Natural Language Processing

We are interested in a web of problems at the intersection of language, causality, deep learning, and interpretability.

• GenAudit: Fixing Factual Errors in Language Model Outputs with Evidence

  Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron Wallace, Zachary Lipton, Jeffrey Bigham
  arXiv (preprint)

• USB: A Unified Summarization Benchmark Across Tasks and Domains

  Kundan Krishna, Sanjana Ramprasad, Prakhar Gupta, Byron Wallace, Jeffrey Bigham, Zachary Lipton
  EMNLP (Findings)

• Improving the Robustness of Summarization Models by Detecting and Removing Input Noise

  Kundan Krishna, Yao Zhao, Jie Ren, Balaji Lakshminarayanan, Jiaming Luo, Mohammad Saleh, Peter J. Liu
  arXiv (preprint)

• Resolving the Human Subjects Status of Machine Learning's Crowdworkers

  Divyansh Kaushik, Zachary Lipton, Alex John London
  arXiv Preprint

• Practical Benefits of Feature Feedback Under Distribution Shift

  Anurag Katakkar*, Clay Yoo*, Weiqin Wang*, Zachary Lipton, Divyansh Kaushik
  BlackBox NLP workshop

• Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations

  Siddhant Arora*, Danish Pruthi*, Norman Sadeh, William Cohen, Zachary Lipton, Graham Neubig
  Association for the Advancement of Artificial Intelligence (AAAI)

• Does Pretraining for Summarization Require Knowledge Transfer?

  Kundan Krishna, Jeffrey Bigham, Zachary Lipton
  Findings of EMNLP

• Evaluating Explanations: How much do explanations from the teacher aid students?

  Danish Pruthi, Rachit Bansal, Bhuwan Dhingra, Livio Baldini Soares, Michael Collins, Zachary Lipton, Graham Neubig, William Cohen
  Transactions of the Association for Computational Linguistics (TACL)

• On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study

  Divyansh Kaushik, Douwe Kiela, Zachary Lipton, Wen-tau Yih
  Association for Computational Linguistics and International Joint Conference on Natural Language Processing (ACL-IJCNLP)

• The math is not the territory: navigating the free energy principle

  Mel Andrews
  Biology & Philosophy.

• Dynabench: Rethinking Benchmarking in NLP

  Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams
  North American Chapter of the Association for Computational Linguistics (NAACL)

• Do Context-Aware Translation Models Pay the Right Attention?

  Kayo Yin, Patrick Fernandes, Danish Pruthi, Aditi Chaudhary, André F. T. Martins, Graham Neubig
  Association for Computational Linguistics (ACL)

• Generating SOAP Notes from Doctor-Patient Conversations

  Kundan Krishna, Sopan Khosla, Jeffrey Bigham, Jeffrey Bigham
  Association for Computational Linguistics (ACL)

• Decoding and Diversity in Machine Translation

  Nick Roberts, Davis Liang, Graham Neubig, Zachary Lipton
  NeurIPS Resistance AI Workshop

• Weakly and Semisupervised Evidence Extraction

  Danish Pruthi, Bhuwan Dhingra, Graham Neubig, Zachary Lipton
  Findings of EMNLP

• On Negative Interference in Multilingual Models:Findings and A Meta-Learning Treatment

  Zirui Wang, Yulia Tsvetkov, Zachary Lipton
  Empirical Methods in Natural Language Processing (EMNLP)

• Why and when should you pool? Analyzing Pooling in Recurrent Architectures

  Pratyush Maini, Keshav Kolluru, Danish Pruthi, Mausam
  Findings of EMNLP

• NeuSpell: A Neural Spelling Correction Toolkit

  Sai Muralidhar Jayanthi, Danish Pruthi, Graham Neubig
  EMNLP (Demo Track)

• Learning to Deceive with Attention-Based Explanations

  Danish Pruthi, Mansi Gupta, Bhuwan Dhingra, Graham Neubig, Zachary Lipton
  Association for Computational Linguistics (ACL)

• Learning the Difference that Makes a Difference with Counterfactually-Augmented Data

  Divyansh Kaushik, Zachary Lipton
  International Conference on Learning Representations (ICLR)

• Extracting Structured Data from Doctor-Patient Conversations by Predicting Noteworthy Utterances

  Kundan Krishna, Amy Pavel, Benjamin Schloss, Jeffrey Bigham, Zachary Lipton
  AAAI Workshop Health Intelligence

• Practical Obstacles to Deploying Active Learning

  David Lowell, Zachary Lipton, Byron Wallace
  Empirical Methods in Natural Language Processing (EMNLP)

• Entity Projection via Machine Translation for Cross-Lingual NER

  Alankar Jain, Bhargavi Paranjape, Zachary Lipton
  Empirical Methods in Natural Language Processing (EMNLP)

• AmazonQA: A Review-Based Question Answering Task

  Mansi Gupta, Nitish Kulkarni, Raghuveer Chanda, Anirudha Rayasam, Zachary Lipton
  International Joint Conference on Machine Learning (IJCAI)

• Combating Adversarial Misspellings with Robust Word Recognition

  Danish Pruthi, Bhuwan Dhingra, Zachary Lipton
  Association for Computational Linguistics (ACL)

• How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks

  Divyansh Kaushik, Zachary Lipton
  Empirical Methods in Natural Language Processing (EMNLP)

• Deep Bayesian Active Learning for Natural Language Processing: Results of a Large-Scale Empirical Study

  Aditya Siddhant, Zachary Lipton
  Empirical Methods in Natural Language Processing (EMNLP)

• Learning Noise-Invariant Representations for Robust Speech Recognition

  Davis Liang, Zhiheng Huang, Zachary Lipton
  IEEE Speech and Language Technology (SLT)

• Deep Active Learning for Named Entity Recognition

  Yanyao Shen, Hyokun Yun, Zachary Lipton, Anima Anandkumar
  International Conference on Learning Representations (ICLR)

• SPINE: SParse Interpretable Neural Embeddings

  Danish Pruthi*, Anant Subramanian*, Harsh Jhamtani*, Taylor Berg-Kirkpatrick, Eduard Hovy
  Association for the Advancement of Artificial Intelligence (AAAI)

• Efficient exploration for dialogue policy learning with BBQ-networks

  Zachary Lipton, Xiujun Li, Jianfeng Gao, Lihong Li, Li Deng
  Association for the Advancement of Artificial Intelligence (AAAI)