Ramakanth Pasunuru

About


I am a Research Scientist at FAIR, Meta. I received my Ph.D. in 2021 from Computer Science Department, UNC Chapel Hill (where I was advised by Prof. Mohit Bansal), and my B.Tech and M.Tech from IIT Kharagpur in 2015.

I am interested in broad range of areas within NLP and computer vision such as multi-modal pre-training, Aligment of LLMs, and Reasoning.

[Google Scholar], [Github], [Twitter]

Publications

For my latest publications, please visit my [Google Scholar] page.

2022

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OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization (pdf)(code)

Srinivasan Iyer*, Xi Victoria Lin*, Ramakanth Pasunuru*, Todor Mihaylov, Daniel Simig, Ping Yu, Kurt Shuster, Tianlu Wang, Qing Liu, Punit Singh Koura, Xian Li, Brian O'Horo, Gabriel Pereyra, Jeff Wang, Christopher Dewan, Asli Celikyilmaz, Luke Zettlemoyer, and Ves Stoyanov

Complementary Explanations for Effective In-Context Learning (pdf)

Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, Ves Stoyanov, Greg Durrett, and Ramakanth Pasunuru

MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation (pdf)

Swarnadeep Saha, Xinyan Velocity Yu, Mohit Bansal, Ramakanth Pasunuru, and Asli Celikyilmaz

Training Trajectories of Language Models Across Scales (pdf)

Mengzhou Xia, Mikel Artetxe, Chunting Zhou, Xi Victoria Lin, Ramakanth Pasunuru, Danqi Chen, Luke Zettlemoyer, and Ves Stoyanov

Few-shot Learning with Multilingual Language Models (pdf)

Xi Victoria Lin, Todor Mihaylov, Mikel Artetxe, Tianlu Wang, Shuohui Chen, Daniel Simig, Myle Ott, Naman Goyal, Shruti Bhosale, Jingfei Du, Ramakanth Pasunuru, Sam Shleifer, Punit Singh Koura, Vishrav Chaudhary, Brian O'Horo, Jeff Wang, Luke Zettlemoyer, Zornitsa Kozareva, Mona Diab, Veselin Stoyanov, and Xian Li

Efficient Large Scale Language Modeling with Mixtures of Experts (pdf)

Mikel Artetxe, Shruti Bhosale, Naman Goyal, Todor Mihaylov, Myle Ott, Sam Shleifer, Xi Victoria Lin, Jingfei Du, Srinivasan Iyer, Ramakanth Pasunuru, Giri Anantharaman, Xian Li, Shuohui Chen, Halil Akin, Mandeep Baines, Louis Martin, Xing Zhou, Punit Singh Koura, Brian O'Horo, Jeff Wang, Luke Zettlemoyer, Mona Diab, Zornitsa Kozareva, and Ves Stoyanov

Improving In-Context Few-Shot Learning via Self-Supervised Training, In NAACL 2022 (pdf)

Mingda Chen, Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov, Srini Iyer, Veselin Stoyanov, and Zornitsa Kozareva

Proposition-Level Clustering for Multi-Document Summarization, In NAACL 2022 (pdf)(code)

Ori Ernst, Avi Caciularu, Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Jacob Goldberger, and Ido Dagan.

Interactive Query-Assisted Summarization via Deep Reinforcement Learning, In NAACL 2022 (pdf)(code)

Ori Shapira, Ramakanth Pasunuru, Mohit Bansal, Ido Dagan, and Yael Amsterdamer

Multi-Document Keyphrase Extraction: Dataset, Baselines and Review (pdf)

Ori Shapira, Ramakanth Pasunuru, Ido Dagan, and Yael Amsterdamer

2021

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Continual Few-Shot Learning for Text Classification, In EMNLP 2021 (pdf)(code)

Ramakanth Pasunuru, Veselin Stoyanov, and Mohit Bansal

iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Exploration, In EMNLP 2021 demo track (pdf)(code+demo)

Eran Hirsch, Alon Eirew, Ori Shapira, Avi Caciularu, Arie Cattan, Ori Ernst, Ramakanth Pasunuru, Hadar Ronen, Mohit Bansal, and Ido Dagan

An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation, In Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP-2021) (pdf)

Han Guo, Ramakanth Pasunuru, and Mohit Bansal

Efficiently Summarizing Text and Graph Encodings of Multi-Document Clusters, In NAACL 2021 (pdf)(code)

Ramakanth Pasunuru, Mengwen Liu, Mohit Bansal, Sujith Ravi, and Markus Dreyer

Data Augmentation for Abstractive Query-Focused Multi-Document Summarization, In AAAI 2021 (pdf)(code)

Ramakanth Pasunuru, Asli Celikyilmaz, Michel Galley, Chenyan Xiong, Yizhe Zhang, Mohit Bansal, and Jianfeng Gao

Dual Reinforcement-Based Specification Generation for Image De-Rendering, In Workshop on Scientific Document Understanding, AAAI 2021 (pdf)

Ramakanth Pasunuru, David Rosenberg, Gideon Mann, and Mohit Bansal

Extending Multi-Document Summarization Evaluation to the Interactive Setting, In NAACL 2021 (pdf)

Ori Shapira, Ramakanth Pasunuru, Hadar Ronen, Mohit Bansal, Yael Amsterdamer, and Ido Dagan

Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline, In CoNLL 2021 (pdf)

Ori Ernst, Ori Shapira, Ramakanth Pasunuru, Michael Lepioshkin, Jacob Goldberger, Mohit Bansal, and Ido Dagan
(Best Paper Runner-Up)

2020

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DORB: Dynamically Optimizing Multiple Rewards with Bandits, In EMNLP 2020 (pdf)

Ramakanth Pasunuru, Han Guo, and Mohit Bansal

FENAS: Flexible and Expressive Neural Architecture Search, In Findings of EMNLP 2020 (pdf)

Ramakanth Pasunuru and Mohit Bansal

Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits, In AAAI 2020 (pdf)

Han Guo, Ramakanth Pasunuru, and Mohit Bansal

2019

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Continual and Multi-Task Architecture Search, In ACL 2019 (pdf)(code)(slides)

Ramakanth Pasunuru and Mohit Bansal

AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning, In NAACL 2019 (pdf)(code)

Han Guo, Ramakanth Pasunuru, and Mohit Bansal

Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation, In NAACL 2019 (pdf)(code)

Ori Shapira, David Gabay, Yang Gao, Hadar Ronen, Ramakanth Pasunuru, Mohit Bansal, Yael Amsterdamer, and Ido Dagan

DSTC7-AVSD: Scene-Aware Video-Dialogue Systems with Dual Attention, In DSTC7 Workshop, AAAI 2019 (pdf)(slides)

Ramakanth Pasunuru and Mohit Bansal

2018

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Game-Based Video-Context Dialogue, In EMNLP 2018 (pdf v2 [fixed Table5 typo])(data/code)(slides)

Ramakanth Pasunuru and Mohit Bansal

Dynamic Multi-Level Multi-Task Learning for Sentence Simplification, In COLING 2018 (pdf)(code)

Han Guo, Ramakanth Pasunuru, and Mohit Bansal
(Area Chair Favorites)

Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation, In ACL 2018 (pdf)

Ramakanth Pasunuru*, Han Guo*, and Mohit Bansal

Multi-Reward Reinforced Summarization with Saliency and Entailment, In NAACL 2018 (pdf)

Ramakanth Pasunuru and Mohit Bansal

2017

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Interactive-Length Multi-Task Video Captioning with Cooperative Feedback, In NIPS 2017 demo track (pdf)

Han Guo, Ramakanth Pasunuru, and Mohit Bansal

Reinforced Video Captioning with Entailment Rewards, In EMNLP 2017 (pdf)(code)

Ramakanth Pasunuru and Mohit Bansal

Towards Improving Abstractive Summarization via Entailment Generation, In Workshop on Summarization Frontiers, EMNLP 2017 (pdf)

Ramakanth Pasunuru, Han Guo, and Mohit Bansal
(Contributed Talk)

Multi-Task Video Captioning with Video and Entailment Generation, In ACL 2017 (pdf)(slides)

Ramakanth Pasunuru and Mohit Bansal
(Outstanding Paper Award)

2016

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Compressed sensing of respiratory signals promoting joint sparsity. In NCC, 2016

Ramakanth Reddy, Priya Ranjan Muduli, and Anirban Mukherjee

2015

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Structural prediction of dynamic bayesian networks with partial prior information. In IEEE, Trans. NanoBioScience, 2015

Aniruddha Maiti, Ramakanth Reddy, and Anirban Mukherjee

(Impact Factor: 2.771)