Sameer Singh

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Carlos GuestrinProfessor, Stanford UniversityVerified email at stanford.edu
Marco Tulio RibeiroGoogle DeepMindVerified email at cs.washington.edu
Matt GardnerScaled CognitionVerified email at scaledcognition.com
Robert L Logan IVUC IrvineVerified email at uci.edu
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Eric WallaceUC BerkeleyVerified email at berkeley.edu
Sebastian RiedelHonorary Professor @ University College London, Researcher @ DeepMindVerified email at cs.ucl.ac.uk
Dheeru DuaUniversity of California, IrvineVerified email at uci.edu
Dylan SlackUC IrvineVerified email at uci.edu
Himabindu LakkarajuAssistant Professor, Harvard UniversityVerified email at seas.harvard.edu
Tim RocktäschelProfessor of Artificial Intelligence at UCL, Open-Endedness Team Lead at Google DeepMindVerified email at cs.ucl.ac.uk
Yasaman RazeghiUniversity of California, IrvineVerified email at uci.edu
Shi FengUniversity of ChicagoVerified email at uchicago.edu
Pouya PezeshkpourUniversity of California, IrvineVerified email at uci.edu
Nitish GuptaResearch Scientist, Google AIVerified email at google.com
Michael WickUniversity of MassachusettsVerified email at cs.umass.edu
Tony Z. ZhaoStanford UniversityVerified email at stanford.edu
Noah A. SmithUniversity of Washington; Allen Institute for Artificial IntelligenceVerified email at cs.washington.edu
Yoshitomo MatsubaraAmazon Alexa AIVerified email at uci.edu
Matthew E PetersSr Research Scientist, Allen Institute for Artificial IntelligenceVerified email at allenai.org

Sameer Singh

Associate Professor, University of California Irvine

Verified email at uci.edu - Homepage

Interpretability and Robustness Information Extraction Natural Language Processing Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
"Why Should I Trust You?": Explaining the Predictions of Any Classifier MT Ribeiro, S Singh, C Guestrin Knowledge Discovery and Data Mining (KDD), 2016	15291	2016
Anchors: High-precision model-agnostic explanations MT Ribeiro, S Singh, C Guestrin Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	1970	2018
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts T Shin, Y Razeghi, RL Logan IV, E Wallace, S Singh Empirical Methods in Natural Language Processing (EMNLP), 2020	1007	2020
Model-Agnostic Interpretability of Machine Learning MT Ribeiro, S Singh, C Guestrin ICML 2016 Workshop on Human Interpretability in Machine Learning, 2016	1000	2016
Beyond Accuracy: Behavioral Testing of NLP Models with CheckList MT Ribeiro, T Wu, C Guestrin, S Singh arXiv preprint arXiv:2005.04118, 2020	834	2020
Knowledge enhanced contextual word representations ME Peters, M Neumann, RL Logan IV, R Schwartz, V Joshi, S Singh, ... arXiv preprint arXiv:1909.04164, 2019	666	2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods D Slack, S Hilgard, E Jia, S Singh, H Lakkaraju Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 180-186, 2020	660	2020
DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs D Dua, Y Wang, P Dasigi, G Stanovsky, S Singh, M Gardner Annual Conference of the North American Chapter of the Association for …, 2019	636	2019
Universal Adversarial Triggers for Attacking and Analyzing NLP E Wallace, S Feng, N Kandpal, M Gardner, S Singh Empirical Methods in Natural Language Processing (EMNLP), 2019	627	2019
Calibrate before use: Improving few-shot performance of language models Z Zhao, E Wallace, S Feng, D Klein, S Singh International Conference on Machine Learning, 12697-12706, 2021	617	2021
Generating Natural Adversarial Examples Z Zhao, D Dua, S Singh International Conference on Learning Representations (ICLR), 2018	615	2018
Semantically Equivalent Adversarial Rules for Debugging NLP Models MT Ribeiro, S Singh, C Guestrin Annual Meeting of the Association for Computational Linguistics (ACL), 2018	456	2018
Evaluating models’ local decision boundaries via contrast sets M Gardner, Y Artzi, V Basmov, J Berant, B Bogin, S Chen, P Dasigi, D Dua, ... Proceedings of the 2020 Conference on Empirical Methods in Natural Language …, 2020	389	2020
Injecting logical background knowledge into embeddings for relation extraction T Rocktäschel, S Singh, S Riedel Proceedings of the 2015 Human Language Technology Conference of the North …, 2015	290	2015
Factorie: Probabilistic programming via imperatively defined factor graphs A McCallum, K Schultz, S Singh Advances in Neural Information Processing Systems 22, 1249-1257, 2009	284	2009
Entity linking via joint encoding of types, descriptions, and context N Gupta, S Singh, D Roth Proceedings of the 2017 Conference on Empirical Methods in Natural Language …, 2017	249	2017
Design challenges for entity linking X Ling, S Singh, DS Weld Transactions of the Association for Computational Linguistics 3, 315-328, 2015	248	2015
Do NLP Models Know Numbers? Probing Numeracy in Embeddings E Wallace, Y Wang, S Li, S Singh, M Gardner arXiv preprint arXiv:1909.07940, 2019	235	2019
Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling RL Logan IV, NF Liu, ME Peters, M Gardner, S Singh Proceedings of the 2019 Conference of the Association for Computational …, 2019	198	2019
COVIDLIES: Detecting COVID-19 Misinformation on Social Media T Hossain, RL Logan IV, A Ugarte, Y Matsubara, S Young, S Singh Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020, 2020	184	2020

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