Singh, Sameer

"Why Should I Trust You?": Explaining the Predictions of Any Classifier

Ribeiro, M. T., Singh, S., & Guestrin, C. (2016) · Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine Learning

Cited by 17,555

“Why Should I Trust You?”: Explaining the Predictions of Any Classifier

Ribeiro, M., Singh, S., & Guestrin, C. (2016) · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 6,682

Anchors: High-Precision Model-Agnostic Explanations

Ribeiro, M. T., Singh, S., & Guestrin, C. (2018) · Proceedings of the AAAI Conference on Artificial Intelligence

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 2,162

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

Shin, T., Razeghi, Y., Logan IV, R. L., Wallace, E., & Singh, S. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 1,279

Beyond Accuracy: Behavioral Testing of NLP models with CheckList

Ribeiro, M. T., Wu, T., Guestrin, C., & Singh, S. (2020) · arXiv

Software Testing and Debugging TechniquesTopic Modeling

Cited by 901

Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods

Slack, D., Hilgard, S., Jia, E., Singh, S., & Lakkaraju, H. (2020) · Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society

Explainable Artificial Intelligence (XAI)Adversarial Robustness in Machine Learning

Cited by 900

Beyond accuracy: behavioral testing of NLP models with CheckList

Ribeiro, M. T., Wu, T., Guestrin, C., & Singh, S. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Software Testing and Debugging TechniquesTopic Modeling

Cited by 890

Model-Agnostic Interpretability of Machine Learning

Ribeiro, M. T., Singh, S., & Guestrin, C. (2016) · arXiv

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 699

Knowledge Enhanced Contextual Word Representations

Peters, M. E., Neumann, M., Logan, R., Schwartz, R., Joshi, V., Singh, S., & Smith, N. A. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 661

Universal Adversarial Triggers for Attacking and Analyzing NLP

Wallace, E., Feng, S., Kandpal, N., Gardner, M., & Singh, S. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 642

Calibrate Before Use: Improving Few-Shot Performance of Language Models

Zhao, T. Z., Wallace, E., Feng, S., Klein, D., & Singh, S. (2021) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 513

Generating Natural Adversarial Examples

Zhao, Z., Dua, D., & Singh, S. (2017) · arXiv

Adversarial Robustness in Machine LearningSoftware Testing and Debugging Techniques

Cited by 508

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Dua, D., Wang, Y., Dasigi, P., Stanovsky, G., Singh, S., & Gardner, M. (2019) · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 393

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs

Dua, D., Wang, Y., Dasigi, P., Stanovsky, G., Singh, S., & Gardner, M. (2019) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 238

Do NLP Models Know Numbers? Probing Numeracy in Embeddings

Wallace, E., Wang, Y., Li, S., Singh, S., & Gardner, M. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

Topic ModelingNatural Language Processing Techniques

Cited by 227

Barack’s Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling

Logan, R., Liu, N. F., Peters, M. E., Gardner, M., & Singh, S. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingNatural Language Processing Techniques

Cited by 168

Interpretation of Natural Language Rules in Conversational Machine Reading

Saeidi, M., Bartolo, M., Lewis, P., Singh, S., Rocktäschel, T., Sheldon, M., Bouchard, G., & Riedel, S. (2018) · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 141

Compositional Questions Do Not Necessitate Multi-hop Reasoning

Min, S., Wallace, E., Singh, S., Gardner, M., Hajishirzi, H., & Zettlemoyer, L. (2019) · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics

Topic ModelingInformation Retrieval and Search Behavior

Cited by 138

Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models

Logan IV, R., Balazevic, I., Wallace, E., Petroni, F., Singh, S., & Riedel, S. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 133

Explaining machine learning models with interactive natural language conversations using TalkToModel

Slack, D., Krishna, S., Lakkaraju, H., & Singh, S. (2023) · Nature Machine Intelligence

Explainable Artificial Intelligence (XAI)Software Testing and Debugging Techniques

Cited by 125

AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models

Wallace, E., Tuyls, J., Wang, J., Subramanian, S., Gardner, M., & Singh, S. (2019) · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP): System Demonstrations

Explainable Artificial Intelligence (XAI)Topic Modeling

Cited by 116

Concealed Data Poisoning Attacks on NLP Models

Wallace, E., Zhao, T., Feng, S., & Singh, S. (2021) · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Adversarial Robustness in Machine LearningPrivacy-Preserving Technologies in Data

Cited by 115

Evaluating Question Answering Evaluation

Chen, A., Stanovsky, G., Singh, S., & Gardner, M. (2019) · Proceedings of the 2nd Workshop on Machine Reading for Question Answering

Topic ModelingNatural Language Processing Techniques

Cited by 105

Entity-Based Knowledge Conflicts in Question Answering

Longpre, S., Perisetla, K., Chen, A., Ramesh, N., DuBois, C., & Singh, S. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingMultimodal Machine Learning Applications

Cited by 101