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Madsen, A., Reddy, S., & Anbil Parthipan, S. C. (2023). Post-hoc Interpretability for Neural NLP: A Survey. ACM Computing Surveys, 55(8), 1-42. Lien externe
Vaibhav Mehta, S., Patil, D., Anbil Parthipan, S. C., & Strubell, E. (2023). An Empirical Investigation of the Role of Pre-training in Lifelong Learning. Journal of Machine Learning Research, 24, 50-50. Lien externe
Nekoei, H., Badrinaaraayanan, A., Sinha, A., Amini, M., Rajendran, J., Mahajan, A., & Anbil Parthipan, S. C. (août 2023). Dealing with non-stationarity in decentralized cooperative multi-agent deep reinforcement learning via multi-timescale learning [Communication écrite]. 2nd Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Qc. Canada. Non disponible
Nekoei, H., Zhao, X. T., Rajendran, J., Liu, M. A., & Anbil Parthipan, S. C. (août 2023). Towards few-shot coordination : revisiting ad-hoc teamplay challenge in the game of Hanabi [Communication écrite]. 2nd Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Qc, Canada. Non disponible
Rahimi-Kalahroudi, A., Rajendran, J., Momennejad, I., van Seijen, H., & Anbil Parthipan, S. C. (août 2023). Replay buffer with local forgetting for adapting to local environment changes in deep model-based reinforcement learning [Communication écrite]. 2nd Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Qc, Canada. Lien externe
Thakkar, M., Bolukbasi, T., Ganapathy, S., Vashishth, S., Anbil Parthipan, S. C., & Talukdar, P. (décembre 2023). Self-Influence Guided Data Reweighting for Language Model Pre-training [Communication écrite]. Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore. Lien externe
Zayed, A., Parthasarathi, P., Mordido, G., Palangi, H., Shabanian, S., & Anbil Parthipan, S. C. (février 2023). Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness [Communication écrite]. 37th AAAI Conference on Artificial Intelligence (AAAI 2023) and 35th Conference on Innovative Applications of Artificial Intelligence (IAAI 2023) and 13th Symposium on Educational Advances in Artificial Intelligence (EAAI 2023), Washington, DC, USA. Lien externe
Zhao, X., Pan, Y., Xiao, C., Anbil Parthipan, S. C., & Rajendran, J. (juillet 2023). Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning [Communication écrite]. 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA. Lien externe
