This page lists most of our publications and preprints since 2015. (It includes a few non-paper citations, like invited talks or edited volumes.) Papers are also available from the personal websites of lab members.

2022

  1. AAAI
    An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity
    Siddhartha Mishra, Nicholas Monath, Michael Boratko, Ariel Kobren, and Andrew McCallum
    Proceedings of the AAAI Conference on Artificial Intelligence, 2022
  2. AAAI
    Sublinear Time Approximation of Text Similarity Matrices
    Archan Ray, Nicholas Monath, Andrew McCallum, and Cameron Musco
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2022
  3. ACL
    Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings
    Shib Dasgupta, Michael Boratko, Siddhartha Mishra, Shriya Atmakuri, Dhruvesh Patel, Xiang Li, and Andrew McCallum
    In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
  4. ACL
    Event-Event Relation Extraction using Probabilistic Box Embedding
    EunJeong Hwang, Jay-Yoon Lee, Tianyi Yang, Dhruvesh Patel, Dongxu Zhang, and Andrew McCallum
    In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022
  5. ACL
    Softmax Bottleneck Makes Language Models Unable to Represent Multi-mode Word Distributions
    In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022
  6. ACL
    RELiC: Retrieving Evidence for Literary Claims
    In Association of Computational Linguistics, 2022
  7. EMNLP
    RankGen: Improving Text Generation with Large Ranking Models
    Kalpesh Krishna, Yapei Chang, John Wieting, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2022
  8. EMNLP
    Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation
    Tu Vu, Aditya Barua, Brian Lester, Daniel Cer, Mohit Iyyer, and Noah Constant
    In Empirical Methods in Natural Language Processing, 2022
  9. EMNLP
    Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature
    Katherine Thai, Marzena Karpinska, Kalpesh Krishna, William Ray, Moira Inghilleri, John Wieting, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2022
  10. EMNLP
    SLING: Sino Linguistic Evaluation of Large Language Models
    Yixiao Song, Kalpesh Krishna, Rajesh Bhatt, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2022
  11. EMNLP
    DEMETR: Diagnosing Evaluation Metrics for Translation
    Marzena Karpinska, Nishant Raj, Katherine Thai, Yixiao Song, Ankita Gupta, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2022
  12. EMNLP
    Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization
    Nishant Yadav, Nicholas Monath, Rico Angell, Manzil Zaheer, and Andrew McCallum
    In Empirical Methods in Natural Language Processing, 2022
  13. EMNLP-Findings
    You can’t pick your neighbors, or can you? When and How to Rely on Retrieval in the KNN-LM
    Andrew Drozdov, Shufan Wang, Razieh Rahimi, Andrew McCallum, Hamed Zamani, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2022
  14. Field Matters
    Corpus-Guided Contrast Sets for Morphosyntactic Feature Detection in Low-Resource English Varieties
    In Proceedings of the 1st Field Matters Workshop on NLP Applications to Field Linguistics, 2022
  15. ICML
    Knowledge base question answering by case-based reasoning over subgraphs
    Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi, Robin Jia, and Andrew McCallum
    In International Conference on Machine Learning, 2022
  16. ICML
    Interactive Correlation Clustering with Existential Cluster Constraints
    In International Conference on Machine Learning, 2022
  17. NAACL
    Entity Linking via Explicit Mention-Mention Coreference Modeling
    Dhruv Agarwal, Rico Angell, Nicholas Monath, and Andrew McCallum
    In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
  18. NAACL
    DISAPERE: A Dataset for Discourse Structure in Peer Review Discussions
    Neha Kennard, Tim O’Gorman, Rajarshi Das, Akshay Sharma, Chhandak Bagchi, Matthew Clinton, Pranay Kumar Yelugam, Hamed Zamani, and Andrew McCallum
    In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022
  19. NAACL
    Modeling Exemplification in Long-form Question Answering via Retrieval
    Shufan Wang, Fangyuan Xu, Laure Thompson, Eunsol Choi, and Mohit Iyyer
    In North American Association for Computational Linguistics, 2022
  20. NAACL
    ChapterBreak: A Challenge Dataset for Long-Range Language Models
    In North American Association for Computational Linguistics, 2022
  21. Negative Results
    How Much Do Modifications to Transformer Language Models Affect Their Ability to Learn Linguistic Knowledge?
    In Workshop on Insights from Negative Results in NLP @ ACL 2022, 2022
  22. TIIS
    ClioQuery: Interactive Query-Oriented Text Analytics for Comprehensive Investigation of Historical News Archives
    Abram Handler, Narges Mahyar, and Brendan O’Connor
    ACM Trans. Interact. Intell. Syst., 2022

2021

  1. AAAI
    Extending Multi-Sense Word Embedding to Phrases and Sentences for Unsupervised Semantic Applications
    Haw-Shiuan Chang, Amol Agrawal, and Andrew McCallum
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2021
  2. ACL
    Energy-Based Reranking: Improving Neural Machine Translation Using Energy-Based Models.
    Sumanta Bhattacharyya, Pedram Rooshenas, Subhajit Naskar, Simeng Sun, Mohit Iyyer, and Andrew McCallum
    In Association for Computational Linguistics, 2021
  3. ACL Findings
    Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence
    In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021
  4. Causal NLP
    Text as Causal Mediators: Research Design for Causal Estimates of Differential Treatment of Social Groups via Language Aspects
    Katherine Keith, Douglas Rice, and Brendan O’Connor
    In Proceedings of the First Workshop on Causal Inference and NLP, 2021
  5. EACL
    Changing the Mind of Transformers for Topically-Controllable Language Generation
    In Conference of the European Chapter of the Association for Computational Linguistics (EACL) (Oral), 2021
  6. EACL
    Multi-facet Universal Schema
    Rohan Paul*, Haw-Shiuan Chang*, and Andrew McCallum
    In Conference of the European Chapter of the Association for Computational Linguistics (EACL) (Oral), 2021
  7. EMNLP
    Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP
    Trapit Bansal, Karthick Prasad Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, and Andrew McCallum
    In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021
  8. EMNLP
    Making Better Use of Unlabeled Data with Task Augmentation and Self-training
    Tu Vu, Thang Luong, Quoc Le, Grady Simon, and Mohit Iyyer
    In forthcoming EMNLP, 2021
  9. EMNLP
    Case-based Reasoning for Natural Language Questions over Knowledge Bases
    Rajarshi Das, Manzil Zaheer, Dung Thai, Ameya Godbole, Ethan Perez, Jay-Yoon Lee, Liz Tan, Lazaros Polymenakos, and Andrew McCallum
    In forthcoming EMNLP, 2021
  10. EMNLP
    Open Aspect Target Sentiment Classification with Natural Language Prompts
    Ronald Seoh, Ian Birle, Mrinal Tak, Haw-Shiuan Chang, Brian Pinette, and Alfred Hough
    In forthcoming EMNLP, 2021
  11. EMNLP
    Diverse Distributions of Self-Supervised Tasks for Meta-Learning in NLP
    Trapit Bansal, Karthick Gunasekaran, Tong Wang, Tsendsuren Munkhdalai, and Andrew McCallum
    In forthcoming EMNLP, 2021
  12. EMNLP
    MS-Mentions: Consistently Annotating Entity Mentions in Materials Science Procedural Text
    Tim O’Gorman, Zach Jensen, Sheshera Mysore, Kevin Huang, Rubayyat Mahbub, Elsa Olivetti, and Andrew McCallum
    In forthcoming EMNLP, 2021
  13. EMNLP
    Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints
    Zichao Wang, Richard Baraniuk, and Andrew Lan
    In forthcoming EMNLP, 2021
  14. EMNLP
    Phrase-BERT: Improved Phrase Embeddings from BERT with an Application to Corpus Exploration
    In forthcoming EMNLP, 2021
  15. EMNLP
    Improved Latent Tree Induction with Distant Supervision via Span Constraints
    Zhiyang Xu, Andrew Drozdov, Jay Yoon Lee, Tim O’Gorman, Subendhu Rongali, Dylan Finkbeiner, Shilpa Suresh, Mohit Iyyer, and Andrew McCallum
    In forthcoming EMNLP, 2021
  16. EMNLP
    IGA: An Intent-Guided Authoring Assistant
    Simeng Sun, Wenlong Zhao, Varun Manjunatha, Rajiv Jain, Vlad Morariu, Franck Dernoncourt, Balaji Vasan Srinivasan, and Mohit Iyyer
    In forthcoming EMNLP, 2021
  17. EMNLP
    Do Long-Range Language Models Actually Use Long-Range Context?
    Simeng Sun, Kalpesh Krishna, Andrew Mattarella-Micke, and Mohit Iyyer
    In forthcoming EMNLP, 2021
  18. EMNLP
    The Perils of Using Mechanical Turk to Evaluate Open-Ended Text Generation
    Marzena Karpinska, Nader Akoury, and Mohit Iyyer
    In forthcoming EMNLP, 2021
  19. EMNLP demo
    Box Embeddings: An open-source library for representation learning using geometric structures
    Tejas Chheda, Purujit Goyal, Trang Tran, Dhruvesh Patel, Michael Boratko, Shib Sankar Dasgupta, and Andrew McCallum
    In forthcoming EMNLP demo, 2021
  20. Find. of ACL
    Predicting In-Hospital Mortality by Combining Clinical Notes with Time-Series Data.
    Iman Deznabi, Mohit Iyyer, and Madalina Fiterau
    In Findings of the Association for Computational Linguistics, 2021
  21. Find. of ACL
    Corpus-Level Evaluation for Event QA: The IndiaPoliceEvents Corpus Covering the 2002 Gujarat Violence
    In Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, 2021
  22. NAACL
    Hurdles to Progress in Long-form Question Answering
    Kalpesh Krishna, Aurko Roy, and Mohit Iyyer
    In North American Association for Computational Linguistics, 2021
  23. NAACL
    TABBIE: Pretrained Representations of Tabular Data
    Hiroshi Iida, June Thai, Varun Manjunatha, and Mohit Iyyer
    In North American Association for Computational Linguistics, 2021
  24. NAACL
    Revisiting Simple Neural Probabilistic Language Models
    In North American Association for Computational Linguistics, 2021
  25. NeurIPS
    Capacity and Bias of Learned Geometric Embeddings for Directed Graphs
    Michael Boratko, Dongxu Zhang, Nicholas Monath, Luke Vilnis, Kenneth L Clarkson, and Andrew McCallum
    Advances in Neural Information Processing Systems, 2021
  26. UAI
    Exact and approximate hierarchical clustering using A
    Craig S Greenberg, Sebastian Macaluso, Nicholas Monath, Avinava Dubey, Patrick Flaherty, Manzil Zaheer, Amr Ahmed, Kyle Cranmer, and Andrew McCallum
    In Uncertainty in Artificial Intelligence, 2021
  27. UAI
    Min/max stability and box distributions
    Michael Boratko, Javier Burroni, Shib Sankar Dasgupta, and Andrew McCallum
    In Uncertainty in Artificial Intelligence, 2021
  28. UnImplicit
    Challenges in Detecting Null Relativizers in African American Language for Sociolinguistic and Psycholinguistic Applications
    Unpublished abstract presented at UnImplicit: The First Workshop on Understanding Implicit and Underspecified Language at ACL-IJCNLP, 2021

2020

  1. AAAI
    Simultaneously linking entities and extracting relations from biomedical text without mention-level supervision
    Trapit Bansal, Pat Verga, Neha Choudhary, and Andrew McCallum
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2020
  2. ACL
    Hard-Coded Gaussian Attention for Neural Machine Translation
    Weiqiu You, Simeng Sun, and Mohit Iyyer
    In Association for Computational Linguistics, 2020
  3. ACL
    Text and Causal Inference: A Review of Using Text to Remove Confounding from Causal Estimates
    In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020
  4. CLEF
    Unsupervised Pre-training for Biomedical Question Answering
    Vaishnavi Kommaraju, Karthick Gunasekaran, Kun Li, Trapit Bansal, Andrew McCallum, Ivana Williams, and Ana-Maria Istrate
    In CLEF (Working Notes), 2020
  5. COLING
    Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks
    Trapit Bansal, Rishikesh Jha, and Andrew McCallum
    In Proceedings of the 28th International Conference on Computational Linguistics, 2020
  6. ECIR
    Weakly-Supervised Open-Retrieval Conversational Question Answering
    Chen Qu, Liu Yang, Cen Chen, W. Bruce Croft, Kalpesh Krishna, and Mohit Iyyer
    In European Conference on Information Retrieval, 2020
  7. EMNLP
    Self-Supervised Meta-Learning for Few-Shot Natural Language Classification Tasks
    Trapit Bansal, Rishikesh Jha, Tsendsuren Munkhdalai, and Andrew McCallum
    In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020
  8. EMNLP
    Exploring and Predicting Transferability across NLP Tasks
    Tu Vu, Tong Wang, Tsendsuren Munkhdalai, Alessandro Sordoni, Adam Trischler, Andrew Mattarella-Micke, Subhransu Maji, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2020
  9. EMNLP
    Reformulating Unsupervised Style Transfer as Paraphrase Generation
    Kalpesh Krishna, John Wieting, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2020
  10. EMNLP
    STORIUM: A Dataset and Evaluation Platform for Machine-in-the-Loop Story Generation
    Nader Akoury, Shufan Wang, Josh Whiting, Stephen Hood, Nanyun Peng, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2020
  11. EMNLP
    Unsupervised Parsing with S-DIORA: Single Tree Encoding for Deep Inside-Outside Recursive Autoencoders
    Andrew Drozdov, Subendhu Rongali, Yi-Pei Chen, Tim O’Gorman, Mohit Iyyer, and Andrew McCallum
    In Empirical Methods in Natural Language Processing, 2020
  12. ICLR
    Thieves on Sesame Street! Model Extraction of BERT-based APIs.
    Kalpesh Krishna, Gaurav Singh Tomar, Ankur Parikh, Nicolas Papernot, and Mohit Iyyer
    In International Conference on Learning Representations, 2020
  13. LREC
    Which Evaluations Uncover Sense Representations that Actually Make Sense?
    Fenfei Guo, Jordan Boyd-Graber, Mohit Iyyer, and Leah Findlater
    In Language Resources and Evaluation Conference, 2020
  14. ML
    Using Error Decay Prediction to Overcome Practical Issues of Deep Active Learning for Named Entity Recognition
    Haw-Shiuan Chang, Shankar Vembu, Sunil Mohan, Rheeya Uppaal, and Andrew McCallum
    Machine Learning, 2020
  15. NLP+CSS
    Analyzing Gender Bias within Narrative Tropes
    Dhruvil Gala, Mohammad Omar Khursheed, Hannah Lerner, Brendan O’Connor, and Mohit Iyyer
    In Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, 2020
  16. NLP+CSS
    Uncertainty over Uncertainty: Investigating the Assumptions, Annotations, and Text Measurements of Economic Policy Uncertainty
    Katherine Keith, Christoph Teichmann, Brendan O’Connor, and Edgar Meij
    In Proceedings of the Fourth Workshop on Natural Language Processing and Computational Social Science, 2020
  17. SIGIR
    Open-Retrieval Conversational Question Answering
    Chen Qu, Liu Yang, Cen Chen, Minghui Qiu, W. Bruce Croft, and Mohit Iyyer
    In 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2020
  18. arXiv
    Topic Modeling with Contextualized Word Representation Clusters
    Laure Thompson and David Mimno
    arXiv preprint arXiv:2010.12626, 2020

2019

  1. ACL
    Optimal Transport-based Alignment of Learned Character Representations for String Similarity
    Derek Tam, Nicholas Monath, Ari Kobren, Aaron Traylor, Rajarshi Das, and Andrew McCallum
    In Association of Computational Linguistics (ACL), 2019
  2. ACL
    A2N: Attending to Neighbors for Knowledge Graph Inference
    Trapit Bansal, Da-Cheng Juan, Sujith Ravi, and Andrew McCallum
    In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019
  3. ACL
    Syntactically Supervised Transformers for Faster Neural Machine Translation
    In Association for Computational Linguistics, 2019
  4. ACL
    Generating Question-Answer Hierarchies
    In Association for Computational Linguistics, 2019
  5. ACL
    Encouraging Paragraph Embeddings to Remember Sentence Identity Improves Classification
    In Association for Computational Linguistics, 2019
  6. AKBC
    Integrating User Feedback under Identity Uncertainty in Knowledge Base Construction
    Ari Kobren, Nicholas Monath, and Andrew McCallum
    In Automated Knowledge Base Construction (AKBC), 2019
  7. CIKM
    Attentive History Selection for Conversational Question Answering
    Chen Qu, Liu Yang, Minghui Qiu, Yongfeng Zhang, Cen Chen, W. Bruce Croft, and Mohit Iyyer
    In Conference on Information and Knowledge Management, 2019
  8. EMNLP
    Investigating Sports Commentator Bias within a Large Corpus of American Football Broadcasts.
    In Empirical Methods in Natural Language Processing, 2019
  9. EMNLP
    Unsupervised Labeled Parsing with Deep Inside-Outside Recursive Autoencoders
    In Empirical Methods in Natural Language Processing, 2019
  10. EMNLP
    Query-focused Sentence Compression in Linear Time
    In Proceedings of EMNLP, 2019
  11. ICLR
    Multi-step Retriever-Reader Interaction for Scalable Open-domain Question Answering
    Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum
    In International Conference on Learning Representations (ICLR), 2019
  12. ICLR
    Building Dynamic Knowledge Graphs from Text using Machine Reading Comprehension
    Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, and Andrew McCallum
    In International Conference on Learning Representations (ICLR), 2019
  13. ICLR
    Smoothing the Geometry of Box Embeddings
    In International Conference on Learning Representations (ICLR) (Oral), 2019
  14. ICML
    Supervised Hierarchical Clustering with Exponential Linkage
    In International Conference on Machine Learning (ICML), 2019
  15. KDD
    Scalable Hierarchical Clustering with Tree Grafting
    Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, Michael Glass, and Andrew McCallum
    In International Conference on Knowledge Discovery and Data Mining (KDD), 2019
  16. KDD
    Paper Matching with Local Fairness Constraints
    Ari Kobren, Barna Saha, and Andrew McCallum
    In International Conference on Knowledge Discovery and Data Mining (KDD), 2019
  17. KDD
    Gradient-based Hierarchical Clustering using Continuous Representations of Trees in Hyperbolic Space
    Nicholas Monath, Manzil Zaheer, Daniel Silva, Andrew McCallum, and Amr Ahmed
    In International Conference on Knowledge Discovery and Data Mining (KDD), 2019
  18. LA+ACL
    The Materials Science Procedural Text Corpus: Annotating Materials Synthesis Procedures with Shallow Semantic Structures
    Sheshera Mysore, Zach Jensen, Edward Kim, Kevin Huang, Haw-Shiuan Chang, Emma Strubell, Jeffrey Flanigan, Andrew McCallum, and Elsa Olivetti
    In Proceedings of the 13th Linguistic Annotation Workshop at ACL, 2019
  19. NAACL
    OpenKI: Integrating Open Information Extraction and Knowledge Bases with Relation Inference
    Dongxu Zhang, Subhabrata Mukherjee, Colin Lockard, Luna Dong, and Andrew McCallum
    In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (NAACL), 2019
  20. NAACL
    Unsupervised Latent Tree Induction with Deep Inside-Outside Recursive Auto-Encoders
    In North American Association for Computational Linguistics, 2019
  21. NAACL
    Casting Light on Invisible Cities: Computationally Engaging with Literary Criticism
    In North American Association for Computational Linguistics, 2019
  22. SCiL
    Preface: SCiL 2019 Editors’ Note
    Proceedings of the Society for Computation in Linguistics, 2019
  23. SIGIR
    BERT with History Modeling for Conversational Question Answering
    Chen Qu, Liu Yang, Minghui Qiu, W. Bruce Croft, Yongfeng Zhang, and Mohit Iyyer
    In 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019
  24. arXiv
    Human acceptability judgements for extractive sentence compression
    arXiv preprint arXiv:1902.00489, 2019

2018

  1. ACL
    Hierarchical Losses and New Resources for Fine-grained Entity Typing and Linking
    Shikhar Murty*, Patrick Verga*, Luke Vilnis, Irena Radovanovic, and Andrew McCallum (* Equal Contribution)
    In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL) (Oral), 2018
  2. ACL
    Probabilistic Embedding of Knowledge Graphs with Box Lattice Measures
    Luke Vilnis*, Xiang Li*, Shikhar Murty, and Andrew McCallum (* Equal Contribution)
    In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL), 2018
  3. ACL
    Twitter Universal Dependency Parsing for African-American and Mainstream American English
    In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018
  4. BlackboxNLP
    Evaluating Grammaticality in Seq2seq Models with a Broad Coverage HPSG Grammar: A Case Study on Machine Translation
    In Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2018
  5. CIKM WS
    Exploring Summary-Expanded Entity Embeddings for Entity Retrieval
    2018
  6. COLING
    Authorless Topic Models: Biasing Models Away from Known Structure
    Laure Thompson and David Mimno
    In Proceedings of the 27th International Conference on Computational Linguistics, 2018
  7. CoNLL
    Embedded-State Latent Conditional Random Fields for Sequence Labeling
    Dung Thai, Sree Harsha Ramesh, Shikhar Murty, Luke Vilnis, and Andrew McCallum
    In Proceedings of the 22nd Conference on Computational Natural Language Learning (CoNLL), 2018
  8. ECIR
    A Neural Passage Model for Ad-hoc Document Retrieval
    In Advances in Information Retrieval. ECIR 2018 (European Conference on Information Retrieval), 2018
  9. EMNLP
    Linguistically-Informed Self-Attention for Semantic Role Labeling
    Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, and Andrew McCallum
    In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP) (Best paper award), 2018
  10. EMNLP
    Marginal Likelihood Training of BiLSTM-CRF for Biomedical Named Entity Recognition from Disjoint Label Sets
    Nathan Greenberg, Trapit Bansal, Patrick Verga, and Andrew McCallum
    In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing (EMNLP) (Oral), 2018
  11. EMNLP
    QuAC: Question Answering in Context
    Eunsol Choi, He He, Mohit Iyyer, Mark Yatskar, Wen-tau Yih, Yejin Choi, Percy Liang, and Luke Zettlemoyer
    In Empirical Methods in Natural Language Processing, 2018
  12. EMNLP
    Pathologies of Neural Models Make Interpretation Difficult
    Shi Feng, Eric Wallace, Alvin Grissom II, Mohit Iyyer, Pedro Rodriguez, and Jordan Boyd-Graber
    In Empirical Methods in Natural Language Processing, 2018
  13. EMNLP
    Revisiting the Importance of Encoding Logic Rules in Sentiment Classification
    Kalpesh Krishna, Preethi Jyothi, and Mohit Iyyer
    In Empirical Methods in Natural Language Processing, 2018
  14. EMNLP
    Uncertainty-aware generative models for inferring document class prevalence
    In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, 2018
  15. ICLR
    Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning
    Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, and Andrew McCallum
    In International Conference on Learning Representations (ICLR), 2018
  16. NAACL
    Distributional Inclusion Vector Embedding for Unsupervised Hypernymy Detection
    Haw-Shiuan Chang, ZiYun Wang, Luke Vilnis, and Andrew McCallum
    In Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT/NAACL), 2018
  17. NAACL
    Simultaneously Self-attending to All Mentions for Full-Abstract Biological Relation Extraction
    In Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT/NAACL), 2018
  18. NAACL
    Training Structured Prediction Energy Networks with Indirect Supervision
    Amirmohammad Rooshenas, Aishwarya Kamath, and Andrew McCallum
    In Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics (HLT/NAACL) (Oral), 2018
  19. NAACL
    Adversarial Example Generation with Syntactically Controlled Paraphrase Networks
    Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer
    In North American Association for Computational Linguistics, 2018
  20. NAACL
    Deep contextualized word representations
    Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer
    In North American Association for Computational Linguistics, 2018
  21. NAACL
    Learning to Color from Language
    Varun Manjunatha, Mohit Iyyer, Jordan Boyd-Graber, and Larry Davis
    In North American Association for Computational Linguistics, 2018
  22. NAACL
    Relational Summarization for Corpus Analysis
    In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018
  23. NAACL
    Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses
    In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers), 2018
  24. SCiL
    Preface: SCiL 2018 Editors’ Note
    Proceedings of the Society for Computation in Linguistics, 2018
  25. SIGIR
    Exploring Diversification In Non-factoid Question Answering
    Lakshmi Vikraman, W. Bruce Croft, and Brendan O’Connor
    In Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval, 2018
  26. SIGIR
    Understanding the Representational Power of Neural Retrieval Models Using NLP Tasks
    In Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval, 2018
  27. TextGraphs
    Efficient Graph-based Word Sense Induction by Distributional Inclusion Vector Embeddings
    Haw-Shiuan Chang, Amol Agrawal, Ananya Ganesh, Anirudha Desai, Vinayak Mathur, Alfred Hough, and Andrew McCallum
    In TextGraphs-12: the Workshop on Graph-based Methods for Natural Language Processing (NAACL WS), 2018

2017

  1. ACL
    Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
    Rajarshi Das, Manzil Zaheer, Siva Reddy, and Andrew McCallum
    In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL), Vancouver, Canada, July 30 - August 4, Volume 2: Short Papers, 2017
  2. AKBC
    RelNet: End-to-end Modeling of Entities & Relations
    Trapit Bansal, Arvind Neelakantan, and Andrew McCallum
    In 6th Workshop on Automated Knowledge Base Construction (AKBC) 2017 at NIPS, 2017
  3. AKBC
    Learning String Alignments for Entity Aliases
    In 6th Workshop on Automated Knowledge Base Construction (AKBC) 2017 at NIPS, 2017
  4. AKBC
    Entity-centric Attribute Feedback for Interactive Knowledge Bases
    Ari Kobren, Nicholas Monath, and Andrew McCallum
    In 6th Workshop on Automated Knowledge Base Construction (AKBC) 2017 at NIPS, 2017
  5. DISCML
    Gradient-based Hierarchical Clustering
    Nicholas Monath, Ari Kobren, Akshay Krishnamurthy, and Andrew McCallum
    In NIPS Workshop on Discrete Structures in Machine Learning (DISCML) (Oral), 2017
  6. DS+J
    Rookie: summarization and visualization for news archives
    Data Science + Journalism Workshop (DS+J) at KDD, 2017
  7. EACL
    Generalizing to Unseen Entities and Entity Pairs with Row-less Universal Schema
    Patrick Verga, Arvind Neelakantan, and Andrew McCallum
    In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Valencia, Spain, April 3-7, 2017, Volume 1: Long Papers (Oral), 2017
  8. EACL
    Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks
    Rajarshi Das, Arvind Neelakantan, David Belanger, and Andrew McCallum
    In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics (EACL), Valencia, Spain, April 3-7, 2017, Volume 1: Long Papers, 2017
  9. EMNLP
    Fast and Accurate Entity Recognition with Iterated Dilated Convolutions
    In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP), Copenhagen, Denmark, September 9-11, 2017, 2017
  10. EMNLP
    Identifying civilians killed by police with distantly supervised entity-event extraction
    Katherine Keith, Abram Handler, Michael Pinkham, Cara Magliozzi, Joshua McDuffie, and Brendan O’Connor
    In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017
  11. EMNLP
    The strange geometry of skip-gram with negative sampling
    David Mimno and Laure Thompson
    In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017
  12. FAT/ML
    Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American English
    arXiv preprint arXiv:1707.00061. Presented at Fairness, Accountability, and Transparency in Machine Learning workshop at KDD, 2017
  13. ICLR
    Learning a Natural Language Interface with Neural Programmer
    Arvind Neelakantan, Quoc V. Le, Martin Abadi, Andrew McCallum, and Dario Amodei
    In International Conference on Learning Representations (ICLR), 2017
  14. ICML
    End-to-End Learning for Structured Prediction Energy Networks
    David Belanger, Bishan Yang, and Andrew McCallum
    In Proceedings of the 34th International Conference on Machine Learning (ICML), Sydney, NSW, Australia, 6-11 August 2017, 2017
  15. ICML WS
    Low-Rank Hidden State Embeddings for Viterbi Sequence Labeling
    Dung Thai, Shikhar Murty, Trapit Bansal, Luke Vilnis, David Belanger, and Andrew McCallum
    In International Conference on Machine Learning Workshop on Deep Structured Prediction (ICML WS), 2017
  16. ICML WS
    Improved Representation Learning for Predicting Commonsense Ontologies
    Xiang Li, Luke Vilnis, and Andrew McCallum
    In International Conference on Machine Learning Workshop on Deep Structured Prediction (ICML WS), 2017
  17. NIPS
    Active Bias: Training a More Accurate Neural Network by Emphasizing High Variance Samples
    Haw-Shiuan Chang, Erik G. Learned-Miller, and Andrew McCallum
    In Advances in Neural Information Processing Systems (NIPS), 2017
  18. NIPS WS
    Automatically Extracting Action Graphs from Materials Science Synthesis Procedures
    Sheshera Mysore, Edward Kim, Emma Strubell, Ao Liu, Haw-Shiuan Chang, Srikrishna Kompella, Kevin Huang, Andrew McCallum, and Elsa Olivetti
    In Workshop on Machine Learning for Molecules and Materials at NIPS, 2017
  19. NLP+CSS
    Proceedings of the Second Workshop on NLP and Computational Social Science
    Dirk Hovy, Svitlana Volkova, David Bamman, David Jurgens, Brendan O’Connor, Oren Tsur, and A. Seza Doğruöz
    2017
  20. SIGKDD
    A Hierarchical Algorithm for Extreme Clustering
    Ari Kobren, Nicholas Monath, Akshay Krishnamurthy, and Andrew McCallum
    In Proceedings of the 23rd ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD), Halifax, NS, Canada, August 13 - 17, 2017 (Oral), 2017
  21. SPNLP
    Dependency Parsing with Dilated Iterated Graph CNNs
    In Proceedings of the 2nd Workshop on Structured Prediction for Natural Language Processing (SPNLP at EMNLP), Copenhagen, Denmark, September 2017, 2017
  22. SemEval
    SemEval 2017 Task 10: ScienceIE - Extracting Keyphrases and Relations from Scientific Publications
    Isabelle Augenstein, Mrinal Das, Sebastian Riedel, Lakshmi Vikraman, and Andrew McCallum
    In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval at ACL), Vancouver, Canada, August 3-4, 2017, 2017
  23. WNUT
    A Dataset and Classifier for Recognizing Social Media English
    In Proceedings of the 3rd Workshop on Noisy User-generated Text, 2017
  24. WWW
    Learning to Extract Events from Knowledge Base Revisions
    Alexander Konovalov, Benjamin Strauss, Alan Ritter, and Brendan O’Connor
    In Proceedings of the 26th International Conference on World Wide Web, 2017

2016

  1. AKBC
    Row-less Universal Schema
    In Proceedings of the 5th Workshop on Automated Knowledge Base Construction (AKBC at NAACL-HLT), San Diego, CA, USA, June 17, 2016 (Oral), 2016
  2. AKBC
    Incorporating Selectional Preferences in Multi-hop Relation Extraction
    Rajarshi Das, Arvind Neelakantan, David Belanger, and Andrew McCallum
    In Proceedings of the 5th Workshop on Automated Knowledge Base Construction (AKBC at NAACL-HLT), San Diego, CA, USA, June 17, 2016, 2016
  3. AKBC
    Call for Discussion: Building a New Standard Dataset for Relation Extraction Tasks
    Teresa Martin, Fiete Botschen, Ajay Nagesh, and Andrew McCallum
    In Proceedings of the 5th Workshop on Automated Knowledge Base Construction (AKBC at NAACL-HLT), San Diego, CA, USA, June 17, 2016, 2016
  4. CIKM
    Improving Entity Ranking for Keyword Queries
    In Proceedings of CIKM, 2016
  5. EMNLP
    Demographic Dialectal Variation in Social Media: A Case Study of African-American English
    Proceedings of EMNLP, 2016
  6. ICML
    Structured Prediction Energy Networks
    In Proceedings of the 33rd International Conference on Machine Learning (ICML), New York City, NY, USA, June 19-24, 2016, 2016
  7. NAACL
    Multilingual Relation Extraction using Compositional Universal Schema
    In NAACL HLT 2016, The 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (HLT/NAACL), San Diego California, USA, June 12-17, 2016 (Oral), 2016
  8. NLP+CSS
    Proceedings of the First Workshop on NLP and Computational Social Science
    David Bamman, A. Seza Doğruöz, Jacob Eisenstein, Dirk Hovy, David Jurgens, Brendan O’Connor, Alice Oh, Oren Tsur, and Svitlana Volkova
    2016
  9. NLP+CSS
    Bag of what? Simple noun phrase extraction for corpus analysis
    In Proceedings of EMNLP: NLP+CSS: Workshop in Natural Language Processing and Computational Social Science, 2016
  10. RecSys
    Ask the GRU: Multi-task Learning for Deep Text Recommendations
    In Proceedings of the 10th ACM Conference on Recommender Systems (RecSys), Boston, MA, USA, September 15-19, 2016, 2016
  11. TAC/KBP
    Extracting Multilingual Relations under Limited Resources: TAC 2016 Cold-Start KB construction and Slot-Filling using Compositional Universal Schema
    Haw-Shiuan Chang, Abdurrahman Munir, Ao Liu, Johnny Tian-Zheng Wei, Aaron Traylor, Ajay Nagesh, Nicholas Monath, Patrick Verga, Emma Strubell, and Andrew McCallum
    In Text Analysis Conference, Knowledge Base Population (TAC/KBP), 2016
  12. WHI
    Visualizing textual models with in-text and word-as-pixel highlighting
    arXiv:1606.06352 at Workshop on Human Interpretability in Machine Learning, 2016

2015

  1. AAAI-SS
    Compositional Vector Space Models for Knowledge Base Inference
    Arvind Neelakantan, Benjamin Roth, and Andrew McCallum
    In AAAI Spring Symposium Series (AAAI-SS), 2015
  2. AAAI-SS
    Knowledge Representation and Reasoning: Integrating Symbolic and Neural Approaches
    Evgeniy Gabrilovich, Ramanathan Guha, Andrew McCallum, and Kevin Murphy
    In AAAI Spring Symposium Series (AAAI-SS), 2015
  3. ACL
    Compositional Vector Space Models for Knowledge Base Completion
    Arvind Neelakantan, Benjamin Roth, and Andrew McCallum
    In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL), July 26-31, 2015, Beijing, China, Volume 1: Long Papers, 2015
  4. ACL
    Learning Dynamic Feature Selection for Fast Sequential Prediction
    Emma Strubell, Luke Vilnis, Kate Silverstein, and Andrew McCallum
    In Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing (ACL), July 26-31, 2015, Beijing, China, Volume 1: Long Papers (Outstanding Paper Award), 2015
  5. EMNLP
    Posterior calibration and exploratory analysis for natural language processing models
    In Proceedings of EMNLP, 2015
  6. ICLR
    Word Representations via Gaussian Embedding
    Luke Vilnis and Andrew McCallum
    In International Conference on Learning Representations (ICLR) (Oral), 2015
  7. ICTIR
    Embedded Representations of Lexical and Knowledge-Base Semantics
    Andrew McCallum
    In Proceedings of the 2015 International Conference on The Theory of Information Retrieval (ICTIR), Northampton, Massachusetts, USA, September 27-30, 2015, 2015
  8. MPSA
    A Little Bit of NLP Goes A Long Way: Finding Meaning in Legislative Texts with Phrase Extraction
    Midwest Political Science Association (MPSA) 73rd Annual Conference, Chicago (IL), 2015
  9. TAC/KBP
    Building Knowledge Bases with Universal Schema: Cold Start and Slot-Filling Approaches
    In Text Analysis Conference, Knowledge Base Population (TAC/KBP), 2015