Srinivasan Iyer

41 papers A* 5A 1Journal 23Unranked 11

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ASTRO: Teaching Language Models to Reason by Reflecting and Backtracking In-Context. CoRR Joongwon Kim, Anirudh Goyal, Liang Tan, Hannaneh Hajishirzi, Srinivasan Iyer, Tianlu Wang
2025	J	`jnl`	Latent Speech-Text Transformer. CoRR Yen-Ju Lu, Yashesh Gaur, Wei Zhou, Benjamin Muller, Jesús Villalba, Najim Dehak, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Srinivasan Iyer, Duc Le
2024	J	`jnl`	Byte Latent Transformer: Patches Scale Better Than Tokens. CoRR Artidoro Pagnoni, Ram Pasunuru, Pedro Rodríguez, John Nguyen, Benjamin Muller, Margaret Li, Chunting Zhou, Lili Yu, Jason Weston, Luke Zettlemoyer, Gargi Ghosh, Mike Lewis, Ari Holtzman, Srinivasan Iyer
2024	J	`jnl`	Instruction-tuned Language Models are Better Knowledge Learners. CoRR Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodriguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srinivasan Iyer
2024	J	`jnl`	Mixture-of-Transformers: A Sparse and Scalable Architecture for Multi-Modal Foundation Models. CoRR Weixin Liang, Lili Yu, Liang Luo, Srinivasan Iyer, Ning Dong, Chunting Zhou, Gargi Ghosh, Mike Lewis, Wen-tau Yih, Luke Zettlemoyer, Xi Victoria Lin
2024	J	`jnl`	MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts. CoRR Xi Victoria Lin, Akshat Shrivastava, Liang Luo, Srinivasan Iyer, Mike Lewis, Gargi Ghosh, Luke Zettlemoyer, Armen Aghajanyan
2023	—	`conf`	Complementary Explanations for Effective In-Context Learning. ACL (Findings) Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, Veselin Stoyanov, Greg Durrett, Ramakanth Pasunuru
2023	A*	`conf`	LIMA: Less Is More for Alignment. NeurIPS 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
2023	A	`conf`	Methods for Measuring, Updating, and Visualizing Factual Beliefs in Language Models. EACL Peter Hase, Mona T. Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer
2022	J	`jnl`	Complementary Explanations for Effective In-Context Learning. CoRR Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, Ves Stoyanov, Greg Durrett, Ramakanth Pasunuru
2022	A*	`conf`	Efficient Large Scale Language Modeling with Mixtures of Experts. EMNLP 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
2022	J	`jnl`	OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization. CoRR 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
2022	A*	`conf`	QUASER: Question Answering with Scalable Extractive Rationalization. SIGIR Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, Yashar Mehdad
2021	A*	`conf`	DeLighT: Deep and Light-weight Transformer. ICLR Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi
2021	—	`conf`	Do Explanations Help Users Detect Errors in Open-Domain QA? An Evaluation of Spoken vs. Visual Explanations. ACL/IJCNLP (Findings) Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Yashar Mehdad, Robin Jia, Srinivasan Iyer
2021	J	`jnl`	Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs. CoRR Peter Hase, Mona T. Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer
2021	J	`jnl`	EASE: Extractive-Abstractive Summarization with Explanations. CoRR Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta, Marjan Ghazvininejad
2021	J	`jnl`	Efficient Large Scale Language Modeling with Mixtures of Experts. CoRR 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
2021	—	`conf`	RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering. NAACL-HLT Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih
2020	J	`jnl`	Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval. CoRR Wenhan Xiong, Xiang Lorraine Li, Srinivasan Iyer, Jingfei Du, Patrick Lewis, William Yang Wang, Yashar Mehdad, Wen-tau Yih, Sebastian Riedel, Douwe Kiela, Barlas Oguz
2020	J	`jnl`	DeLighT: Very Deep and Light-weight Transformer. CoRR Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi
2020	—	`conf`	Efficient One-Pass End-to-End Entity Linking for Questions. EMNLP (1) Belinda Z. Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, Wen-tau Yih
2020	J	`jnl`	Efficient One-Pass End-to-End Entity Linking for Questions. CoRR Belinda Z. Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, Wen-tau Yih
2020	J	`jnl`	FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. CoRR Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Wen-tau Yih, Yashar Mehdad, Srinivasan Iyer
2020	J	`jnl`	Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA. CoRR Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Robin Jia, Yashar Mehdad, Srinivasan Iyer
2020	J	`jnl`	RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering. CoRR Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih
2019	—	`conf`	JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation. EMNLP/IJCNLP (1) Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer
2019	J	`jnl`	JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation. CoRR Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer
2019	—	`conf`	Learning Programmatic Idioms for Scalable Semantic Parsing. EMNLP/IJCNLP (1) Srinivasan Iyer, Alvin Cheung, Luke Zettlemoyer
2019	J	`jnl`	Learning Programmatic Idioms for Scalable Semantic Parsing. CoRR Srinivasan Iyer, Alvin Cheung, Luke Zettlemoyer
2019	—	`—`	Learning to Map Natural Language to General Purpose Source Code. Srinivasan Iyer
2018	—	`conf`	Learning to Map Context-Dependent Sentences to Executable Formal Queries. NAACL-HLT Alane Suhr, Srinivasan Iyer, Yoav Artzi
2018	J	`jnl`	Learning to Map Context-Dependent Sentences to Executable Formal Queries. CoRR Alane Suhr, Srinivasan Iyer, Yoav Artzi
2018	A*	`conf`	Mapping Language to Code in Programmatic Context. EMNLP Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer
2018	J	`jnl`	Mapping Language to Code in Programmatic Context. CoRR Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer
2018	—	`conf`	Neural Semantic Parsing. ACL (5) Matt Gardner, Pradeep Dasigi, Srinivasan Iyer, Alane Suhr, Luke Zettlemoyer
2017	—	`conf`	Learning a Neural Semantic Parser from User Feedback. ACL (1) Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, Luke Zettlemoyer
2017	J	`jnl`	Learning a Neural Semantic Parser from User Feedback. CoRR Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, Luke Zettlemoyer
2017	—	`conf`	Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. ACL (1) Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, Luke Zettlemoyer
2017	J	`jnl`	Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. CoRR Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, Luke Zettlemoyer
2016	—	`conf`	Summarizing Source Code using a Neural Attention Model. ACL (1) Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer