Sameer Singh

Orcid: 0000-0003-0621-6323

Affiliations:
  • University of California, Irvine, CA, USA
  • University of Washington, Seattle, WA, USA (2013-2016)
  • University of Massachusetts, Amherst, MA, USA (PhD 2014)
  • Vanderbilt University, Nashville, TN, USA (2004-2007)


According to our database1, Sameer Singh authored at least 167 papers between 2006 and 2024.

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Bibliography

2024
Skill Set Optimization: Reinforcing Language Model Behavior via Transferable Skills.
CoRR, 2024

2023
Explaining machine learning models with interactive natural language conversations using TalkToModel.
Nat. Mac. Intell., August, 2023

Evaluating the generalisability of neural rumour verification models.
Inf. Process. Manag., 2023

Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals.
CoRR, 2023

What's In My Big Data?
CoRR, 2023

EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning.
CoRR, 2023

The Bias Amplification Paradox in Text-to-Image Generation.
CoRR, 2023

Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors.
CoRR, 2023

PURR: Efficiently Editing Language Model Hallucinations by Denoising Language Model Corruptions.
CoRR, 2023

TABLET: Learning From Instructions For Tabular Data.
CoRR, 2023

ART: Automatic multi-step reasoning and tool-use for large language models.
CoRR, 2023

Design Factors of Maestro: A Serious Game for Robust AI Education.
Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Volume 2, 2023

Post Hoc Explanations of Language Models Can Improve Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Do Embodied Agents Dream of Pixelated Sheep: Embodied Decision Making using Language Guided World Modelling.
Proceedings of the International Conference on Machine Learning, 2023

Coverage-based Example Selection for In-Context Learning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

MISGENDERED: Limits of Large Language Models in Understanding Pronouns.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

To Adapt or to Annotate: Challenges and Interventions for Domain Adaptation in Open-Domain Question Answering.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Factual and Informative Review Generation for Explainable Recommendation.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Maestro: A Gamified Platform for Teaching AI Robustness.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
TCAB: A Large-Scale Text Classification Attack Benchmark.
CoRR, 2022

Quantifying Social Biases Using Templates is Unreliable.
CoRR, 2022

TalkToModel: Understanding Machine Learning Models With Open Ended Dialogues.
CoRR, 2022

Learning to Query Internet Text for Informing Reinforcement Learning Agents.
CoRR, 2022

Structurally Diverse Sampling Reduces Spurious Correlations in Semantic Parsing Datasets.
CoRR, 2022

Impact of Pretraining Term Frequencies on Few-Shot Reasoning.
CoRR, 2022

Rethinking Explainability as a Dialogue: A Practitioner's Perspective.
CoRR, 2022

Identifying Adversarial Attacks on Text Classifiers.
CoRR, 2022

BottleFit: Learning Compressed Representations in Deep Neural Networks for Effective and Efficient Split Computing.
Proceedings of the 23rd IEEE International Symposium on a World of Wireless, 2022

FRUIT: Faithfully Reflecting Updated Information in Text.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Continued Pretraining for Better Zero- and Few-Shot Promptability.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Snoopy: An Online Interface for Exploring the Effect of Pretraining Term Frequencies on Few-Shot LM Performance.
Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Structurally Diverse Sampling for Sample-Efficient Training and Comprehensive Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Successive Prompting for Decomposing Complex Questions.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

ReCLIP: A Strong Zero-Shot Baseline for Referring Expression Comprehension.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Combining Feature and Instance Attribution to Detect Artifacts.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Cutting Down on Prompts and Parameters: Simple Few-Shot Learning with Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Zero- and Few-Shot NLP with Pretrained Language Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022

PYLON: A PyTorch Framework for Learning with Constraints.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts.
CoRR, 2021

Modular Framework for Visuomotor Language Grounding.
CoRR, 2021

Feature Attributions and Counterfactual Explanations Can Be Manipulated.
CoRR, 2021

Counterfactual Explanations Can Be Manipulated.
CoRR, 2021

Calibrate Before Use: Improving Few-Shot Performance of Language Models.
CoRR, 2021

Reliable Post hoc Explanations: Modeling Uncertainty in Explainability.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Counterfactual Explanations Can Be Manipulated.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Concealed Data Poisoning Attacks on NLP Models.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

An Empirical Comparison of Instance Attribution Methods for NLP.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Beyond Accuracy: Behavioral Testing of NLP Models with Checklist (Extended Abstract).
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Calibrate Before Use: Improving Few-shot Performance of Language Models.
Proceedings of the 38th International Conference on Machine Learning, 2021

Entity-Based Knowledge Conflicts in Question Answering.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Paired Examples as Indirect Supervision in Latent Decision Models.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Generative Context Pair Selection for Multi-hop Question Answering.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Learning with Instance Bundles for Reading Comprehension.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Competency Problems: On Finding and Removing Artifacts in Language Data.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

What Models Know About Their Attackers: Deriving Attacker Information From Latent Representations.
Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021

Benchmarking Scalable Methods for Streaming Cross Document Entity Coreference.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Enforcing Consistency in Weakly Supervised Semantic Parsing.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Improved Consistency Regularization for GANs.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Customizing Triggers with Concealed Data Poisoning.
CoRR, 2020

How Much Should I Trust You? Modeling Uncertainty of Black Box Explanations.
CoRR, 2020

Image Augmentations for GAN Training.
CoRR, 2020

Evaluating NLP Models via Contrast Sets.
CoRR, 2020

Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-Constrained Edge Computing Systems.
IEEE Access, 2020

Building a Better Lie Detector with BERT: The Difference Between Truth and Lies.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature Attribution.
Proceedings of the 8th International Conference on Learning Representations, 2020

Neural Module Networks for Reasoning over Text.
Proceedings of the 8th International Conference on Learning Representations, 2020

Gradient-based Analysis of NLP Models is Manipulable.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Interpreting Predictions of NLP Models.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts, 2020

MedICaT: A Dataset of Medical Images, Captions, and Textual References.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

COVIDLies: Detecting COVID-19 Misinformation on Social Media.
Proceedings of the 1st Workshop on NLP for COVID-19@ EMNLP 2020, Online, December 2020, 2020

MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020


Revisiting Evaluation of Knowledge Base Completion Models.
Proceedings of the Conference on Automated Knowledge Base Construction, 2020

Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods.
Proceedings of the AIES '20: AAAI/ACM Conference on AI, 2020

Tweeki: Linking Named Entities on Twitter to a Knowledge Graph.
Proceedings of the Sixth Workshop on Noisy User-generated Text, 2020

Obtaining Faithful Interpretations from Compositional Neural Networks.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Beyond Accuracy: Behavioral Testing of NLP Models with CheckList.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

On Importance Sampling-Based Evaluation of Latent Language Models.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Dynamic Sampling Strategies for Multi-Task Reading Comprehension.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Benefits of Intermediate Annotations in Reading Comprehension.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Minecraft as a Platform for Project-Based Learning in AI.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Detecting conversation topics in primary care office visits from transcripts of patient-provider interactions.
J. Am. Medical Informatics Assoc., 2019

ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension.
CoRR, 2019

Explain Your Move: Understanding Agent Actions Using Focused Feature Saliency.
CoRR, 2019

How can we fool LIME and SHAP? Adversarial Attacks on Post hoc Explanation Methods.
CoRR, 2019

Memory Augmented Recursive Neural Networks.
CoRR, 2019

Improving Differentially Private Models with Active Learning.
CoRR, 2019

Universal Adversarial Triggers for NLP.
CoRR, 2019

Analyzing Compositionality in Visual Question Answering.
Proceedings of the Visually Grounded Interaction and Language (ViGIL), 2019

Deep Adversarial Learning for NLP.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

PoMo: Generating Entity-Specific Post-Modifiers in Context.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

GenderQuant: Quantifying Mention-Level Genderedness.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Distilled Split Deep Neural Networks for Edge-Assisted Real-Time Systems.
Proceedings of the 2019 Workshop on Hot Topics in Video Analytics and Intelligent Edges, 2019

Do NLP Models Know Numbers? Probing Numeracy in Embeddings.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

AllenNLP Interpret: A Framework for Explaining Predictions of NLP Models.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Universal Adversarial Triggers for Attacking and Analyzing NLP.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Knowledge Enhanced Contextual Word Representations.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications.
Proceedings of the 1st Conference on Automated Knowledge Base Construction, 2019

Are Red Roses Red? Evaluating Consistency of Question-Answering Models.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Compositional Questions Do Not Necessitate Multi-hop Reasoning.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Barack's Wife Hillary: Using Knowledge Graphs for Fact-Aware Language Modeling.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Comprehensive Multi-Dataset Evaluation of Reading Comprehension.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

Evaluating Question Answering Evaluation.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

2018
A Framework of Rapid Regional Tsunami Damage Recognition From Post-event TerraSAR-X Imagery Using Deep Neural Networks.
IEEE Geosci. Remote. Sens. Lett., 2018

Compact Factorization of Matrices Using Generalized Round-Rank.
CoRR, 2018

Combining Symbolic and Function Evaluation Expressions In Neural Programs.
CoRR, 2018

Mining Knowledge Graphs From Text.
Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Generating Natural Adversarial Examples.
Proceedings of the 6th International Conference on Learning Representations, 2018

Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs.
Proceedings of the 6th International Conference on Learning Representations, 2018

Interpretation of Natural Language Rules in Conversational Machine Reading.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Embedding Multimodal Relational Data for Knowledge Base Completion.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018

Semantically Equivalent Adversarial Rules for Debugging NLP models.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

Anchors: High-Precision Model-Agnostic Explanations.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Relational Learning and Feature Extraction by Querying over Heterogeneous Information Networks.
CoRR, 2017

Semantic compression for edge-assisted systems.
Proceedings of the 2017 Information Theory and Applications Workshop, 2017

Entity Linking via Joint Encoding of Types, Descriptions, and Context.
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

From Reinforcement Learning to Deep Reinforcement Learning: An Overview.
Proceedings of the Braverman Readings in Machine Learning. Key Ideas from Inception to Current State, 2017

Embedding Multimodal Relational Data.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

Multimodal Attribute Extraction.
Proceedings of the 6th Workshop on Automated Knowledge Base Construction, 2017

Intelligent data filtering in constrained IoT systems.
Proceedings of the 51st Asilomar Conference on Signals, Systems, and Computers, 2017

2016
Model-Agnostic Interpretability of Machine Learning.
CoRR, 2016

Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance.
CoRR, 2016

Programs as Black-Box Explanations.
CoRR, 2016

"Why Should I Trust You?": Explaining the Predictions of Any Classifier.
Proceedings of the Demonstrations Session, 2016

Better call Saul: Flexible Programming for Learning and Inference in NLP.
Proceedings of the COLING 2016, 2016

Connotation Frames: A Data-Driven Investigation.
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016

Creating Interactive and Visual Educational Resources for AI.
Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence, 2016

2015
Design Challenges for Entity Linking.
Trans. Assoc. Comput. Linguistics, 2015

Connotation Frames: Typed Relations of Implied Sentiment in Predicate-Argument Structure.
CoRR, 2015

Collectively Embedding Multi-Relational Data for Predicting User Preferences.
CoRR, 2015

Towards Two-Way Interaction with Reading Machines.
Proceedings of the Statistical Language and Speech Processing, 2015

WOLFE: An NLP-friendly Declarative Machine Learning Stack.
Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

Injecting Logical Background Knowledge into Embeddings for Relation Extraction.
Proceedings of the NAACL HLT 2015, The 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Denver, Colorado, USA, May 31, 2015

Towards Combined Matrix and Tensor Factorization for Universal Schema Relation Extraction.
Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, 2015

Efficient Second-Order Gradient Boosting for Conditional Random Fields.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

Towards Extracting Faithful and Descriptive Representations of Latent Variable Models.
Proceedings of the 2015 AAAI Spring Symposia, 2015

On Approximate Reasoning Capabilities of Low-Rank Vector Spaces.
Proceedings of the 2015 AAAI Spring Symposia, 2015

2014
Distributed Non-Parametric Representations for Vital Filtering: UW at TREC KBA 2014.
Proceedings of The Twenty-Third Text REtrieval Conference, 2014

WOLFE: Strength Reduction and Approximate Programming for Probabilistic Programming.
Proceedings of the Statistical Relational Artificial Intelligence, 2014

2013
Anytime Belief Propagation Using Sparse Domains.
CoRR, 2013

Universal Schema for Slot Filling and Cold Start: UMass IESL at TACKBP 2013.
Proceedings of the Sixth Text Analysis Conference, 2013

Dynamic Knowledge-Base Alignment for Coreference Resolution.
Proceedings of the Seventeenth Conference on Computational Natural Language Learning, 2013

A joint model for discovering and linking entities.
Proceedings of the 2013 workshop on Automated knowledge base construction, 2013

Assessing confidence of knowledge base content with an experimental study in entity resolution.
Proceedings of the 2013 workshop on Automated knowledge base construction, 2013

AKBC 2013: third workshop on automated knowledge base construction.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

Joint inference of entities, relations, and coreference.
Proceedings of the 2013 workshop on Automated knowledge base construction, 2013

Automated probabilistic modeling for relational data.
Proceedings of the 22nd ACM International Conference on Information and Knowledge Management, 2013

2012
Compiling Relational Database Schemata into Probabilistic Graphical Models
CoRR, 2012

Monte Carlo MCMC: Efficient Inference by Sampling Factors.
Proceedings of the Joint Workshop on Automatic Knowledge Base Construction and Web-scale Knowledge Extraction, 2012

Monte Carlo MCMC: Efficient Inference by Approximate Sampling.
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012

A Discriminative Hierarchical Model for Fast Coreference at Large Scale.
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, July 8-14, 2012, Jeju Island, Korea, 2012

2011
Large-Scale Cross-Document Coreference Using Distributed Inference and Hierarchical Models.
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, 2011

2010
Distantly Labeling Data for Large Scale Cross-Document Coreference
CoRR, 2010

Constraint-Driven Rank-Based Learning for Information Extraction.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2010

Minimally-Supervised Extraction of Entities from Text Advertisements.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2010

2009
Parallel Large Scale Feature Selection for Logistic Regression.
Proceedings of the SIAM International Conference on Data Mining, 2009

Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009

2007
Common coupling and pointer variables, with application to a Linux case study.
Softw. Qual. J., 2007

Fine-grain analysis of common coupling and its application to a Linux case study.
J. Syst. Softw., 2007

2006
Transfer of Learning for Complex Task Domains: a Demonstration using Multiple Robots.
Proceedings of the 2006 IEEE International Conference on Robotics and Automation, 2006


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