Andrew Robert Williams, Arjun Ashok, Étienne Marcotte, Valentina Zantedeschi, Jithendaraa Subramanian, Roland Riachi, James Requeima, Alexandre Lacoste, Irina Rish, Nicolas Chapados and Alexandre Drouin
Paper (2025)
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| Additional Information: | https://servicenow.github.io/context-is-key-forecasting/v0/ |
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| Department: | Department of Computer Engineering and Software Engineering |
| PolyPublie URL: | https://publications.polymtl.ca/76487/ |
| Conference Title: | 42nd International Conference on Machine Learning (PMLR 2025) |
| Conference Location: | Vancouver, BC, Canada |
| Conference Date(s): | 2025-02-13 - 2025-02-19 |
| Publisher: | PMLR |
| Official URL: | https://proceedings.mlr.press/v267/williams25a.htm... |
| Date Deposited: | 12 May 2026 12:12 |
| Last Modified: | 12 May 2026 12:12 |
| Cite in APA 7: | Williams, A. R., Ashok, A., Marcotte, É., Zantedeschi, V., Subramanian, J., Riachi, R., Requeima, J., Lacoste, A., Rish, I., Chapados, N., & Drouin, A. (2025, February). Context is Key: A Benchmark for Forecasting with Essential Textual Information [Paper]. 42nd International Conference on Machine Learning (PMLR 2025), Vancouver, BC, Canada. https://proceedings.mlr.press/v267/williams25a.html |
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