| InsightBench: Evaluating Business Analytics Agents Through Multi-Step Insight Generation G Sahu, A Puri, J Rodriguez, A Drouin, P Taslakian, V Zantedeschi, ... arXiv preprint arXiv:2407.06423, 2024 | | 2024 |
| WorkArena++: Towards Compositional Planning and Reasoning-based Common Knowledge Work Tasks L Boisvert, M Thakkar, M Gasse, M Caccia, D Chezelles, T Le Sellier, ... arXiv preprint arXiv:2407.05291, 2024 | | 2024 |
| Evaluating Interventional Reasoning Capabilities of Large Language Models T Kasetty, D Mahajan, GK Dziugaite, A Drouin, D Sridhar arXiv preprint arXiv:2404.05545, 2024 | 3 | 2024 |
| WorkArena: How Capable are Web Agents at Solving Common Knowledge Work Tasks? A Drouin, M Gasse, M Caccia, IH Laradji, M Del Verme, T Marty, ... arXiv preprint arXiv:2403.07718, 2024 | 9 | 2024 |
| Geo-bench: Toward foundation models for earth monitoring A Lacoste, N Lehmann, P Rodriguez, E Sherwin, H Kerner, B Lütjens, ... Advances in Neural Information Processing Systems 36, 2024 | 27 | 2024 |
| Lag-llama: Towards foundation models for probabilistic time series forecasting K Rasul, A Ashok, AR Williams, H Ghonia, R Bhagwatkar, A Khorasani, ... Preprint, 2024 | 67* | 2024 |
| Capture the Flag: Uncovering Data Insights with Large Language Models I Laradji, P Taslakian, S Rajeswar, V Zantedeschi, A Lacoste, ... arXiv preprint arXiv:2312.13876, 2023 | | 2023 |
| TACTis-2: Better, faster, simpler attentional copulas for multivariate time series A Ashok, É Marcotte, V Zantedeschi, N Chapados, A Drouin arXiv preprint arXiv:2310.01327, 2023 | 7 | 2023 |
| Benchmarking bayesian causal discovery methods for downstream treatment effect estimation CC Emezue, A Drouin, T Deleu, S Bauer, Y Bengio arXiv preprint arXiv:2307.04988, 2023 | 1 | 2023 |
| Causal discovery with language models as imperfect experts S Long, A Piché, V Zantedeschi, T Schuster, A Drouin arXiv preprint arXiv:2307.02390, 2023 | 21 | 2023 |
| Regions of reliability in the evaluation of multivariate probabilistic forecasts É Marcotte, V Zantedeschi, A Drouin, N Chapados International Conference on Machine Learning, 23958-24004, 2023 | 4 | 2023 |
| Benchmarking Bayesian Causal Discovery Methods for Downstream Treatment Effect Estimation C Chinenye Emezue, A Drouin, T Deleu, S Bauer, Y Bengio arXiv e-prints, arXiv: 2307.04988, 2023 | | 2023 |
| Invariant Causal Set Covering Machines T Godon, B Bauvin, P Germain, J Corbeil, A Drouin arXiv preprint arXiv:2306.04777, 2023 | | 2023 |
| Using Typed Data for Causal Fault Discovery in Networks A Drouin, A Lacoste, P Taslakian, P Brouillard, S Lachapelle US Patent App. 17/466,376, 2023 | | 2023 |
| The Unsolved Challenges of LLMs as Generalist Web Agents: A Case Study R Assouel, T Marty, M Caccia, IH Laradji, A Drouin, S Rajeswar, ... NeurIPS 2023 Foundation Models for Decision Making Workshop, 2023 | 2 | 2023 |
| RandomSCM: interpretable ensembles of sparse classifiers tailored for omics data T Godon, PL Plante, B Bauvin, E Francovic-Fontaine, A Drouin, J Corbeil arXiv preprint arXiv:2208.06436, 2022 | 1 | 2022 |
| TACTiS: Transformer-attentional copulas for time series A Drouin, É Marcotte, N Chapados International Conference on Machine Learning, 5447-5493, 2022 | 40 | 2022 |
| Typing assumptions improve identification in causal discovery P Brouillard, P Taslakian, A Lacoste, S Lachapelle, A Drouin Conference on Causal Learning and Reasoning, 162-177, 2022 | 12 | 2022 |
| Toward foundation models for earth monitoring: Proposal for a climate change benchmark A Lacoste, ED Sherwin, H Kerner, H Alemohammad, B Lütjens, J Irvin, ... arXiv preprint arXiv:2112.00570, 2021 | 27 | 2021 |
| bytesteady: Fast classification using byte-level n-gram embeddings X Zhang, A Drouin, R Li arXiv preprint arXiv:2106.13302, 2021 | 1 | 2021 |
Alexandre LacosteStaff Research Scientist, ServiceNow ResearchVerified email at servicenow.com
