Multi-Task Video Captioning with Video and Entailment Generation. - Ramakanth Pasunuru; Mohit Bansal (ACL (1), 2017)

Reinforced Video Captioning with Entailment Rewards. - Ramakanth Pasunuru; Mohit Bansal (EMNLP, 2017)

Towards Improving Abstractive Summarization via Entailment Generation. - Ramakanth Pasunuru; Han Guo; Mohit Bansal (NFiS@EMNLP, 2017)

Soft Layer-Specific Multi-Task Summarization with Entailment and Question Generation. - Han Guo; Ramakanth Pasunuru; Mohit Bansal (ACL (1), 2018)

Dynamic Multi-Level Multi-Task Learning for Sentence Simplification. - Han Guo; Ramakanth Pasunuru; Mohit Bansal (COLING, 2018)

Game-Based Video-Context Dialogue. - Ramakanth Pasunuru; Mohit Bansal (EMNLP, 2018)

Multi-Reward Reinforced Summarization with Saliency and Entailment. - Ramakanth Pasunuru; Mohit Bansal (NAACL-HLT (2), 2018)

Continual and Multi-Task Architecture Search. - Ramakanth Pasunuru; Mohit Bansal (ACL (1), 2019)

AutoSeM: Automatic Task Selection and Mixing in Multi-Task Learning. - Han Guo; Ramakanth Pasunuru; Mohit Bansal (NAACL-HLT (1), 2019)

Crowdsourcing Lightweight Pyramids for Manual Summary Evaluation. - Ori Shapira; David Gabay; Yang Gao 021; Hadar Ronen; Ramakanth Pasunuru; Mohit Bansal; Yael Amsterdamer; Ido Dagan (NAACL-HLT (1), 2019)

Multi-Source Domain Adaptation for Text Classification via DistanceNet-Bandits. - Han Guo; Ramakanth Pasunuru; Mohit Bansal (AAAI, 2020)

FENAS: Flexible and Expressive Neural Architecture Search. - Ramakanth Pasunuru; Mohit Bansal (EMNLP (Findings), 2020)

DORB: Dynamically Optimizing Multiple Rewards with Bandits. - Ramakanth Pasunuru; Han Guo; Mohit Bansal (EMNLP (1), 2020)

SuperPAL: Supervised Proposition ALignment for Multi-Document Summarization and Derivative Sub-Tasks. - Ori Ernst; Ori Shapira; Ramakanth Pasunuru; Michael Lepioshkin; Jacob Goldberger; Mohit Bansal; Ido Dagan (CoRR, 2020)

Evaluating Interactive Summarization: an Expansion-Based Framework. - Ori Shapira; Ramakanth Pasunuru; Hadar Ronen; Mohit Bansal; Yael Amsterdamer; Ido Dagan (CoRR, 2020)

Data Augmentation for Abstractive Query-Focused Multi-Document Summarization. - Ramakanth Pasunuru; Asli Celikyilmaz; Michel Galley; Chenyan Xiong; Yizhe Zhang 002; Mohit Bansal; Jianfeng Gao 001 (AAAI, 2021)

Dual Reinforcement-Based Specification Generation for Image De-Rendering. - Ramakanth Pasunuru; David S. Rosenberg; Gideon Mann; Mohit Bansal (SDU@AAAI, 2021)

Summary-Source Proposition-level Alignment: Task, Datasets and Supervised Baseline. - Ori Ernst; Ori Shapira; Ramakanth Pasunuru; Michael Lepioshkin; Jacob Goldberger; Mohit Bansal; Ido Dagan (CoNLL, 2021)

iFacetSum: Coreference-based Interactive Faceted Summarization for Multi-Document Exploration. - Eran Hirsch; Alon Eirew; Ori Shapira; Avi Caciularu; Arie Cattan; Ori Ernst; Ramakanth Pasunuru; Hadar Ronen; Mohit Bansal; Ido Dagan (EMNLP (Demos), 2021)

Continual Few-Shot Learning for Text Classification. - Ramakanth Pasunuru; Veselin Stoyanov; Mohit Bansal (EMNLP (1), 2021)

Efficiently Summarizing Text and Graph Encodings of Multi-Document Clusters. - Ramakanth Pasunuru; Mengwen Liu; Mohit Bansal; Sujith Ravi; Markus Dreyer (NAACL-HLT, 2021)

Extending Multi-Document Summarization Evaluation to the Interactive Setting. - Ori Shapira; Ramakanth Pasunuru; Hadar Ronen; Mohit Bansal; Yael Amsterdamer; Ido Dagan (NAACL-HLT, 2021)

An Overview of Uncertainty Calibration for Text Classification and the Role of Distillation. - Han Guo; Ramakanth Pasunuru; Mohit Bansal (RepL4NLP@ACL-IJCNLP, 2021)

Multi-Document Keyphrase Extraction: A Literature Review and the First Dataset. - Ori Shapira; Ramakanth Pasunuru; Ido Dagan; Yael Amsterdamer (CoRR, 2021)

A Proposition-Level Clustering Approach for Multi-Document Summarization. - Ori Ernst; Avi Caciularu; Ori Shapira; Ramakanth Pasunuru; Mohit Bansal; Jacob Goldberger; Ido Dagan (CoRR, 2021)

Few-shot Learning with Multilingual Language Models. - Xi Victoria Lin; Todor Mihaylov; Mikel Artetxe; Tianlu Wang; Shuohui Chen; Daniel Simig; Myle Ott; Naman Goyal 001; Shruti Bhosale; Jingfei Du; Ramakanth Pasunuru; Sam Shleifer; et al. (CoRR, 2021)

Efficient Large Scale Language Modeling with Mixtures of Experts. - Mikel Artetxe; Shruti Bhosale; Naman Goyal 001; Todor Mihaylov; Myle Ott; Sam Shleifer; Xi Victoria Lin; Jingfei Du; Srinivasan Iyer 001; Ramakanth Pasunuru; Giri Anantharaman; Xian Li 003; et al. (CoRR, 2021)

Multi-Objective Learning for Multi-Modal Natural Language Generation. - Ramakanth Pasunuru (2021)

Efficient Large Scale Language Modeling with Mixtures of Experts. - Mikel Artetxe; Shruti Bhosale; Naman Goyal 001; Todor Mihaylov; Myle Ott; Sam Shleifer; Xi Victoria Lin; Jingfei Du; Srinivasan Iyer 001; Ramakanth Pasunuru; Giridharan Anantharaman; Xian Li 003; et al. (EMNLP, 2022)

Few-shot Learning with Multilingual Generative Language Models. - Xi Victoria Lin; Todor Mihaylov; Mikel Artetxe; Tianlu Wang; Shuohui Chen; Daniel Simig; Myle Ott; Naman Goyal 001; Shruti Bhosale; Jingfei Du; Ramakanth Pasunuru; Sam Shleifer; et al. (EMNLP, 2022)

Improving In-Context Few-Shot Learning via Self-Supervised Training. - Mingda Chen; Jingfei Du; Ramakanth Pasunuru; Todor Mihaylov; Srini Iyer 001; Veselin Stoyanov; Zornitsa Kozareva (NAACL-HLT, 2022)

Proposition-Level Clustering for Multi-Document Summarization. - Ori Ernst; Avi Caciularu; Ori Shapira; Ramakanth Pasunuru; Mohit Bansal; Jacob Goldberger; Ido Dagan (NAACL-HLT, 2022)

Interactive Query-Assisted Summarization via Deep Reinforcement Learning. - Ori Shapira; Ramakanth Pasunuru; Mohit Bansal; Ido Dagan; Yael Amsterdamer (NAACL-HLT, 2022)

OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization. - Srinivasan Iyer 001; Xi Victoria Lin; Ramakanth Pasunuru; Todor Mihaylov; Daniel Simig; Ping Yu; Kurt Shuster 001; Tianlu Wang; Qing Liu; Punit Singh Koura; Xian Li 003; Brian O'Horo; et al. (CoRR, 2022)

MURMUR: Modular Multi-Step Reasoning for Semi-Structured Data-to-Text Generation. - Swarnadeep Saha; Xinyan Yu 001; Mohit Bansal; Ramakanth Pasunuru; Asli Celikyilmaz (ACL (Findings), 2023)

Training Trajectories of Language Models Across Scales. - Mengzhou Xia; Mikel Artetxe; Chunting Zhou; Xi Victoria Lin; Ramakanth Pasunuru; Danqi Chen 001; Luke Zettlemoyer; Veselin Stoyanov (ACL (1), 2023)

Complementary Explanations for Effective In-Context Learning. - Xi Ye; Srinivasan Iyer 001; Asli Celikyilmaz; Veselin Stoyanov; Greg Durrett; Ramakanth Pasunuru (ACL (Findings), 2023)

Crystal: Introspective Reasoners Reinforced with Self-Feedback. - Jiacheng Liu 010; Ramakanth Pasunuru; Hannaneh Hajishirzi; Yejin Choi 001; Asli Celikyilmaz (EMNLP, 2023)

Shepherd: A Critic for Language Model Generation. - Tianlu Wang; Ping Yu; Xiaoqing Ellen Tan; Sean O'Brien; Ramakanth Pasunuru; Jane Dwivedi-Yu; Olga Golovneva; Luke Zettlemoyer; Maryam Fazel-Zarandi; Asli Celikyilmaz (CoRR, 2023)

Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning. - Lili Yu; Bowen Shi; Ramakanth Pasunuru; Benjamin Muller; Olga Golovneva; Tianlu Wang; Arun Babu; Binh Tang; Brian Karrer; Shelly Sheynin; Candace Ross; Adam Polyak; et al. (CoRR, 2023)

Making PPO even better: Value-Guided Monte-Carlo Tree Search decoding. - Jiacheng Liu 010; Andrew Cohen; Ramakanth Pasunuru; Yejin Choi 001; Hannaneh Hajishirzi; Asli Celikyilmaz (CoRR, 2023)

Walking Down the Memory Maze: Beyond Context Limit through Interactive Reading. - Howard Chen 003; Ramakanth Pasunuru; Jason Weston; Asli Celikyilmaz (CoRR, 2023)

PathFinder: Guided Search over Multi-Step Reasoning Paths. - Olga Golovneva; Sean O'Brien; Ramakanth Pasunuru; Tianlu Wang; Luke Zettlemoyer; Maryam Fazel-Zarandi; Asli Celikyilmaz (CoRR, 2023)

Augmented Language Models: a Survey. - Grégoire Mialon; Roberto Dessì; Maria Lomeli; Christoforos Nalmpantis; Ramakanth Pasunuru; Roberta Raileanu; Baptiste Rozière; Timo Schick; Jane Dwivedi-Yu; Asli Celikyilmaz; Edouard Grave; Yann LeCun; et al. (Trans. Mach. Learn. Res., 2023)

ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization. - David Wan; Koustuv Sinha; Srini Iyer 001; Asli Celikyilmaz; Mohit Bansal; Ramakanth Pasunuru (ACL (Findings), 2024)

The ART of LLM Refinement: Ask, Refine, and Trust. - Kumar Shridhar; Koustuv Sinha; Andrew Cohen; Tianlu Wang; Ping Yu; Ramakanth Pasunuru; Mrinmaya Sachan; Jason Weston; Asli Celikyilmaz (NAACL-HLT, 2024)

Characterizing and Efficiently Accelerating Multimodal Generation Model Inference. - Yejin Lee 010; Anna Y. Sun; Basil Hosmer; Bilge Acun; Can Balioglu; Changhan Wang; Charles David Hernandez; Christian Puhrsch; Daniel Haziza; Driss Guessous; Francisco Massa; Jacob Kahn; et al. (CoRR, 2024)

Byte Latent Transformer: Patches Scale Better Than Tokens. - Artidoro Pagnoni; Ramakanth Pasunuru; Pedro Rodríguez 001; John Nguyen; Benjamin Muller; Margaret Li; Chunting Zhou; Lili Yu; Jason E. Weston; Luke Zettlemoyer; Gargi Ghosh; Mike Lewis; et al. (ACL (1), 2025)

Efficient Tool Use with Chain-of-Abstraction Reasoning. - Silin Gao; Jane Dwivedi-Yu; Ping Yu; Xiaoqing Ellen Tan; Ramakanth Pasunuru; Olga Golovneva; Koustuv Sinha; Asli Celikyilmaz; Antoine Bosselut; Tianlu Wang (COLING, 2025)