Srinivasan Iyer

According to our database, Srinivasan Iyer authored at least 36 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts.

Xi Victoria Lin, Akshat Shrivastava, Liang Luo, Srinivasan Iyer, Mike Lewis, Gargi Ghosh, Luke Zettlemoyer, Armen Aghajanyan

CoRR, 2024

ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization.

David Wan, Koustuv Sinha, Srini Iyer, Asli Celikyilmaz, Mohit Bansal, Ramakanth Pasunuru

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Instruction-tuned Language Models are Better Knowledge Learners.

Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodríguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srini Iyer

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

LIMA: Less Is More for Alignment.

Chunting Zhou, Pengfei Liu, Puxin Xu, Srinivasan Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

LEVER: Learning to Verify Language-to-Code Generation with Execution.

Ansong Ni, Srini Iyer, Dragomir Radev, Veselin Stoyanov, Wen-Tau Yih, Sida I. Wang, Xi Victoria Lin

Proceedings of the International Conference on Machine Learning, 2023

Demystifying Prompts in Language Models via Perplexity Estimation.

Hila Gonen, Srini Iyer, Terra Blevins, Noah A. Smith, Luke Zettlemoyer

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Methods for Measuring, Updating, and Visualizing Factual Beliefs in Language Models.

Peter Hase, Mona T. Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer

Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, 2023

Complementary Explanations for Effective In-Context Learning.

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

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022

OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization.

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, Ves Stoyanov

CoRR, 2022

QUASER: Question Answering with Scalable Extractive Rationalization.

Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, Yashar Mehdad

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization.

Alexander R. Fabbri, Xiaojian Wu, Srini Iyer, Haoran Li, Mona T. Diab

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Improving In-Context Few-Shot Learning via Self-Supervised Training.

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

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Efficient Large Scale Language Modeling with Mixtures of Experts.

Mikel Artetxe, Shruti Bhosale, Naman Goyal, Todor Mihaylov, Myle Ott, Sam Shleifer, Xi Victoria Lin, Jingfei Du, Srinivasan Iyer, Ramakanth Pasunuru, Giridharan Anantharaman, Xian Li, Shuohui Chen, Halil Akin, Mandeep Baines, Louis Martin, Xing Zhou, Punit Singh Koura, Brian O'Horo, Jeffrey Wang, Luke Zettlemoyer, Mona T. Diab, Zornitsa Kozareva, Veselin Stoyanov

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection.

Badr AlKhamissi, Faisal Ladhak, Srini Iyer, Veselin Stoyanov, Zornitsa Kozareva, Xian Li, Pascale Fung, Lambert Mathias, Asli Celikyilmaz, Mona T. Diab

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Efficient Large Scale Language Modeling with Mixtures of Experts.

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 T. Diab, Zornitsa Kozareva, Ves Stoyanov

CoRR, 2021

Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs.

Peter Hase, Mona T. Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer

CoRR, 2021

EASE: Extractive-Abstractive Summarization with Explanations.

Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta, Marjan Ghazvininejad

CoRR, 2021

Multi-Perspective Abstractive Answer Summarization.

Alexander R. Fabbri, Xiaojian Wu, Srini Iyer, Mona T. Diab

CoRR, 2021

RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering.

Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval.

Wenhan Xiong, Xiang Lorraine Li, Srini Iyer, Jingfei Du, Patrick S. H. Lewis, William Yang Wang, Yashar Mehdad, Scott Yih, Sebastian Riedel, Douwe Kiela, Barlas Oguz

Proceedings of the 9th International Conference on Learning Representations, 2021

DeLighT: Deep and Light-weight Transformer.

Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi

Proceedings of the 9th International Conference on Learning Representations, 2021

FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation.

Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Scott Yih, Yashar Mehdad, Srini Iyer

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Do Explanations Help Users Detect Errors in Open-Domain QA? An Evaluation of Spoken vs. Visual Explanations.

Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Yashar Mehdad, Robin Jia, Srinivasan Iyer

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA.

Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Robin Jia, Yashar Mehdad, Srinivasan Iyer

CoRR, 2020

RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering.

Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih

CoRR, 2020

DeLighT: Very Deep and Light-weight Transformer.

Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi

CoRR, 2020

Efficient One-Pass End-to-End Entity Linking for Questions.

Belinda Z. Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, Wen-tau Yih

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Learning to Map Natural Language to General Purpose Source Code.

Srinivasan Iyer

PhD thesis, 2019

Learning Programmatic Idioms for Scalable Semantic Parsing.

Srinivasan Iyer, Alvin Cheung, Luke Zettlemoyer

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation.

Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Learning to Map Context-Dependent Sentences to Executable Formal Queries.

Alane Suhr, Srinivasan Iyer, Yoav Artzi

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Mapping Language to Code in Programmatic Context.

Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Neural Semantic Parsing.

Matt Gardner, Pradeep Dasigi, Srinivasan Iyer, Alane Suhr, Luke Zettlemoyer

Proceedings of ACL 2018, Melbourne, Australia, July 15-20, 2018, Tutorial Abstracts, 2018

2017

Neural AMR: Sequence-to-Sequence Models for Parsing and Generation.

Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, Luke Zettlemoyer

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

Learning a Neural Semantic Parser from User Feedback.

Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, Luke Zettlemoyer

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Summarizing Source Code using a Neural Attention Model.

Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016