Ramakanth Pasunuru
Ramakanth Pasunuru
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Augmented language models: a survey
G Mialon, R Dessė, M Lomeli, C Nalmpantis, R Pasunuru, R Raileanu, ...
arXiv preprint arXiv:2302.07842, 2023
Multi-reward reinforced summarization with saliency and entailment
R Pasunuru, M Bansal
arXiv preprint arXiv:1804.06451, 2018
Soft layer-specific multi-task summarization with entailment and question generation
H Guo, R Pasunuru, M Bansal
arXiv preprint arXiv:1805.11004, 2018
Opt-iml: Scaling language model instruction meta learning through the lens of generalization
S Iyer, XV Lin, R Pasunuru, T Mihaylov, D Simig, P Yu, K Shuster, T Wang, ...
arXiv preprint arXiv:2212.12017, 2022
Multi-task video captioning with video and entailment generation
R Pasunuru, M Bansal
arXiv preprint arXiv:1704.07489, 2017
Reinforced video captioning with entailment rewards
R Pasunuru, M Bansal
arXiv preprint arXiv:1708.02300, 2017
Multi-source domain adaptation for text classification via distancenet-bandits
H Guo, R Pasunuru, M Bansal
Proceedings of the AAAI conference on artificial intelligence 34 (05), 7830-7838, 2020
Dynamic multi-level multi-task learning for sentence simplification
H Guo, R Pasunuru, M Bansal
arXiv preprint arXiv:1806.07304, 2018
Efficient large scale language modeling with mixtures of experts
M Artetxe, S Bhosale, N Goyal, T Mihaylov, M Ott, S Shleifer, XV Lin, J Du, ...
arXiv preprint arXiv:2112.10684, 2021
Scaling autoregressive multi-modal models: Pretraining and instruction tuning
L Yu, B Shi, R Pasunuru, B Muller, O Golovneva, T Wang, A Babu, B Tang, ...
arXiv preprint arXiv:2309.02591 2 (3), 2023
Efficiently summarizing text and graph encodings of multi-document clusters
R Pasunuru, M Liu, M Bansal, S Ravi, M Dreyer
Proceedings of the 2021 Conference of the North American Chapter of the …, 2021
Crowdsourcing lightweight pyramids for manual summary evaluation
O Shapira, D Gabay, Y Gao, H Ronen, R Pasunuru, M Bansal, ...
arXiv preprint arXiv:1904.05929, 2019
Autosem: Automatic task selection and mixing in multi-task learning
H Guo, R Pasunuru, M Bansal
arXiv preprint arXiv:1904.04153, 2019
Data augmentation for abstractive query-focused multi-document summarization
R Pasunuru, A Celikyilmaz, M Galley, C Xiong, Y Zhang, M Bansal, J Gao
Proceedings of the AAAI Conference on Artificial Intelligence 35 (15), 13666 …, 2021
Continual and multi-task architecture search
R Pasunuru, M Bansal
arXiv preprint arXiv:1906.05226, 2019
Towards improving abstractive summarization via entailment generation
R Pasunuru, H Guo, M Bansal
Proceedings of the Workshop on New Frontiers in Summarization, 27-32, 2017
Complementary explanations for effective in-context learning
X Ye, S Iyer, A Celikyilmaz, V Stoyanov, G Durrett, R Pasunuru
arXiv preprint arXiv:2211.13892, 2022
Few-shot learning with multilingual language models
XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ...
arXiv preprint arXiv:2112.10668, 2021
Few-shot learning with multilingual generative language models
XV Lin, T Mihaylov, M Artetxe, T Wang, S Chen, D Simig, M Ott, N Goyal, ...
Proceedings of the 2022 Conference on Empirical Methods in Natural Language …, 2022
Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov, Srini Iyer, Veselin Stoyanov, and Zornitsa Kozareva. 2022. Improving in-context few-shot learning via self-supervised training
M Chen
arXiv preprint arXiv:2205.01703, 2022
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