Prasanna Parthasarathi
Citado por
Citado por
Extending neural generative conversational model using external knowledge sources
P Parthasarathi, J Pineau
arXiv preprint arXiv:1809.05524, 2018
Learning an unreferenced metric for online dialogue evaluation
K Sinha, P Parthasarathi, J Wang, R Lowe, WL Hamilton, J Pineau
arXiv preprint arXiv:2005.00583, 2020
Unnatural language inference
K Sinha, P Parthasarathi, J Pineau, A Williams
arXiv preprint arXiv:2101.00010, 2020
a2t: Attend, adapt and transfer: Attentive deep architecture for adaptive transfer from multiple sources
J Rajendran, A Lakshminarayanan, MM Khapra, P Prasanna, ...
Neural assistant: Joint action prediction, response generation, and latent knowledge reasoning
A Neelakantan, S Yavuz, S Narang, V Prasad, B Goodrich, D Duckworth, ...
arXiv preprint arXiv:1910.14613, 2019
Adaapt: A deep architecture for adaptive policy transfer from multiple sources
J Rajendran, P Prasanna, B Ravindran, MM Khapra
arXiv preprint arXiv 1510, 2015
Local structure matters most: Perturbation study in NLU
L Clouatre, P Parthasarathi, A Zouaq, S Chandar
arXiv preprint arXiv:2107.13955, 2021
Maca: A modular architecture for conversational agents
HP Truong, P Parthasarathi, J Pineau
Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, 93-102, 2017
Sometimes we want ungrammatical translations
P Parthasarathi, K Sinha, J Pineau, A Williams
Findings of the Association for Computational Linguistics: EMNLP 2021, 3205-3227, 2021
Do Encoder Representations of Generative Dialogue Models have sufficient summary of the Information about the task?
P Parthasarathi, J Pineau, S Chandar
Proceedings of the 22nd Annual Meeting of the Special Interest Group on …, 2021
Memory Augmented Optimizers for Deep Learning
PA McRae, P Parthasarathi, M Assran, S Chandar
arXiv preprint arXiv:2106.10708, 2021
A Brief Study on the Effects of Training Generative Dialogue Models with a Semantic loss
P Parthasarathi, M Abdelsalam, J Pineau, S Chandar
arXiv preprint arXiv:2106.10619, 2021
On Task-Level Dialogue Composition of Generative Transformer Model
P Parthasarathi, A Neelakantan, S Narang
arXiv preprint arXiv:2010.04826, 2020
The RLLChatbot: a solution to the ConvAI challenge
N Gontier, K Sinha, P Henderson, I Serban, M Noseworthy, ...
arXiv preprint arXiv:1811.02714, 2018
Variational encoder decoder for image generation conditioned on captions
J Romoff, N Angelard-Gontier, P Parthasarathi
In Proceedings of the 33rd International Conference on Machine Learning, 2016
Proceedings of the Workshop on Novel Ideas in Learning-to-Learn through Interaction (NILLI 2022)
P Parthasarathi, MA Côté
Proceedings of the Workshop on Novel Ideas in Learning-to-Learn through …, 2022
Deep Learning on a Healthy Data Diet: Finding Important Examples for Fairness
A Zayed, P Parthasarathi, G Mordido, H Palangi, S Shabanian, S Chandar
arXiv preprint arXiv:2211.11109, 2022
Detecting Languages Unintelligible to Multilingual Models through Local Structure Probes
L Clouâtre, P Parthasarathi, A Zouaq, S Chandar
arXiv preprint arXiv:2211.05015, 2022
Local Structure Matters Most in Most Languages
L Clouâtre, P Parthasarathi, A Zouaq, S Chandar
arXiv preprint arXiv:2211.05025, 2022
Quantifying language understanding of neural language models
P Parthasarathi
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Artículos 1–20