| 2026 | EACL | LLMs Know More About Numbers than They Can Say. | Fengting Yuchi, Li Du, Jason Eisner |
| 2025 | ICLR | Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo. | Joo Loula, Benjamin LeBrun, Li Du, Ben Lipkin, Clemente Pasti, Gabriel Grand, Tianyu Liu, Yahya Emara, Marjorie Freedman, Jason Eisner, Ryan Cotterell, Vikash Mansinghka, Alexander K. Lew, Tim Vieira, Timothy J. O'Donnell |
| 2025 | NAACL | MICE for CATs: Model-Internal Confidence Estimation for Calibrating Agents with Tools. | Nishant Subramani, Jason Eisner, Justin Svegliato, Benjamin Van Durme, Yu Su, Sam Thomson |
| 2024 | ACL | Do Androids Know They're Only Dreaming of Electric Sheep? | Sky CH-Wang, Benjamin Van Durme, Jason Eisner, Chris Kedzie |
| 2024 | ACL | When is a Language Process a Language Model? | Li Du, Holden Lee, Jason Eisner, Ryan Cotterell |
| 2024 | ACL | LLM-Rubric: A Multidimensional, Calibrated Approach to Automated Evaluation of Natural Language Texts. | Helia Hashemi, Jason Eisner, Corby Rosset, Benjamin Van Durme, Chris Kedzie |
| 2024 | ACL | A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia. | Giovanni Monea, Maxime Peyrard, Martin Josifoski, Vishrav Chaudhary, Jason Eisner, Emre Kiciman, Hamid Palangi, Barun Patra, Robert West |
| 2024 | ACL | LLMs in the Imaginarium: Tool Learning through Simulated Trial and Error. | Boshi Wang, Hao Fang, Jason Eisner, Benjamin Van Durme, Yu Su |
| 2024 | EMNLP | Language-to-Code Translation with a Single Labeled Example. | Kaj Bostrom, Harsh Jhamtani, Hao Fang, Sam Thomson, Richard Shin, Patrick Xia, Benjamin Van Durme, Jason Eisner, Jacob Andreas |
| 2024 | EMNLP | Learning to Retrieve Iteratively for In-Context Learning. | Yunmo Chen, Tongfei Chen, Harsh Jhamtani, Patrick Xia, Richard Shin, Jason Eisner, Benjamin Van Durme |
| 2024 | ICML | Principled Gradient-Based MCMC for Conditional Sampling of Text. | Li Du, Afra Amini, Lucas Torroba Hennigen, Xinyan Velocity Yu, Holden Lee, Jason Eisner, Ryan Cotterell |
| 2024 | NAACL | Interpreting User Requests in the Context of Natural Language Standing Instructions. | Nikita Moghe, Patrick Xia, Jacob Andreas, Jason Eisner, Benjamin Van Durme, Harsh Jhamtani |
| 2023 | ACL | A Measure-Theoretic Characterization of Tight Language Models. | Li Du, Lucas Torroba Hennigen, Tiago Pimentel, Clara Meister, Jason Eisner, Ryan Cotterell |
| 2023 | ACL | The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding. | Hao Fang, Anusha Balakrishnan, Harsh Jhamtani, John Bufe, Jean Crawford, Jayant Krishnamurthy, Adam Pauls, Jason Eisner, Jacob Andreas, Dan Klein |
| 2023 | ACL | Toward Interactive Dictation. | Belinda Z. Li, Jason Eisner, Adam Pauls, Sam Thomson |
| 2023 | ACL | Contrastive Decoding: Open-ended Text Generation as Optimization. | Xiang Lisa Li, Ari Holtzman, Daniel Fried, Percy Liang, Jason Eisner, Tatsunori Hashimoto, Luke Zettlemoyer, Mike Lewis |
| 2023 | ACL | Privacy-Preserving Domain Adaptation of Semantic Parsers. | Fatemehsadat Mireshghallah, Yu Su, Tatsunori Hashimoto, Jason Eisner, Richard Shin |
| 2023 | ACL | Efficient Semiring-Weighted Earley Parsing. | Andreas Opedal, Ran Zmigrod, Tim Vieira, Ryan Cotterell, Jason Eisner |
| 2023 | EACL | On the Intersection of Context-Free and Regular Languages. | Clemente Pasti, Andreas Opedal, Tiago Pimentel, Tim Vieira, Jason Eisner, Ryan Cotterell |
| 2023 | EMNLP | Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL. | Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner |
| 2023 | Interspeech | Unsupervised Code-switched Text Generation from Parallel Text. | Jie Chi, Brian Lu, Jason Eisner, Peter Bell, Preethi Jyothi, Ahmed M. Ali |
| 2022 | ACL | Online Semantic Parsing for Latency Reduction in Task-Oriented Dialogue. | Jiawei Zhou, Jason Eisner, Michael Newman, Emmanouil Antonios Platanios, Sam Thomson |
| 2022 | EMNLP | When More Data Hurts: A Troubling Quirk in Developing Broad-Coverage Natural Language Understanding Systems. | Elias Stengel-Eskin, Emmanouil Antonios Platanios, Adam Pauls, Sam Thomson, Hao Fang, Benjamin Van Durme, Jason Eisner, Yu Su |
| 2022 | EMNLP | Algorithms for Acyclic Weighted Finite-State Automata with Failure Arcs. | Anej Svete, Benjamin Dayan, Ryan Cotterell, Tim Vieira, Jason Eisner |
| 2022 | ICLR | Transformer Embeddings of Irregularly Spaced Events and Their Participants. | Hongyuan Mei, Chenghao Yang, Jason Eisner |
| 2021 | EMNLP | Constrained Language Models Yield Few-Shot Semantic Parsers. | Richard Shin, Christopher H. Lin, Sam Thomson, Charles Chen, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, Benjamin Van Durme |
| 2021 | EMNLP | Searching for More Efficient Dynamic Programs. | Tim Vieira, Ryan Cotterell, Jason Eisner |
| 2021 | NAACL | Limitations of Autoregressive Models and Their Alternatives. | Chu-Cheng Lin, Aaron Jaech, Xin Li, Matthew R. Gormley, Jason Eisner |
| 2021 | NAACL | Learning How to Ask: Querying LMs with Mixtures of Soft Prompts. | Guanghui Qin, Jason Eisner |
| 2020 | ACL | A Corpus for Large-Scale Phonetic Typology. | Elizabeth Salesky, Eleanor Chodroff, Tiago Pimentel, Matthew Wiesner, Ryan Cotterell, Alan W. Black, Jason Eisner |
| 2020 | ICML | Neural Datalog Through Time: Informed Temporal Modeling via Logical Specification. | Hongyuan Mei, Guanghui Qin, Minjie Xu, Jason Eisner |
| 2020 | IJCAI | Specializing Word Embeddings (for Parsing) by Information Bottleneck (Extended Abstract). | Xiang Lisa Li, Jason Eisner |
| 2019 | AAAI | Spell Once, Summon Anywhere: A Two-Level Open-Vocabulary Language Model. | S. J. Mielke, Jason Eisner |
| 2019 | ACL | What Kind of Language Is Hard to Language-Model? | S. J. Mielke, Ryan Cotterell, Kyle Gorman, Brian Roark, Jason Eisner |
| 2019 | EMNLP | Specializing Word Embeddings (for Parsing) by Information Bottleneck. | Xiang Lisa Li, Jason Eisner |
| 2019 | EMNLP | Spelling-Aware Construction of Macaronic Texts for Teaching Foreign-Language Vocabulary. | Adithya Renduchintala, Philipp Koehn, Jason Eisner |
| 2019 | ICML | Imputing Missing Events in Continuous-Time Event Streams. | Hongyuan Mei, Guanghui Qin, Jason Eisner |
| 2019 | NAACL | Neural Finite-State Transducers: Beyond Rational Relations. | Chu-Cheng Lin, Hao Zhu, Matthew R. Gormley, Jason Eisner |
| 2019 | NAACL | Contextualization of Morphological Inflection. | Ekaterina Vylomova, Ryan Cotterell, Trevor Cohn, Timothy Baldwin, Jason Eisner |
| 2018 | CoNLL | The CoNLL-SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection. | Ryan Cotterell, Christo Kirov, John Sylak-Glassman, Graldine Walther, Ekaterina Vylomova, Arya D. McCarthy, Katharina Kann, S. J. Mielke, Garrett Nicolai, Miikka Silfverberg, David Yarowsky, Jason Eisner, Mans Hulden |
| 2018 | EMNLP | Synthetic Data Made to Order: The Case of Parsing. | Dingquan Wang, Jason Eisner |
| 2018 | LREC | UniMorph 2.0: Universal Morphology. | Christo Kirov, Ryan Cotterell, John Sylak-Glassman, Graldine Walther, Ekaterina Vylomova, Patrick Xia, Manaal Faruqui, S. J. Mielke, Arya McCarthy, Sandra Kbler, David Yarowsky, Jason Eisner, Mans Hulden |
| 2018 | NAACL | A Deep Generative Model of Vowel Formant Typology. | Ryan Cotterell, Jason Eisner |
| 2018 | NAACL | Unsupervised Disambiguation of Syncretism in Inflected Lexicons. | Ryan Cotterell, Christo Kirov, S. J. Mielke, Jason Eisner |
| 2018 | NAACL | Are All Languages Equally Hard to Language-Model? | Ryan Cotterell, S. J. Mielke, Jason Eisner, Brian Roark |
| 2018 | NAACL | Neural Particle Smoothing for Sampling from Conditional Sequence Models. | Chu-Cheng Lin, Jason Eisner |
| 2017 | ACL | Bayesian Modeling of Lexical Resources for Low-Resource Settings. | Nicholas Andrews, Mark Dredze, Benjamin Van Durme, Jason Eisner |
| 2017 | ACL | Probabilistic Typology: Deep Generative Models of Vowel Inventories. | Ryan Cotterell, Jason Eisner |
| 2017 | CoNLL | CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages. | Ryan Cotterell, Christo Kirov, John Sylak-Glassman, Graldine Walther, Ekaterina Vylomova, Patrick Xia, Manaal Faruqui, Sandra Kbler, David Yarowsky, Jason Eisner, Mans Hulden |
| 2017 | CoNLL | Knowledge Tracing in Sequential Learning of Inflected Vocabulary. | Adithya Renduchintala, Philipp Koehn, Jason Eisner |
| 2017 | EACL | Explaining and Generalizing Skip-Gram through Exponential Family Principal Component Analysis. | Ryan Cotterell, Adam Poliak, Benjamin Van Durme, Jason Eisner |
| 2017 | PLDI | Dyna: toward a self-optimizing declarative language for machine learning applications. | Tim Vieira, Matthew Francis-Landau, Nathaniel Wesley Filardo, Farzad Khorasani, Jason Eisner |
| 2016 | ACL | Morphological Smoothing and Extrapolation of Word Embeddings. | Ryan Cotterell, Hinrich Schtze, Jason Eisner |
| 2016 | ACL | User Modeling in Language Learning with Macaronic Texts. | Adithya Renduchintala, Rebecca Knowles, Philipp Koehn, Jason Eisner |
| 2016 | ACL | Creating Interactive Macaronic Interfaces for Language Learning. | Adithya Renduchintala, Rebecca Knowles, Philipp Koehn, Jason Eisner |
| 2016 | CoNLL | Analyzing Learner Understanding of Novel L2 Vocabulary. | Rebecca Knowles, Adithya Renduchintala, Philipp Koehn, Jason Eisner |
| 2016 | EMNLP | Inside-Outside and Forward-Backward Algorithms Are Just Backprop (tutorial paper). | Jason Eisner |
| 2016 | EMNLP | Speed-Accuracy Tradeoffs in Tagging with Variable-Order CRFs and Structured Sparsity. | Tim Vieira, Ryan Cotterell, Jason Eisner |
| 2016 | NAACL | Weighting Finite-State Transductions With Neural Context. | Pushpendre Rastogi, Ryan Cotterell, Jason Eisner |
| 2016 | SC | Fine-Grained Parallelism in Probabilistic Parsing with Habanero Java. | Matthew Francis-Landau, Bing Xue, Jason Eisner, Vivek Sarkar |
| 2015 | ACL | Structured Belief Propagation for NLP. | Matthew R. Gormley, Jason Eisner |
| 2015 | EMNLP | Dual Decomposition Inference for Graphical Models over Strings. | Nanyun Peng, Ryan Cotterell, Jason Eisner |
| 2015 | NAACL | Penalized Expectation Propagation for Graphical Models over Strings. | Ryan Cotterell, Jason Eisner |
| 2014 | ACL | Robust Entity Clustering via Phylogenetic Inference. | Nicholas Andrews, Jason Eisner, Mark Dredze |
| 2014 | ACL | Stochastic Contextual Edit Distance and Probabilistic FSTs. | Ryan Cotterell, Nanyun Peng, Jason Eisner |
| 2014 | ACL | Structured Belief Propagation for NLP. | Matthew Gormley, Jason Eisner |
| 2013 | ACL | Nonconvex Global Optimization for Latent-Variable Models. | Matthew R. Gormley, Jason Eisner |
| 2013 | EMNLP | Dynamic Feature Selection for Dependency Parsing. | He He, Hal Daum III, Jason Eisner |
| 2012 | COLING | Easy-first Coreference Resolution. | Veselin Stoyanov, Jason Eisner |
| 2012 | EMNLP | Name Phylogeny: A Generative Model of String Variation. | Nicholas Andrews, Jason Eisner, Mark Dredze |
| 2012 | ICLP | A Flexible Solver for Finite Arithmetic Circuits. | Nathaniel Wesley Filardo, Jason Eisner |
| 2012 | NAACL | Shared Components Topic Models. | Matthew R. Gormley, Mark Dredze, Benjamin Van Durme, Jason Eisner |
| 2012 | NAACL | Implicitly Intersecting Weighted Automata using Dual Decomposition. | Michael J. Paul, Jason Eisner |
| 2012 | NAACL | Unsupervised Learning on an Approximate Corpus. | Jason Smith, Jason Eisner |
| 2012 | NAACL | Minimum-Risk Training of Approximate CRF-Based NLP Systems. | Veselin Stoyanov, Jason Eisner |
| 2011 | EMNLP | Discovering Morphological Paradigms from Plain Text Using a Dirichlet Process Mixture Model. | Markus Dreyer, Jason Eisner |
| 2011 | EMNLP | Minimum Imputed-Risk: Unsupervised Discriminative Training for Machine Translation. | Zhifei Li, Ziyuan Wang, Jason Eisner, Sanjeev Khudanpur, Brian Roark |
| 2010 | COLING | Unsupervised Discriminative Language Model Training for Machine Translation using Simulated Confusion Sets. | Zhifei Li, Ziyuan Wang, Sanjeev Khudanpur, Jason Eisner |
| 2009 | ACL | Variational Decoding for Statistical Machine Translation. | Zhifei Li, Jason Eisner, Sanjeev Khudanpur |
| 2009 | EMNLP | Graphical Models over Multiple Strings. | Markus Dreyer, Jason Eisner |
| 2009 | EMNLP | First- and Second-Order Expectation Semirings with Applications to Minimum-Risk Training on Translation Forests. | Zhifei Li, Jason Eisner |
| 2009 | EMNLP | Parser Adaptation and Projection with Quasi-Synchronous Grammar Features. | David A. Smith, Jason Eisner |
| 2009 | EMNLP | Learning Linear Ordering Problems for Better Translation. | Roy W. Tromble, Jason Eisner |
| 2008 | ACL | Machine Translation System Combination using ITG-based Alignments. | Damianos Karakos, Jason Eisner, Sanjeev Khudanpur, Markus Dreyer |
| 2008 | EMNLP | Latent-Variable Modeling of String Transductions with Finite-State Methods. | Markus Dreyer, Jason Smith, Jason Eisner |
| 2008 | EMNLP | Dependency Parsing by Belief Propagation. | David A. Smith, Jason Eisner |
| 2008 | EMNLP | Modeling Annotators: A Generative Approach to Learning from Annotator Rationales. | Omar Zaidan, Jason Eisner |
| 2007 | EMNLP | Bootstrapping Feature-Rich Dependency Parsers with Entropic Priors. | David A. Smith, Jason Eisner |
| 2007 | ICASSP | Iterative Denoising using Jensen-Renyi Divergences with an Application to Unsupervised Document Categorization. | Damianos Karakos, Sanjeev Khudanpur, Jason Eisner, Carey E. Priebe |
| 2007 | NAACL | Cross-Instance Tuning of Unsupervised Document Clustering Algorithms. | Damianos Karakos, Jason Eisner, Sanjeev Khudanpur, Carey E. Priebe |
| 2007 | NAACL | Using "Annotator Rationales" to Improve Machine Learning for Text Categorization. | Omar Zaidan, Jason Eisner, Christine D. Piatko |
| 2006 | ACL | Annealing Structural Bias in Multilingual Weighted Grammar Induction. | Noah A. Smith, Jason Eisner |
| 2006 | ACL | Minimum Risk Annealing for Training Log-Linear Models. | David A. Smith, Jason Eisner |
| 2006 | CCS | A natural language approach to automated cryptanalysis of two-time pads. | Joshua Mason, Kathryn Watkins, Jason Eisner, Adam Stubblefield |
| 2006 | EMNLP | Better Informed Training of Latent Syntactic Features. | Markus Dreyer, Jason Eisner |
| 2006 | NAACL | A fast finite-state relaxation method for enforcing global constraints on sequence decoding. | Roy W. Tromble, Jason Eisner |
| 2005 | ACL | Contrastive Estimation: Training Log-Linear Models on Unlabeled Data. | Noah A. Smith, Jason Eisner |
| 2005 | ICASSP | Unsupervised classification via decision trees: an information-theoretic perspective. | Damianos Karakos, Sanjeev Khudanpur, Jason Eisner, Carey E. Priebe |
| 2005 | NAACL | Compiling Comp Ling: Weighted Dynamic Programming and the Dyna Language. | Jason Eisner, Eric Goldlust, Noah A. Smith |
| 2005 | NAACL | Bootstrapping Without the Boot. | Jason Eisner, Damianos Karakos |
| 2004 | ACL | Dyna: A Language for Weighted Dynamic Programming. | Jason Eisner, Eric Goldlust, Noah A. Smith |
| 2004 | ACL | Annealing Techniques For Unsupervised Statistical Language Learning. | Noah A. Smith, Jason Eisner |
| 2003 | ACL | Learning Non-Isomorphic Tree Mappings for Machine Translation. | Jason Eisner |
| 2003 | NAACL | Simpler and More General Minimization for Weighted Finite-State Automata. | Jason Eisner |
| 2002 | ACL | Parameter Estimation for Probabilistic Finite-State Transducers. | Jason Eisner |
| 2002 | ACL | Phonological Comprehension and the Compilation of Optimality Theory. | Jason Eisner |
| 2002 | EMNLP | Transformational Priors Over Grammars. | Jason Eisner |
| 2000 | COLING | Directional Constraint Evaluation in Optimality Theory. | Jason Eisner |
| 1999 | ACL | Efficient Parsing for Bilexical Context-Free Grammars and Head Automaton Grammars. | Jason Eisner, Giorgio Satta |
| 1997 | ACL | Efficient Generation in Primitive Optimality Theory. | Jason Eisner |
| 1996 | ACL | Efficient Normal-Form Parsing for Combinatory Categorial Grammar. | Jason Eisner |
| 1996 | COLING | Three New Probabilistic Models for Dependency Parsing: An Exploration. | Jason Eisner |
| 1995 | MuC | University of Pennsylvania: description of the University of Pennsylvania system used for MUC-6. | Breck Baldwin, Michael Collins, Jason Eisner, Adwait Ratnaparkhi, Joseph Rosenzweig, Anoop Sarkar |
| 1992 | AAAI | A Probabilistic Parser Applied to Software Testing Documents. | Mark A. Jones, Jason Eisner |