鈥�.) J. Pineau, V. Mooser, T. Marron, N.D. Beckmann, S. Kim-Schulze, A.W. Charney, S. Gnjatic, D.E. Kaufmann, M. Merard, J.B. Richards. 鈥淐irculating proteins to predict COVID-19 severity鈥�. Scientific Reports 13 (1), 6236. 2023.

H. Satija, A. Lazaric, M. Pirotta, J. Pineau. 鈥淕roup Fairness in Reinforcement Learning鈥�. Transactions on Machine Learning Research. pp.1-60. 2023.

D.S. Sachan, M. Lewis, D. Yogatama, L. Zettlemoyer, J. Pineau, M. Zaheer. 鈥淨uestions Are All You Need to Train a Dense Passage Retriever鈥�. Transactions of the Association for Computational Linguistics 11, 600-616. 2023.

M.A. Legault, J. Hartford, M. Lu, A.Y. Yang, J. Pineau. 鈥淓valuating machine learning instrumental variable methods to estimate conditional treatment effects in Mendelian randomization鈥�. International Genetic Epidemiology Society. 2023.

P. Henderson, J. Hu, M. Diab, J. Pineau. 鈥淩ethinking Machine Learning Benchmarks in the Context of Professional Codes of Conduct鈥�. Third ACM Symposium on Computer Science and Law (CSLAW 2024).

M. Wabartha, J. Pineau. 鈥淧iecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning鈥�. NeurIPS workshop on XAI in Action: Past, Present, and Future Applications. 2023.

2022

Madhulika Srikumar et al. 鈥淎dvancing ethics review practices in AI research鈥�. In: Nature Machine Intelligence 4.12 (2022), pp. 1061鈥� 1064.

Devendra Singh Sachan et al. 鈥淨uestions are all you need to train a dense passage retriever鈥�. In: Transactions of the Association for Computational Linguistics 11 (2023), pp. 600鈥�616.

Devendra Sachan et al. 鈥淚mproving Passage Retrieval with Zero-Shot Question Generation鈥�. In: Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing. 2022, pp. 3781鈥�3797.

Bogdan Mazoure et al. 鈥淟ow-Rank Representation of Reinforcement Learning Policies鈥�. In: Journal of Artificial Intelligence Research 75 (2022), pp. 597鈥�636.

GX-Chen Anthony et al. 鈥淎 Generalized Bootstrap Target for Value-Learning, Efficiently Combining Value and Feature Predictions鈥�. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 36. 6. 2022, pp. 6829鈥�6837.

Ekaterina Kochmar et al. 鈥淎utomated datadriven generation of personalized pedagogical interventions in intelligent tutoring systems鈥�. In: International Journal of Artificial Intelligence in Education 32.2 (2022), pp. 323鈥�349.

Lucas Caccia et al. 鈥淣ew Insights on Reducing Abrupt Representation Change in Online Continual Learning鈥�. In: International Conference on Learning Representations. 2021.

Martin Cousineau et al. 鈥淓stimating causal effects with optimization-based methods: A review and empirical comparison鈥�. In: European Journal of Operational Research 304.2 (2023), pp. 367鈥�380.

2021

J. Pineau, P. Vincent-Lamarre, K. Sinha, V. Larivi猫re, A. Beygelzimer, F. D鈥橝lche-Buc, E. Fox, and H. Larochelle. 鈥淚mproving reproducibility in machine learning research: a report from the NeurIPS 2019 reproducibility program,鈥� Journal of Machine Learning Research 22. 2021.p.1-20

E. Kochmar, D.D. Vu, R. Belfer, V. Gupta, I.V. Serban, and J. Pineau. 鈥淎utomated Data-Driven Generation of Personalized Pedagogical Interventions in Intelligent Tutoring Systems,鈥� International Journal of Artificial Intelligence in Education, 2021, 1-27

H. Satija, P.S. Thomas, J. Pineau, and R. Laroche. 鈥淢ulti-Objective SPIBB: Seldonian Offline Policy Improvement with Safety Constraints in Finite MDPs,鈥� Advances in Neural Information Processing Systems (NeurIPS) 2021

J. Lee, W. Jeon, B. Lee, J. Pineau, and K.E. Kim. 鈥淥ptidice: Offline policy optimization via stationary distribution correction estimation,鈥� International Conference on Machine Learning (ICML), 2021, 6120-6130

S. Sodhani, A. Zhang, and J. Pineau. 鈥淢ultitask reinforcement learning with context-based representations,鈥� International Conference on Machine Learning (ICML), 2021, 9767-9779

K. Sinha, P. Parthasarathi, J. Pineau, and A. Williams. 鈥淯nnatural language inference,鈥� Annual Meeting of the Association for Computational Linguistics (ACL). 2021. Outstanding Paper Award.

P. Parthasarathi, J. Pineau, and S. Chandar. 鈥淒o Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task?,鈥� Special Interest Group on Discourse and Dialogue (SigDial). 2021.

P. Parthasarathi, M. Abdelsalam, J. Pineau, and S. Chandar. 鈥淎 Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss,鈥� Special Interest Group on Discourse and Dialogue (SigDial). 2021

J. Romoff, P. Henderson, D. Kanaa, E. Bengio, A. Touati, P.L. Bacon, and J. Pineau. 鈥淭Dprop: Does Adaptive Optimization With Jacobi Preconditioning Help Temporal Difference Learning?,鈥� International Conference on Autonomous Agents and MultiAgent Systems (AAMAS). 2021

P. Parthasarathi, K. Sinha, J. Pineau, and A. Williams. 鈥淪ometimes we want ungrammatical translations,鈥� Conference on Empirical Methods in Natural Language Processing (EMNLP). 2021

K. Sinha, R. Jia, D. Hupkes, J. Pineau, A. Williams, and D. Kiela. 鈥淥rder word matters pre-training for little,鈥� Conference on Empirical Methods in Natural Language Processing (EMNLP). 2021

D. Jambor, K. Teru, J. Pineau, and W.L. Hamilton. 鈥淓xploring the Limits of Few-Shot Link Prediction in Knowledge Graphs,鈥� European Chapter of the Association for Computational Linguistics (EACL). 2021.

S. Delacroix, J. Pineau, and J. Montgomery. 鈥淒emocratising the digital revolution: the role of data governance,鈥� Book chapter in Reflections on AI for Humanity, Braunschweig & Ghallab (eds.), Springer, 2021. 40-52. Accepted, to appear in 2022

M. Cousineau, V. Verter, S.A. Murphy, and J. Pineau. 鈥淓stimating Causal Effects with Optimization-Based Methods: A Review and Empirical Comparison,鈥� European Journal of Operational Research 2022.

L. Caccia, R. Aljundi, N. Asadi, T. Tuytelaars, J. Pineau, and E. Belilovsky. 鈥淣ew Insights on Reducing Abrupt Representation Change in Online Continual Learning,鈥� International Conference on Learning Representations 2022

A. GX-Chen, V. Chelu, B.A. Richards, and J. Pineau. 鈥淎 Generalized Bootstrap Target for Value- Learning, Efficiently Combining Value and Feature Predictions,鈥� American Associate for Artificial Page 44 CIM 2021 Annual Report CIM 2021 Annual Report Page 45 Intelligence (AAAI) 2021.

L. Caccia, R. Aljundi, N. Asadi, T. Tuytelaars, J. Pineau, and E. Belilovsky. 鈥淩educing representation drift in online continual learning,鈥� arXiv preprint arXiv:2104.05025

K. Bullard, D. Kiela, F. Meier, J. Pineau, and J. Foerster. 鈥淨uasi-equivalence discovery for zeroshot emergent communication,鈥� arXiv preprint arXiv:2103.08067

C. Lyle, A. Zhang, M. Jiang, J. Pineau, and Y. Gal. 鈥淩esolving Causal Confusion in Reinforcement Learning via Robust Exploration,鈥� Self-Supervision for Reinforcement Learning Workshop-ICLR 2021

M. Tomar, A. Zhang, R. Calandra, M.E. Taylor, and J. Pineau. 鈥淢odel-invariant state abstractions for model-based reinforcement learning,鈥� arXiv preprint arXiv:2102.09850

B. Li, V. Fran莽ois-Lavet, T. Doan, and J. Pineau. 鈥淒omain adversarial reinforcement learning,鈥� arXiv preprint arXiv:2102.07097

A. Sriram, M. Muckley, K. Sinha, F. Shamout, J. Pineau, K.J. Geras, L. Azour, Y. Aphinyanaphongs, N. Yakubova, and W. Moore. 鈥淐ovid-19 prognosis via self-supervised representation learning and multiimage prediction,鈥� arXiv preprint arXiv:2101.04909

C.Y. Su, S. Zhou, E. Gonzalez-Kozlova, G. Butler- Laporte, (...) J. Pineau (...) and B. Richards. 鈥淐irculating proteins to predict adverse COVID-19 outcomes,鈥� medRxiv. . org/10.1101/2021.10.04.21264015

2020

Benjamin Haibe-Kains, George Alexandru Adam, Ahmed Hosny, Farnoosh Khodakarami, MAQC Board, Levi Waldron, Bo Wang, Chris McIntosh, Anshul Kundaje, Casey S Greene, Michael M Hoffman, Jeffrey T Leek, Wolfgang Huber, Alvis Brazma, Joelle Pineau, Robert Tibshirani, Trevor Hastie, John Ioannidis, John Quackenbush, Hugo JWL Aerts. The importance of transparency and reproducibility in artificial intelligence research. Nature. 2020.

Nathan Peifer-Smadja, Redwan Maatoug, Fran莽ois-Xavier Lescure, Eric D鈥橭rtenzio, Joelle Pineau and Jean-R茅mi King. Machine Learning for COVID-19 needs global collaboration and data-sharing. Nature Machine Intelligence. 2020.

Vincenzo Forgetta, Julyan Keller-Baruch, Marie Forest, Audrey Durand, Sahir Bhatnagar, John P Kemp, Maria Nethander, Daniel Evans, John A Morris, Douglas P Kiel, Fernando Rivadeneira, Helena Johansson, Nicholas C Harvey, Dan Mellstr枚m, Magnus Karlsson, Cyrus Cooper, David M Evans, Robert Clarke, John A Kanis, Eric Orwoll, Eugene V McCloskey, Claes Ohlsson, Joelle Pineau, William D Leslie, Celia MT Greenwood, J Brent Richards. Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study. PLoS medicine 17 (7). 2020.

Ximeng Mao, Joelle Pineau, Roy Keyes, Shirin A Enger. RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy via Deep Learning. International Journal of Radiation Oncology Biology Physics. 2020

Peter Henderson, Jieru Hu, Joshua Romoff, Emma Brunskill, Dan Jurafsky, Joelle Pineau. Towards the Systematic Reporting of the Energy and Carbon Footprints of Machine Learning. JMLR. 21(248), pp.1鈭�43.

Koustuv Sinha, Joelle Pineau, Jessica Forde, Rosemary Nan Ke, Hugo Laorchelle. Neurips 2019 Reproducibility Challenge. A special issue of the journal ReScience C 6(2). 2020.

Clare Lyle, Amy Zhang, Angelos Filos, Shagun Sodhani, Marta Kwiatkowska, Yarin Gal, Doina Precup, Joelle Pineau. Invariant Causal Prediction for Block MDPs. ICML 2020.

Harsh Satija, Philip Amortila, Joelle Pineau. Constrained Markov Decision Processes via Backward Value Functions. ICML 2020.

Lucas Caccia, Eugene Belilovsky, Massimo Caccia, Joelle Pineau. Online Learned Continual Compression with Adaptive Quantization Module. ICML 2020.

Emmanuel Bengio, Joelle Pineau, Doina Precup. Interference and Generalization in Temporal Difference Learning. Submitted and accepted to ICML 2020.

Maxime Wabartha, Audrey Durand, Vincent Fran莽ois-Lavet, Joelle Pineau. Handling Black Swan Events in Deep Learning with Diversely Extrapolated Neural Networks. IJCAI 2020.

Ahmed Touati, Amy Zhang, Joelle Pineau, Pascal Vincent. Stable Policy Optimization via Off-Policy Divergence Regularization. UAI 2020.

Koustuv Sinha, Prasanna Parthasarathi, Jasmine Wang, Ryan Lowe, William L Hamilton, Joelle Pineau. Learning an Unreferenced Metric for Online Dialogue Evaluation. ACL 2020.

Ge Yang, Amy Zhang, Ari Morcos, Joelle Pineau, Pieter Abbeel, Roberto Calandra. Plan2Vec: Unsupervised Representation Learning by Latent Plans. Learning for Dynamics and Control (L4DC) 2020.

Iulian Vlad Serban, Varun Gupta, Ekaterina Kochmar, Dung D Vu, Robert Belfer, Joelle Pineau, Aaron Courville, Laurent Charlin, Yoshua Bengio. A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM. AIED 2020.

Ekaterina Kochmar, Dung D Vu, Robert Belfer, Varun Gupta, Iulian V Serban, Joelle Pineau. Automated Personalized Feedback Improves Learning Gains in an Intelligent Tutoring System. AIED 2020.

R.Y. (David) Tao, Vincent Francois-Lavet, Joelle Pineau. Novelty Search in Representational Space for Sample Efficient Exploration. NeurIPS 2020. Oral presentation (1% of submissions).

Paul Barde, Julien Roy, Wonseok Jeon, Joelle Pineau, Chris Pal, Derek Nowrouzezahrai. Adversarial Soft Advantage Fitting: Imitation Learning without Policy Optimization. NeurIPS 2020. Spotlight presentation (4% of submissions).

2019

I.V. Serban, C. Sankar, M. Pieped, J. Pineau, Y. Bengio. 鈥淭he Bottleneck Simulator: A Model-based Deep Reinforcement Learning Approach鈥�. Journal of Machine Learning Research (JMLR). Accepted.

V. Fran莽ois-Lavet, G. Rabusseau, J. Pineau, D. Ernst, R. Fontaineau. 鈥淥n Overfitting and Asymptotic Bias in Batch Reinforcement Learning with Partial Observability鈥�. Journal of AI Research (JAIR). Vol.65. pp.1-30. 2019.

A.M.Froomkin, I. Kerr, J. Pineau. 鈥淲hen AIs outperform doctors: Confronting the challenges of a tort-induced over-reliance on machine learning鈥�. Arizona Law Review, vol.61:33. 2019.

P. Paquette, Y. Lu, S. Bocco, M.O. Smith, S. Ortiz-Gagne, J. K. Kummerfeld, S. Singh, J. Pineau, A. Courville. 鈥淣o Press Diplomacy: Modeling Multi-Agent Gameplay鈥�. NeurIPS 2019.

M. Assran, J. Romoff, N. Ballas, J. Pineau, M. Rabbat. 鈥淕ossip-based Actor-Learner Architectures for Deep Reinforcement Learning鈥�. NeurIPS 2019.

J. Romoff, P. Henderson, A. Touati, E. Brunskill, J. Pineau, Y. Ollivier, 鈥淪eparable value functions across time-scales鈥�. ICML 2019.

A. Das, T. Gervet, J. Romoff, D. Batra, D. Parikh, M. Rabbat, J. Pineau, 鈥淭arMAC: Targeted Multi-Agent Communication鈥�. ICML 2019.

K. Sinha, S. Sodhani, J. Dong, J. Pineau, W. L. Hamilton. 鈥淐LUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text鈥�. EMNLP 2019.

B. Mazoure, T. Doan, A. Durand, R.D. Helm, J. Pineau. 鈥淟everaging exploration in off-policy algorithms via normalizing flows鈥�. CoRL 2019

L. Caccia, H. van Hoof, A. Courville, J. Pineau. 鈥淒eep Generative Modeling of LiDAR Data鈥�. IROS 2019.

R. Lowe, J. Foerster, Y-L. Boureau, J. Pineau, Y. Dauphin. 鈥淥n the Pitfalls of Measuring Emergent Communication鈥�. AAMAS 2019.

J. Pineau, K. Sinha, G. Fried, R.N. Ke, H. Larochelle (guest editors). ReScience Journal, vol.5(2). Special Issue on the ICLR Reproducibility Challenge 2019.

2018

V. Francois-Lavet, P. Henderson, R. Islam, M. Bellemare, J. Pineau. "An Introduction to Deep Reinforcement Learning鈥�. Foundations and Trends in Machine Learning. 11 (3-4). pp.219-354. 2018.

I. V. Serban, R. Lowe, P. Henderson, L. Charlin, J. Pineau. "A Survey of Available Corpora for Building Data-Driven Dialogue Systems: The Journal Version鈥�. Dialogue & Discourse. 9 (1). pp.1-49. 2018.

A. Durand, O. Maillard, J. Pineau. "Streaming kernel regression with provably adaptive mean, variance, and regularization鈥�. Journal of Machine Learning Research. 19. pp.1-34. 2018.

P. Henderson,R. Islam, P. Bachman, J. Pineau, D. Precup, D. Meger."Deep Reinforcement Learning that Matters鈥�. AAAI. 7 pages. 2018.

P. Henderson, W-D. Chang, P.L. Bacon, D. Meger, J. Pineau, D. Precup. "OptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning鈥�. AAAI. 7 pages. 2018.

P. Henderson, K. Sinha, N. Angelard-Gontier, N.R. Ke, G. Fried, R. Lowe, J. Pineau. "Ethical Challenges in Data-Driven Dialogue Systems鈥�. AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society. 7 pages. 2018.

M. Smith, H. van Hoof, J. Pineau. "An Inference-Based Policy Gradient Method for Learning Options鈥�. ICML. 8 pages. 2018.

A. Durand, C. Achilleos, D. Iacovides, K. Strati, T. Mitsis, J. Pineau. "Contextual Bandits for Adapting Treatment in a Mouse Model of de Novo Carcinogenesis鈥�. Machine Learning for Healthcare. pp.67-82 2018.

P. Thodoro, A. Durand, J. Pineau, D. Precup. "Temporal Regularization for Markov Decision Processes鈥�. NeurIPS (formerly NIPS). 8 pages. 2018.

P. Parthasarathi, J. Pineau. "Extending Neural Generative Conversational Model using External Knowledge Sources鈥�. EMNLP. 6 pages. 2018.

J. Romo, P. Henderson, A. Piche, V. Francois-Lavet, J. Pineau. "Reward Estimation forVariance Reduction in Deep Reinforcement Learning鈥�. International Conference on Robot Learning (CoRL). 11 pages. 2018.

P. Henderson, J. Romo, J. Pineau. "Where Did My OptimumGo?: An Empirical Analysis of Gradient Descent Optimization in Policy Gradient Methods鈥�. EWRL. 2018.

A. Touati, H. Satija, J. Romo, J. Pineau, P. Vincent. "Randomized Value Functions via Multiplicative Normalizing Flows鈥�. 8 pages. EWRL. 2018.

2017

M. Ghorbel, J. Pineau, R. Gourdeau, S. Javdani, S. Srinivasa. 鈥淎 Decision-Theoretic Approach for the Collaborative Control of a Smart Wheelchair鈥�. In. Journal of Social Robotics. pp. 1-15. 2017.

R. Lowe, N. Pow, I.V. Serban, L. Charlin, C-W. Liu J. Pineau. 鈥淭raining end-to-end dialogue systems with the ubuntu dialogue corpus鈥�. In. Dialogue & Discourse. pp. 31-65. 2017.

A. Emami, J El Youssef, R Rabasa-Lhoret, J Pineau, JR Castle, A Haidar. 鈥淢odeling Glucagon Action in Patients with Type 1 Diabetes鈥�. IEEE journal of biomedical and health informatics 21 (4), 1163-1171. 2017.

W. Choi, O. Cyens, T. Chan, M. Schijven, S. Lajoie, M.E. Mancini, P. Dev, L. Fellander-Tsai, M. Ferland, P. Kato, J. Lau, M. Montonaro, J. Pineau, R. Aggarwal. 鈥淓ngagement and Learning in Simulation: Recommendations of the Simnovate Engaged Learning Domain Group鈥�. BMJ Simulation & Technology Enhanced Learning. 2017

R. Lowe, M. Noseworthy, I.V. Serban, N. Angelard-Gontier, E. Bengio, J. Pineau. 鈥淭owards an Automatic Turing Test: Learning to Evaluate Dialogue Responses鈥�. Association for Computational Linguistics (ACL). 2017. Outstanding paper track (1.5% of submissions).

G. Rabusseau, B. Balle, J. Pineau. 鈥淢ultitask Spectral Learning of Weighted Automata鈥�. Neural Information Processing Systems (NIPS). 2017.

D. Bahdanau, P. Brakel, K. Xu, A. Goyal, R. Lowe, J. Pineau, A. Courville, Y. Bengio. 鈥淎n Actor-Critic Algorithm for Sequence Prediction鈥�. International Conference on Learning Representations (ICLR). 2017.

I.V. Serban, A. Sordoni, R. Lowe, L. Charlin, J. Pineau, A. Courville, Y. Bengio.鈥淎 Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues鈥�. Association for the Advancement of Artificial Intelligence (AAAI). 2017.

I.V. Serban, R. Lowe, L. Charlin, J. Pineau. 鈥淕enerative Deep Neural Networks for Dialogue: A Short Review鈥�. Empirical Methods in Natural Language Processing (EMNLP). 2017.

I.V. Serban, A.G. Ororbia II, J. Pineau, A. Courville. 鈥淧iecewise Latent Variables for Neural Variational Text Processing鈥�. Empirical Methods in Natural Language Processing (EMNLP). 2017.

M. Noseworthy, J.C.K. Cheung, J. Pineau. 鈥淧redicting Success in Goal-Driven Human-Human Dialogues鈥�. SIGdial Meeting on Discourse and Dialogue (SIGdial). 2017.

H.P. Truong, P. Parthasarathi, J. Pineau. 鈥淢ACA: A Modular Architecture for Conversational Agents鈥�. SIGdial Meeting on Discourse and Dialogue (SIGDIAL). 2017.

M. Smith, L. Charlin, J. Pineau. 鈥淎 Sparse Probabilistic Model of User Preference Data鈥�. Canadian Conference on Artificial Intelligence (CAIAC). 2017.

E. Bengio, V. Thomas, J. Pineau, D. Precup, Y. Bengio. 鈥淚ndependently Controllable Features鈥� Reinforcement Learning and Decision Making (RLDM). arXiv: 1708.01289. 2017.

I.V. Serban, C. Sankar, M. Germain, S. Zhang, Z. Lin, S. Subramanian, T. Kim, M. Pieper, S. Chandar, N. Ke, S. Rajeswar, A. Brebisson, J.M.R. Sotelo, D. Suhubdy, V. Michalski, A. Nguyen, J. Pineau, Y. Bengio. 鈥淎 Deep Reinforcement Learning Chatbot (Short Version)鈥�. Neural Information Processing Systems (NIPS) Workshop on Conversational AI. 2017.

X. Cao, G. Rabusseau, J. Pineau. 鈥淭ensor Regression Networks with various Low-Rank Tensor Approximations. arXiv: 1712.09520. 2017.

A. Goyal, N.R. Ke, A. Lamb, C. Pal, J. Pineau, Y. Bengio. 鈥淎CtuAL: Actor-Critic Under Adversarial Learning鈥� arXiv: 1711.04755. 2017.

A. Durand, O-A. Maillard, J. Pineau. 鈥淪treaming kernel regression with provably adaptive mean, variance, and regularization鈥� arXiv: 1708.00768. 2017.

P. Henderson,R. Islam, P. Bachman, J. Pineau, D. Precup, D. Meger.鈥淒eep Reinforcement Learning that Matters鈥�. arXiv: 1709.06560. (Accepted at AAAI 2018.)

P. Henderson, W-D. Chang, P.L. Bacon, D. Meger, J. Pineau, D. Precup. 鈥淥ptionGAN: Learning Joint Reward-Policy Options using Generative Adversarial Inverse Reinforcement Learning鈥�. arXiv: 1709.06683. (Accepted at AAAI 2018.)

P. Henderson, K. Sinha, N. Angelard-Gontier, N.R. Ke, G. Fried, R. Lowe, J. Pineau. 鈥淓thical Challenges in Data-Driven Dialogue Systems鈥�. arXiv: 1711.09050. (Accepted at AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society. 2018.)