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Srinivasan Iyer 0001
Person information
- affiliation: Facebook AI Research, Meta AI Research, Seattle, WA, USA
- affiliation (PhD 2019): University of Washington, Paul G. Allen Computer Science and Engineering, Seattle, WA, USA
Other persons with the same name
- Srinivasan Iyer 0002 (aka: Srinivasan V Iyer 0002) — Stanford University, Stanford Center for Biomedical Informatics Research, CA, USA
- Srinivasan Iyer 0003 — University of Texas at Dallas, Erik Jonsson School of Engineering and Computer Science, Richardson, TX, USA
- Srinivasan Iyer 0004 — Vivekanand Education Society's Institute of Technology, Sindhi Society, Chembur, Mumbai, India
- Srinivasan Iyer 0005 — Senseair AB, Delsbo, Sweden
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2020 – today
- 2024
- [c26]Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodríguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srini Iyer:
Instruction-tuned Language Models are Better Knowledge Learners. ACL (1) 2024: 5421-5434 - [c25]David Wan, Koustuv Sinha, Srini Iyer, Asli Celikyilmaz, Mohit Bansal, Ramakanth Pasunuru:
ACUEval: Fine-grained Hallucination Evaluation and Correction for Abstractive Summarization. ACL (Findings) 2024: 10036-10056 - [i26]Zhengbao Jiang, Zhiqing Sun, Weijia Shi, Pedro Rodriguez, Chunting Zhou, Graham Neubig, Xi Victoria Lin, Wen-tau Yih, Srinivasan Iyer:
Instruction-tuned Language Models are Better Knowledge Learners. CoRR abs/2402.12847 (2024) - [i25]Xi Victoria Lin, Akshat Shrivastava, Liang Luo, Srinivasan Iyer, Mike Lewis, Gargi Ghosh, Luke Zettlemoyer, Armen Aghajanyan:
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts. CoRR abs/2407.21770 (2024) - 2023
- [c24]Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, Veselin Stoyanov, Greg Durrett, Ramakanth Pasunuru:
Complementary Explanations for Effective In-Context Learning. ACL (Findings) 2023: 4469-4484 - [c23]Peter Hase, Mona T. Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer:
Methods for Measuring, Updating, and Visualizing Factual Beliefs in Language Models. EACL 2023: 2706-2723 - [c22]Hila Gonen, Srini Iyer, Terra Blevins, Noah A. Smith, Luke Zettlemoyer:
Demystifying Prompts in Language Models via Perplexity Estimation. EMNLP (Findings) 2023: 10136-10148 - [c21]Ansong Ni, Srini Iyer, Dragomir Radev, Veselin Stoyanov, Wen-Tau Yih, Sida I. Wang, Xi Victoria Lin:
LEVER: Learning to Verify Language-to-Code Generation with Execution. ICML 2023: 26106-26128 - [c20]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:
LIMA: Less Is More for Alignment. NeurIPS 2023 - [i24]Ansong Ni, Srini Iyer, Dragomir Radev, Ves Stoyanov, Wen-tau Yih, Sida I. Wang, Xi Victoria Lin:
LEVER: Learning to Verify Language-to-Code Generation with Execution. CoRR abs/2302.08468 (2023) - [i23]Chunting Zhou, Pengfei Liu, Puxin Xu, Srini Iyer, Jiao Sun, Yuning Mao, Xuezhe Ma, Avia Efrat, Ping Yu, Lili Yu, Susan Zhang, Gargi Ghosh, Mike Lewis, Luke Zettlemoyer, Omer Levy:
LIMA: Less Is More for Alignment. CoRR abs/2305.11206 (2023) - 2022
- [c19]Badr AlKhamissi, Faisal Ladhak, Srini Iyer, Veselin Stoyanov, Zornitsa Kozareva, Xian Li, Pascale Fung, Lambert Mathias, Asli Celikyilmaz, Mona T. Diab:
ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection. EMNLP 2022: 2109-2120 - [c18]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:
Efficient Large Scale Language Modeling with Mixtures of Experts. EMNLP 2022: 11699-11732 - [c17]Alexander R. Fabbri, Xiaojian Wu, Srini Iyer, Haoran Li, Mona T. Diab:
AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization. NAACL-HLT 2022: 2508-2520 - [c16]Mingda Chen, Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov, Srini Iyer, Veselin Stoyanov, Zornitsa Kozareva:
Improving In-Context Few-Shot Learning via Self-Supervised Training. NAACL-HLT 2022: 3558-3573 - [c15]Asish Ghoshal, Srinivasan Iyer, Bhargavi Paranjape, Kushal Lakhotia, Scott Wen-tau Yih, Yashar Mehdad:
QUASER: Question Answering with Scalable Extractive Rationalization. SIGIR 2022: 1208-1218 - [i22]Mingda Chen, Jingfei Du, Ramakanth Pasunuru, Todor Mihaylov, Srini Iyer, Veselin Stoyanov, Zornitsa Kozareva:
Improving In-Context Few-Shot Learning via Self-Supervised Training. CoRR abs/2205.01703 (2022) - [i21]Badr AlKhamissi, Faisal Ladhak, Srini Iyer, Ves Stoyanov, Zornitsa Kozareva, Xian Li, Pascale Fung, Lambert Mathias, Asli Celikyilmaz, Mona T. Diab:
ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection. CoRR abs/2205.12495 (2022) - [i20]Xi Ye, Srinivasan Iyer, Asli Celikyilmaz, Ves Stoyanov, Greg Durrett, Ramakanth Pasunuru:
Complementary Explanations for Effective In-Context Learning. CoRR abs/2211.13892 (2022) - [i19]Hila Gonen, Srini Iyer, Terra Blevins, Noah A. Smith, Luke Zettlemoyer:
Demystifying Prompts in Language Models via Perplexity Estimation. CoRR abs/2212.04037 (2022) - [i18]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:
OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization. CoRR abs/2212.12017 (2022) - 2021
- [c14]Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Yashar Mehdad, Robin Jia, Srinivasan Iyer:
Do Explanations Help Users Detect Errors in Open-Domain QA? An Evaluation of Spoken vs. Visual Explanations. ACL/IJCNLP (Findings) 2021: 1103-1116 - [c13]Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Scott Yih, Yashar Mehdad, Srini Iyer:
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. EMNLP (1) 2021: 3712-3727 - [c12]Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi:
DeLighT: Deep and Light-weight Transformer. ICLR 2021 - [c11]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:
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval. ICLR 2021 - [c10]Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih:
RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering. NAACL-HLT 2021: 1280-1287 - [i17]Alexander R. Fabbri, Xiaojian Wu, Srini Iyer, Mona T. Diab:
Multi-Perspective Abstractive Answer Summarization. CoRR abs/2104.08536 (2021) - [i16]Haoran Li, Arash Einolghozati, Srinivasan Iyer, Bhargavi Paranjape, Yashar Mehdad, Sonal Gupta, Marjan Ghazvininejad:
EASE: Extractive-Abstractive Summarization with Explanations. CoRR abs/2105.06982 (2021) - [i15]Alexander R. Fabbri, Xiaojian Wu, Srini Iyer, Haoran Li, Mona T. Diab:
AnswerSumm: A Manually-Curated Dataset and Pipeline for Answer Summarization. CoRR abs/2111.06474 (2021) - [i14]Peter Hase, Mona T. Diab, Asli Celikyilmaz, Xian Li, Zornitsa Kozareva, Veselin Stoyanov, Mohit Bansal, Srinivasan Iyer:
Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs. CoRR abs/2111.13654 (2021) - [i13]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:
Efficient Large Scale Language Modeling with Mixtures of Experts. CoRR abs/2112.10684 (2021) - 2020
- [c9]Belinda Z. Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, Wen-tau Yih:
Efficient One-Pass End-to-End Entity Linking for Questions. EMNLP (1) 2020: 6433-6441 - [i12]Sachin Mehta, Marjan Ghazvininejad, Srinivasan Iyer, Luke Zettlemoyer, Hannaneh Hajishirzi:
DeLighT: Very Deep and Light-weight Transformer. CoRR abs/2008.00623 (2020) - [i11]Wenhan Xiong, Xiang Lorraine Li, Srinivasan Iyer, Jingfei Du, Patrick S. H. Lewis, William Yang Wang, Yashar Mehdad, Wen-tau Yih, Sebastian Riedel, Douwe Kiela, Barlas Oguz:
Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval. CoRR abs/2009.12756 (2020) - [i10]Belinda Z. Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, Wen-tau Yih:
Efficient One-Pass End-to-End Entity Linking for Questions. CoRR abs/2010.02413 (2020) - [i9]Srinivasan Iyer, Sewon Min, Yashar Mehdad, Wen-tau Yih:
RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering. CoRR abs/2010.10757 (2020) - [i8]Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Robin Jia, Yashar Mehdad, Srinivasan Iyer:
Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA. CoRR abs/2012.15075 (2020) - [i7]Kushal Lakhotia, Bhargavi Paranjape, Asish Ghoshal, Wen-tau Yih, Yashar Mehdad, Srinivasan Iyer:
FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation. CoRR abs/2012.15482 (2020)
2010 – 2019
- 2019
- [b1]Srinivasan Iyer:
Learning to Map Natural Language to General Purpose Source Code. University of Washington, USA, 2019 - [c8]Srinivasan Iyer, Alvin Cheung, Luke Zettlemoyer:
Learning Programmatic Idioms for Scalable Semantic Parsing. EMNLP/IJCNLP (1) 2019: 5425-5434 - [c7]Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer:
JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation. EMNLP/IJCNLP (1) 2019: 5435-5445 - [i6]Srinivasan Iyer, Alvin Cheung, Luke Zettlemoyer:
Learning Programmatic Idioms for Scalable Semantic Parsing. CoRR abs/1904.09086 (2019) - [i5]Rajas Agashe, Srinivasan Iyer, Luke Zettlemoyer:
JuICe: A Large Scale Distantly Supervised Dataset for Open Domain Context-based Code Generation. CoRR abs/1910.02216 (2019) - 2018
- [c6]Matt Gardner, Pradeep Dasigi, Srinivasan Iyer, Alane Suhr, Luke Zettlemoyer:
Neural Semantic Parsing. ACL (5) 2018: 17-18 - [c5]Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer:
Mapping Language to Code in Programmatic Context. EMNLP 2018: 1643-1652 - [c4]Alane Suhr, Srinivasan Iyer, Yoav Artzi:
Learning to Map Context-Dependent Sentences to Executable Formal Queries. NAACL-HLT 2018: 2238-2249 - [i4]Alane Suhr, Srinivasan Iyer, Yoav Artzi:
Learning to Map Context-Dependent Sentences to Executable Formal Queries. CoRR abs/1804.06868 (2018) - [i3]Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer:
Mapping Language to Code in Programmatic Context. CoRR abs/1808.09588 (2018) - 2017
- [c3]Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, Luke Zettlemoyer:
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. ACL (1) 2017: 146-157 - [c2]Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, Luke Zettlemoyer:
Learning a Neural Semantic Parser from User Feedback. ACL (1) 2017: 963-973 - [i2]Ioannis Konstas, Srinivasan Iyer, Mark Yatskar, Yejin Choi, Luke Zettlemoyer:
Neural AMR: Sequence-to-Sequence Models for Parsing and Generation. CoRR abs/1704.08381 (2017) - [i1]Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, Luke Zettlemoyer:
Learning a Neural Semantic Parser from User Feedback. CoRR abs/1704.08760 (2017) - 2016
- [c1]Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Luke Zettlemoyer:
Summarizing Source Code using a Neural Attention Model. ACL (1) 2016
Coauthor Index
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