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Sarath Chandar Anbil ParthipanDepartment of Computer Engineering and Software Engineering
Profile in the Directory of Experts of Polytechnique Montréal
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Abdelsalam, M., Faramarzi, M., Sodhani, S., & Anbil Parthipan, S. C. (2021, June). IIRC: Incremental Implicitly-Refined Classification [Paper]. Conference on Computer Vision and Pattern Recognition (CVPR) (31 pages). External link
Anbil Parthipan, S. C. (2019). On challenges in training recurrent neural networks [Ph.D. Thesis, Université de Montréal]. External link
Anbil Parthipan, S. C., Sankar, C., Vorontsov, E., Kahou, S. E., & Bengio, Y. (2019). Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies. AAAI Conference on Artificial Intelligence, 33(1), 3280-3287. External link
Anbil Parthipan, S. C., Khapra, M. M., Larochelle, H., & Ravindran, B. (2016). Correlational Neural Networks. Neural Computation, 28(2), 257-285. External link
Anbil Parthipan, S. C. (2015). Correlational Neural Networks for Common Representation Learning [Master's Thesis, Indian Institute of Technology Madras]. Unavailable
Anbil Parthipan, S. C., Lauly, S., Larochelle, H., Khapra, M. M., Ravindran, B., Raykar, V., & Saha, A. (2014, December). An autoencoder approach to learning bilingual word representations [Paper]. 27th International Conference on Neural Information Processing Systems, Montréal, Qc, Canada. External link
Bouchoucha, R., Haj Yahmed, A., Patil, D., Rajendran, J., Nikanjam, A., Anbil Parthipan, S. C., & Khomh, F. (2024, October). Toward Debugging Deep Reinforcement Learning Programs with RLExplorer [Paper]. IEEE International Conference on Software Maintenance and Evolution (ICSME 2024), Flagstaff, AZ, USA. External link
Bard, N., Foerster, J. N., Anbil Parthipan, S. C., Burch, N., Lanctot, M., Song, H. F., Parisotto, E., Dumoulin, V., Moitra, S., Hughes, E., Dunning, I., Mourad, S., Larochelle, H., Bellemare, M. G., & Bowling, M. (2020). The Hanabi challenge: A new frontier for AI research. Artificial Intelligence, 280, 19 pages. External link
Chitsaz, K., Fournier, Q., Torcato Mordido, G. F., & Anbil Parthipan, S. C. (2024, November). Exploring Quantization for Efficient Pre-Training of Transformer Language Models [Paper]. Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, FL, USA. External link
Clouâtre, L., Parthasarathi, P., Zouaq, A., & Anbil Parthipan, S. C. (2022, May). Local Structure Matters Most: Perturbation Study in NLU [Paper]. 60th Annual Meeting of the Association-for-Computational-Linguistics (ACL 2022), Dublin, IRELAND. External link
Clouatre, L., Trempe, P., Zouaq, A., & Anbil Parthipan, S. C. (2021, August). MLMLM: link prediction with mean likelihood masked language model [Paper]. The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021), Bangkok, Thailand. Available
De Vries, H., Strub, F., Anbil Parthipan, S. C., Pietquin, O., Larochelle, H., & Courville, A. (2017, July). GuessWhat?! Visual Object Discovery through Multi-modal Dialogue [Paper]. IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2017), Honolulu, HI, USA. External link
Faramarzi, M., Amini, M., Badrinaaraayanan, A., Verma, V., & Anbil Parthipan, S. C. (2022, February). PatchUp: A Feature-Space Block-Level Regularization Technique for Convolutional Neural Networks [Paper]. 36th AAAI Conference on Artificial Intelligence (AAAI 2022). External link
Gottipati, S. K., Pathak, Y., Sattarov, B., Sahir, Nuttall, R., Amini, M., Taylor, M. E., & Anbil Parthipan, S. C. (2021, February). Towered Actor Critic For Handling Multiple Action Types In Reinforcement Learning For Drug Discovery [Paper]. 35th AAAI Conference on Artificial Intelligence / 33rd Conference on Innovative Applications of Artificial Intelligence / 11th Symposium on Educational Advances in Artificial Intelligence. External link
Gottipati, S. K., Sattarov, B., Niu, S., Pathak, Y., Wei, H., Liu, S., Thomas, K. M. J., Blackburn, S., Coley, C. W., Tang, J., Anbil Parthipan, S. C., & Bengio, Y. (2020, July). Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning. [Paper]. 37th International Conference on Machine Learning (ICML 2020), Vienna, Austria. External link
Gottipati, S. K., Pathak, Y., Nuttall, R., Sahir, Chunduru, R., Touati, A., Subramanian, S. G., Taylor, M. E., & Anbil Parthipan, S. C. (2020, December). Maximum reward formulation in reinforcement learning [Paper]. 2020 NeurIPS Deep RL Workshop (15 pages). External link
Gulcehre, C., Anbil Parthipan, S. C., Cho, K., & Bengio, Y. (2018). Dynamic neural turing machine with continuous and discrete addressing schemes. Neural Computation, 30(4), 857-884. External link
Henwood, S., Torcato Mordido, G. F., Savaria, Y., Anbil Parthipan, S. C., & Leduc-Primeau, F. (2024, October). Sharpness-Aware Minimization Scaled by Outlier Normalization for Robust DNNs on In-Memory Computing Accelerators [Paper]. 58th Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, USA. External link
Huang, J., Parthasarathi, P., Rezagholizadeh, M., & Anbil Parthipan, S. C. (2024, November). Context-Aware Assistant Selection for Improved Inference Acceleration with Large Language Models [Paper]. Conference on Empirical Methods in Natural Language Processing, Miami, Florida, USA. External link
Lafleur, D., Anbil Parthipan, S. C., & Pesant, G. (2022, July). Combining reinforcement learning and constraint programming for sequence-generation tasks with hard constraints [Paper]. 28th International Conference on Principles and Practice of Constraint Programming (CP 2022), Haifa, Israel. External link
Laleh, T., Faramarzi, M., Rish, I., & Anbil Parthipan, S. C. (2020, July). Chaotic continual learning [Paper]. 37th International Conference on Machine Learning (PMLR 2020), Vienna, Austria (6 pages). External link
Madsen, A., Anbil Parthipan, S. C., & Reddy, S. (2024, August). Are self-explanations from Large Language Models faithful? [Paper]. 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Hybrid, Bangkok, Thailand. External link
Madsen, A., Reddy, S., & Anbil Parthipan, S. C. (2024, July). Faithfulness Measurable Masked Language Models [Paper]. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria. External link
Madsen, A., Reddy, S., & Anbil Parthipan, S. C. (2023). Post-hoc Interpretability for Neural NLP: A Survey. ACM Computing Surveys, 55(8), 1-42. External link
McRae, P.-A., Parthasarathi, P., Assran, M., & Anbil Parthipan, S. C. (2022, April). Memory augmented optimizers for deep learning [Poster]. 10th International Conference on Learning Representations (ICLR 2022). External link
Nekoei, H., Badrinaaraayanan, A., Sinha, A., Amini, M., Rajendran, J., Mahajan, A., & Anbil Parthipan, S. C. (2023, August). Dealing with non-stationarity in decentralized cooperative multi-agent deep reinforcement learning via multi-timescale learning [Paper]. 2nd Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Qc. Canada. Unavailable
Nekoei, H., Zhao, X. T., Rajendran, J., Liu, M. A., & Anbil Parthipan, S. C. (2023, August). Towards few-shot coordination : revisiting ad-hoc teamplay challenge in the game of Hanabi [Paper]. 2nd Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Qc, Canada. Unavailable
Nekoei, H., Badrinaaraayanan, A., Courville, A., & Anbil Parthipan, S. C. (2021, July). Continuous Coordination As a Realistic Scenario for Lifelong Learning [Paper]. International Conference on Machine Learning (ICML 2021). External link
Olewicki, D., Habchi, S., Nayrolles, M., Faramarzi, M., Anbil Parthipan, S. C., & Adams, B. (2024, April). On the Costs and Benefits of Adopting Lifelong Learning for Software Analytics - Empirical Study on Brown Build and Risk Prediction [Paper]. 46th International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP 2024), Lisbon, Portugal. External link
Prato, G., Huang, J., Parthasarathi, P., Sodhani, S., & Anbil Parthipan, S. C. (2024, November). Do Large Language Models Know How Much They Know? [Paper]. Conference on Empirical Methods in Natural Language Processing (EMNLP 2024), Miami, FL, USA. External link
Parthasarathi, P., Abdelsalam, M., Anbil Parthipan, S. C., & Pineau, J. (2021, July). A brief study on the effects of training generative dialogue models with a semantic loss [Paper]. 22nd Annual Meeting of the Special-Interest-Group-on-Discourse-and-Dialogue (SIGDIAL 2021), Singapore, Singapore. External link
Prato, G., Duchesneau, M., Anbil Parthipan, S. C., & Tapp, A. (2019, July). Towards Lossless Encoding of Sentences [Paper]. 57th annual meeting of the Association for Computational Linguistics (ACL), Florence, Italy. External link
Rahimi-Kalahroudi, A., Rajendran, J., Momennejad, I., van Seijen, H., & Anbil Parthipan, S. C. (2023, August). Replay buffer with local forgetting for adapting to local environment changes in deep model-based reinforcement learning [Paper]. 2nd Conference on Lifelong Learning Agents (CoLLAs 2023), Montreal, Qc, Canada. External link
Reddy, R., Anbil Parthipan, S. C., & Ravindran, B. (2019, May). Edge Replacement Grammars : A Formal Language Approach for Generating Graphs [Paper]. SIAM International Conference on Data Mining (SDM 2019), Calgary, Alberta, Canada. External link
Rajendran, J., Khapra, M. M., Anbil Parthipan, S. C., & Ravindran, B. (2016, June). Bridge Correlational Neural Networks for Multilingual Multimodal Representation Learning [Paper]. Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, San Diego, California. External link
Rongali, S., Anbil Parthipan, S. C., & Ravindran, B. (2015, March). From multiple views to single view: a neural network approach [Paper]. 2nd ACM IKDD Conference on Data Sciences, Bangalore, India. External link
Saha, A., Pahuja, V., Khapra, M. M., Sankaranarayanan, K., & Anbil Parthipan, S. C. (2018, February). Complex Sequential Question Answering: Towards Learning to Converse Over Linked Question Answer Pairs with a Knowledge Graph [Paper]. 32nd AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, Louisiana. External link
Saha, A., Khapra, M. M., Anbil Parthipan, S. C., Rajendran, J., & Cho, K. (2016, December). A Correlational Encoder Decoder Architecture for Pivot Based Sequence Generation [Paper]. 26th International Conference on Computational Linguistics (COLING 2016), Osaka, Japan. External link
Serban, I. V., García-Durán, A., Gülçehre, Ç., Ahn, S., Anbil Parthipan, S. C., Courville, A., & Bengio, Y. (2016, August). Generating Factoid Questions with Recurrent Neural Networks: The 30M Factoid Question-Answer Corpus [Paper]. 54th annual meeting of the Association for Computational Linguistics, Berlin, Germany. External link
Torcato Mordido, G. F., Malviya, P., Baratin, A., & Anbil Parthipan, S. C. (2024, July). Lookbehind-SAM: k Steps Back, 1 Step Forward [Paper]. 41st International Conference on Machine Learning (ICML 2024), Vienna, Austria. External link
Thakkar, M., Bolukbasi, T., Ganapathy, S., Vashishth, S., Anbil Parthipan, S. C., & Talukdar, P. (2023, December). Self-Influence Guided Data Reweighting for Language Model Pre-training [Paper]. Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore. External link
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. External link
Van Seijen, H., Nekoei, H., Racah, E., & Anbil Parthipan, S. C. (2020, December). The LoCA regret: A consistent metric to evaluate model-based behavior in reinforcement learning [Paper]. 34th Conference on Neural Information Processing Systems (NeurIPS 2020). Unavailable
Wan, Y., Rahimi-Kalahroudi, A., Rajendran, J., Momennejad, I., Anbil Parthipan, S. C., & van Seijen, H. (2022, July). Towards Evaluating Adaptivity of Model-Based Reinforcement Learning Methods [Paper]. 39th International Conference on Machine Learning (ICML 2022), Baltimore, MD. External link
Zholus, A., Kuznetsov, M., Schutski, R., Shayakhmetov, R., Polykovskiy, D., Anbil Parthipan, S. C., & Zhavoronkov, A. (2025). BindGPT: A Scalable Framework for 3D Molecular Design via Language Modeling and Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence, 39(24), 26083-26091. External link
Zayed, A., Torcato Mordido, G. F., Baldini, I., & Anbil Parthipan, S. C. (2024, August). Why Don't Prompt-Based Fairness Metrics Correlate? [Paper]. 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand. External link
Zhao, X., Pan, Y., Xiao, C., Anbil Parthipan, S. C., & Rajendran, J. (2023, July). Conditionally Optimistic Exploration for Cooperative Deep Multi-Agent Reinforcement Learning [Paper]. 39th Conference on Uncertainty in Artificial Intelligence (UAI 2023), Pittsburgh, PA, USA. External link
Zayed, A., Parthasarathi, P., Torcato Mordido, G. F., Palangi, H., Shabanian, S., & Anbil Parthipan, S. C. (2023, February). Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness [Paper]. 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. External link
