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2020 – today
- 2024
[j2]Jessy Lin, Nicholas Tomlin, Jacob Andreas, Jason Eisner:
Decision-Oriented Dialogue for Human-AI Collaboration. Trans. Assoc. Comput. Linguistics 12: 892-911 (2024)- [c94]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. ACL (Findings) 2024: 231-247 - [c93]Afra Feyza Akyürek, Ekin Akyürek, Leshem Choshen, Derry Wijaya, Jacob Andreas:
Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability. ACL (Findings) 2024: 9802-9818 - [c92]Alexis Ross, Jacob Andreas:
Toward In-Context Teaching: Adapting Examples to Students' Misconceptions. ACL (1) 2024: 13283-13310 - [c91]Gabriel Grand, Lionel Wong, Matthew Bowers, Theo X. Olausson, Muxin Liu, Joshua B. Tenenbaum, Jacob Andreas:
LILO: Learning Interpretable Libraries by Compressing and Documenting Code. ICLR 2024 - [c90]Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau:
Linearity of Relation Decoding in Transformer Language Models. ICLR 2024 - [c89]Athul Paul Jacob, Abhishek Gupta, Jacob Andreas:
Modeling Boundedly Rational Agents with Latent Inference Budgets. ICLR 2024 - [c88]Athul Paul Jacob, Yikang Shen, Gabriele Farina, Jacob Andreas:
The Consensus Game: Language Model Generation via Equilibrium Search. ICLR 2024 - [c87]Andi Peng, Ilia Sucholutsky, Belinda Z. Li, Theodore R. Sumers, Thomas L. Griffiths, Jacob Andreas, Julie Shah:
Learning with Language-Guided State Abstractions. ICLR 2024 - [c86]Lionel Wong, Jiayuan Mao, Pratyusha Sharma, Zachary S. Siegel, Jiahai Feng, Noa Korneev, Joshua B. Tenenbaum, Jacob Andreas:
Learning Grounded Action Abstractions from Language. ICLR 2024 - [c85]Ekin Akyürek, Bailin Wang, Yoon Kim, Jacob Andreas:
In-Context Language Learning: Architectures and Algorithms. ICML 2024 - [c84]Bairu Hou, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang:
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling. ICML 2024 - [c83]Tamar Rott Shaham, Sarah Schwettmann, Franklin Wang, Achyuta Rajaram, Evan Hernandez, Jacob Andreas, Antonio Torralba:
A Multimodal Automated Interpretability Agent. ICML 2024 - [c82]Harsh Jhamtani, Hao Fang, Patrick Xia, Eran Levy, Jacob Andreas, Benjamin Van Durme:
Natural Language Decomposition and Interpretation of Complex Utterances. IJCAI 2024: 6306-6314 - [c81]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. NAACL-HLT 2024: 1311-1329 - [c80]Zhaofeng Wu, Linlu Qiu, Alexis Ross, Ekin Akyürek, Boyuan Chen, Bailin Wang, Najoung Kim, Jacob Andreas, Yoon Kim:
Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks. NAACL-HLT 2024: 1819-1862 - [c79]Athul Paul Jacob, Gabriele Farina, Jacob Andreas:
Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning. NAACL-HLT 2024: 2944-2955 - [c78]Nikita Moghe, Patrick Xia, Jacob Andreas, Jason Eisner, Benjamin Van Durme, Harsh Jhamtani:
Interpreting User Requests in the Context of Natural Language Standing Instructions. NAACL-HLT (Findings) 2024: 4043-4060 - [i100]Afra Feyza Akyürek, Ekin Akyürek, Leshem Choshen, Derry Wijaya
, Jacob Andreas:
Deductive Closure Training of Language Models for Coherence, Accuracy, and Updatability. CoRR abs/2401.08574 (2024) - [i99]Ekin Akyürek, Bailin Wang, Yoon Kim, Jacob Andreas:
In-Context Language Learning: Architectures and Algorithms. CoRR abs/2401.12973 (2024) - [i98]Andi Peng, Ilia Sucholutsky, Belinda Z. Li, Theodore R. Sumers, Thomas L. Griffiths, Jacob Andreas, Julie A. Shah:
Learning with Language-Guided State Abstractions. CoRR abs/2402.18759 (2024) - [i97]Gabriel Grand, Valerio Pepe, Jacob Andreas, Joshua B. Tenenbaum:
Loose LIPS Sink Ships: Asking Questions in Battleship with Language-Informed Program Sampling. CoRR abs/2402.19471 (2024) - [i96]Kunal Handa, Yarin Gal, Ellie Pavlick, Noah D. Goodman, Jacob Andreas, Alex Tamkin, Belinda Z. Li:
Bayesian Preference Elicitation with Language Models. CoRR abs/2403.05534 (2024) - [i95]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Lexicon-Level Contrastive Visual-Grounding Improves Language Modeling. CoRR abs/2403.14551 (2024) - [i94]Emmy Liu, Graham Neubig, Jacob Andreas:
An Incomplete Loop: Deductive, Inductive, and Abductive Learning in Large Language Models. CoRR abs/2404.03028 (2024) - [i93]Achyuta Rajaram, Neil Chowdhury, Antonio Torralba, Jacob Andreas, Sarah Schwettmann:
Automatic Discovery of Visual Circuits. CoRR abs/2404.14349 (2024) - [i92]Tamar Rott Shaham, Sarah Schwettmann, Franklin Wang, Achyuta Rajaram, Evan Hernandez, Jacob Andreas, Antonio Torralba:
A Multimodal Automated Interpretability Agent. CoRR abs/2404.14394 (2024) - [i91]Megha Srivastava, Cédric Colas, Dorsa Sadigh, Jacob Andreas:
Policy Learning with a Language Bottleneck. CoRR abs/2405.04118 (2024) - [i90]Alexis Ross, Jacob Andreas:
Toward In-Context Teaching: Adapting Examples to Students' Misconceptions. CoRR abs/2405.04495 (2024) - [i89]Canaan Breiss, Alexis Ross, Amani Maina-Kilaas, Roger Levy, Jacob Andreas:
Learning Phonotactics from Linguistic Informants. CoRR abs/2405.04726 (2024) - [i88]Anna A. Ivanova, Aalok Sathe, Benjamin Lipkin, Unnathi Kumar, Setayesh Radkani, Thomas Hikaru Clark, Carina Kauf, Jennifer Hu, R. T. Pramod, Gabriel Grand, Vivian C. Paulun, Maria Ryskina, Ekin Akyürek, Ethan Wilcox, Nafisa Rashid, Leshem Choshen, Roger Levy, Evelina Fedorenko, Joshua B. Tenenbaum, Jacob Andreas:
Elements of World Knowledge (EWOK): A cognition-inspired framework for evaluating basic world knowledge in language models. CoRR abs/2405.09605 (2024) - [i87]Bairu Hou, Yang Zhang, Jacob Andreas, Shiyu Chang:
A Probabilistic Framework for LLM Hallucination Detection via Belief Tree Propagation. CoRR abs/2406.06950 (2024) - [i86]Belinda Z. Li, Emmy Liu, Alexis Ross, Abbas Zeitoun, Graham Neubig, Jacob Andreas:
Language Modeling with Editable External Knowledge. CoRR abs/2406.11830 (2024) - [i85]Eric Zhang, Leshem Choshen, Jacob Andreas:
Unforgettable Generalization in Language Models. CoRR abs/2409.02228 (2024) - [i84]Andi Peng, Belinda Z. Li, Ilia Sucholutsky, Nishanth Kumar, Julie A. Shah, Jacob Andreas, Andreea Bobu:
Adaptive Language-Guided Abstraction from Contrastive Explanations. CoRR abs/2409.08212 (2024) - 2023
- [c77]Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning:
Grokking of Hierarchical Structure in Vanilla Transformers. ACL (2) 2023: 439-448 - [c76]Ekin Akyürek, Jacob Andreas:
LexSym: Compositionality as Lexical Symmetry. ACL (1) 2023: 639-657 - [c75]Hao Fang, Anusha Balakrishnan, Harsh Jhamtani, John Bufe, Jean Crawford, Jayant Krishnamurthy, Adam Pauls, Jason Eisner, Jacob Andreas, Dan Klein:
The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding. ACL (Findings) 2023: 5682-5700 - [c74]Belinda Z. Li, Maxwell I. Nye, Jacob Andreas:
Language Modeling with Latent Situations. ACL (Findings) 2023: 12556-12571 - [c73]Shinjini Ghosh, Yoon Kim, Ramón Fernandez Astudillo, Tahira Naseem, Jacob Andreas:
Alignment via Mutual Information. CoNLL 2023: 488-497 - [c72]Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning:
Pushdown Layers: Encoding Recursive Structure in Transformer Language Models. EMNLP 2023: 3233-3247 - [c71]Kevin Liu, Stephen Casper, Dylan Hadfield-Menell, Jacob Andreas:
Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness? EMNLP 2023: 4791-4797 - [c70]Ekin Akyürek, Dale Schuurmans, Jacob Andreas, Tengyu Ma, Denny Zhou:
What learning algorithm is in-context learning? Investigations with linear models. ICLR 2023 - [c69]Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning:
Characterizing intrinsic compositionality in transformers with Tree Projections. ICLR 2023 - [c68]Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas:
Guiding Pretraining in Reinforcement Learning with Large Language Models. ICML 2023: 8657-8677 - [c67]Bairu Hou, Joe O'Connor, Jacob Andreas, Shiyu Chang, Yang Zhang:
PromptBoosting: Black-Box Text Classification with Ten Forward Passes. ICML 2023: 13309-13324 - [c66]Sarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba:
FIND: A Function Description Benchmark for Evaluating Interpretability Methods. NeurIPS 2023 - [c65]Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas:
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. NeurIPS 2023 - [i83]Belinda Z. Li, William Chen, Pratyusha Sharma, Jacob Andreas:
LaMPP: Language Models as Probabilistic Priors for Perception and Action. CoRR abs/2302.02801 (2023) - [i82]Yuqing Du, Olivia Watkins, Zihan Wang, Cédric Colas, Trevor Darrell, Pieter Abbeel, Abhishek Gupta, Jacob Andreas:
Guiding Pretraining in Reinforcement Learning with Large Language Models. CoRR abs/2302.06692 (2023) - [i81]Eric Chu, Jacob Andreas, Stephen Ansolabehere, Deb Roy:
Language Models Trained on Media Diets Can Predict Public Opinion. CoRR abs/2303.16779 (2023) - [i80]Evan Hernandez, Belinda Z. Li, Jacob Andreas:
Measuring and Manipulating Knowledge Representations in Language Models. CoRR abs/2304.00740 (2023) - [i79]Harsh Jhamtani, Hao Fang, Patrick Xia, Eran Levy, Jacob Andreas, Benjamin Van Durme:
Natural Language Decomposition and Interpretation of Complex Utterances. CoRR abs/2305.08677 (2023) - [i78]Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning:
Grokking of Hierarchical Structure in Vanilla Transformers. CoRR abs/2305.18741 (2023) - [i77]Jessy Lin, Nicholas Tomlin, Jacob Andreas, Jason Eisner:
Decision-Oriented Dialogue for Human-AI Collaboration. CoRR abs/2305.20076 (2023) - [i76]Lionel Wong, Gabriel Grand, Alexander K. Lew, Noah D. Goodman, Vikash K. Mansinghka, Jacob Andreas, Joshua B. Tenenbaum:
From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought. CoRR abs/2306.12672 (2023) - [i75]Ziqian Zhong, Ziming Liu, Max Tegmark, Jacob Andreas:
The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks. CoRR abs/2306.17844 (2023) - [i74]Zhaofeng Wu, Linlu Qiu, Alexis Ross, Ekin Akyürek, Boyuan Chen, Bailin Wang, Najoung Kim, Jacob Andreas, Yoon Kim:
Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks. CoRR abs/2307.02477 (2023) - [i73]Evan Hernandez, Arnab Sen Sharma, Tal Haklay, Kevin Meng, Martin Wattenberg, Jacob Andreas, Yonatan Belinkov, David Bau:
Linearity of Relation Decoding in Transformer Language Models. CoRR abs/2308.09124 (2023) - [i72]Sarah Schwettmann, Tamar Rott Shaham, Joanna Materzynska, Neil Chowdhury, Shuang Li, Jacob Andreas, David Bau, Antonio Torralba:
A Function Interpretation Benchmark for Evaluating Interpretability Methods. CoRR abs/2309.03886 (2023) - [i71]Athul Paul Jacob, Yikang Shen, Gabriele Farina, Jacob Andreas:
The Consensus Game: Language Model Generation via Equilibrium Search. CoRR abs/2310.09139 (2023) - [i70]Belinda Z. Li, Alex Tamkin, Noah D. Goodman, Jacob Andreas:
Eliciting Human Preferences with Language Models. CoRR abs/2310.11589 (2023) - [i69]Chengxu Zhuang, Evelina Fedorenko, Jacob Andreas:
Visual Grounding Helps Learn Word Meanings in Low-Data Regimes. CoRR abs/2310.13257 (2023) - [i68]Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning:
Pushdown Layers: Encoding Recursive Structure in Transformer Language Models. CoRR abs/2310.19089 (2023) - [i67]Gabriel Grand, Lionel Wong, Matthew Bowers, Theo X. Olausson, Muxin Liu, Joshua B. Tenenbaum, Jacob Andreas:
LILO: Learning Interpretable Libraries by Compressing and Documenting Code. CoRR abs/2310.19791 (2023) - [i66]Bairu Hou, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang:
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling. CoRR abs/2311.08718 (2023) - [i65]Athul Paul Jacob, Gabriele Farina, Jacob Andreas:
Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning. CoRR abs/2311.09712 (2023) - [i64]Nikita Moghe, Patrick Xia, Jacob Andreas, Jason Eisner, Benjamin Van Durme, Harsh Jhamtani:
Interpreting User Requests in the Context of Natural Language Standing Instructions. CoRR abs/2311.09796 (2023) - [i63]Kevin Liu, Stephen Casper, Dylan Hadfield-Menell, Jacob Andreas:
Cognitive Dissonance: Why Do Language Model Outputs Disagree with Internal Representations of Truthfulness? CoRR abs/2312.03729 (2023) - [i62]Athul Paul Jacob, Abhishek Gupta, Jacob Andreas:
Modeling Boundedly Rational Agents with Latent Inference Budgets. CoRR abs/2312.04030 (2023) - [i61]Shawn Im, Jacob Andreas, Yilun Zhou:
Evaluating the Utility of Model Explanations for Model Development. CoRR abs/2312.06032 (2023) - [i60]Lionel Wong, Jiayuan Mao, Pratyusha Sharma, Zachary S. Siegel, Jiahai Feng, Noa Korneev, Joshua B. Tenenbaum, Jacob Andreas:
Learning adaptive planning representations with natural language guidance. CoRR abs/2312.08566 (2023) - 2022
- [c64]Anton Belyy, Chieh-Yang Huang, Jacob Andreas, Emmanouil Antonios Platanios, Sam Thomson, Richard Shin, Subhro Roy, Aleksandr Nisnevich, Charles Chen, Benjamin Van Durme:
Guided K-best Selection for Semantic Parsing Annotation. ACL (demo) 2022: 114-126 - [c63]Pratyusha Sharma, Antonio Torralba, Jacob Andreas:
Skill Induction and Planning with Latent Language. ACL (1) 2022: 1713-1726 - [c62]Catherine Wong, William P. McCarthy, Gabriel Grand, Yoni Friedman, Josh Tenenbaum, Jacob Andreas, Robert D. Hawkins, Judith E. Fan:
Identifying concept libraries from language about object structure. CogSci 2022 - [c61]Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu:
Towards Tracing Knowledge in Language Models Back to the Training Data. EMNLP (Findings) 2022: 2429-2446 - [c60]Jacob Andreas:
Language Models as Agent Models. EMNLP (Findings) 2022: 5769-5779 - [c59]Bailin Wang, Ivan Titov, Jacob Andreas, Yoon Kim:
Hierarchical Phrase-Based Sequence-to-Sequence Learning. EMNLP 2022: 8211-8229 - [c58]Afra Feyza Akyürek, Ekin Akyürek, Derry Wijaya, Jacob Andreas:
Subspace Regularizers for Few-Shot Class Incremental Learning. ICLR 2022 - [c57]Evan Hernandez, Sarah Schwettmann, David Bau, Teona Bagashvili, Antonio Torralba, Jacob Andreas:
Natural Language Descriptions of Deep Visual Features. ICLR 2022 - [c56]Athul Paul Jacob, David J. Wu, Gabriele Farina, Adam Lerer, Hengyuan Hu, Anton Bakhtin, Jacob Andreas, Noam Brown:
Modeling Strong and Human-Like Gameplay with KL-Regularized Search. ICML 2022: 9695-9728 - [c55]Belinda Z. Li, Jane A. Yu, Madian Khabsa, Luke Zettlemoyer, Alon Y. Halevy, Jacob Andreas:
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks. NAACL-HLT 2022: 4696-4715 - [c54]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. NeurIPS 2022 - [c53]Pratyusha Sharma, Balakumar Sundaralingam, Valts Blukis, Chris Paxton, Tucker Hermans, Antonio Torralba, Jacob Andreas, Dieter Fox:
Correcting Robot Plans with Natural Language Feedback. Robotics: Science and Systems 2022 - [i59]Evan Hernandez, Sarah Schwettmann, David Bau, Teona Bagashvili, Antonio Torralba, Jacob Andreas:
Natural Language Descriptions of Deep Visual Features. CoRR abs/2201.11114 (2022) - [i58]Ekin Akyürek, Jacob Andreas:
Compositionality as Lexical Symmetry. CoRR abs/2201.12926 (2022) - [i57]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. CoRR abs/2202.01771 (2022) - [i56]Olivia Watkins, Trevor Darrell, Pieter Abbeel, Jacob Andreas, Abhishek Gupta:
Teachable Reinforcement Learning via Advice Distillation. CoRR abs/2203.11197 (2022) - [i55]Pratyusha Sharma, Balakumar Sundaralingam, Valts Blukis, Chris Paxton, Tucker Hermans, Antonio Torralba, Jacob Andreas, Dieter Fox:
Correcting Robot Plans with Natural Language Feedback. CoRR abs/2204.05186 (2022) - [i54]Catherine Wong, William P. McCarthy, Gabriel Grand, Yoni Friedman, Joshua B. Tenenbaum, Jacob Andreas, Robert D. Hawkins, Judith E. Fan:
Identifying concept libraries from language about object structure. CoRR abs/2205.05666 (2022) - [i53]Ekin Akyürek, Tolga Bolukbasi, Frederick Liu, Binbin Xiong, Ian Tenney, Jacob Andreas, Kelvin Guu:
Tracing Knowledge in Language Models Back to the Training Data. CoRR abs/2205.11482 (2022) - [i52]Hao Fang, Anusha Balakrishnan, Harsh Jhamtani, John Bufe, Jean Crawford, Jayant Krishnamurthy, Adam Pauls, Jason Eisner, Jacob Andreas, Dan Klein:
The Whole Truth and Nothing But the Truth: Faithful and Controllable Dialogue Response Generation with Dataflow Transduction and Constrained Decoding. CoRR abs/2209.07800 (2022) - [i51]Alex Gu, Tamara Mitrovska, Daniela Velez, Jacob Andreas, Armando Solar-Lezama:
ObSynth: An Interactive Synthesis System for Generating Object Models from Natural Language Specifications. CoRR abs/2210.11468 (2022) - [i50]Shikhar Murty, Pratyusha Sharma, Jacob Andreas, Christopher D. Manning:
Characterizing Intrinsic Compositionality in Transformers with Tree Projections. CoRR abs/2211.01288 (2022) - [i49]Bailin Wang, Ivan Titov, Jacob Andreas, Yoon Kim:
Hierarchical Phrase-based Sequence-to-Sequence Learning. CoRR abs/2211.07906 (2022) - [i48]Ekin Akyürek, Dale Schuurmans, Jacob Andreas, Tengyu Ma, Denny Zhou:
What learning algorithm is in-context learning? Investigations with linear models. CoRR abs/2211.15661 (2022) - [i47]Jacob Andreas:
Language Models as Agent Models. CoRR abs/2212.01681 (2022) - [i46]Bairu Hou, Joe O'Connor, Jacob Andreas, Shiyu Chang, Yang Zhang:
PromptBoosting: Black-Box Text Classification with Ten Forward Passes. CoRR abs/2212.09257 (2022) - [i45]Belinda Z. Li, Maxwell I. Nye, Jacob Andreas:
Language Modeling with Latent Situations. CoRR abs/2212.10012 (2022) - 2021
- [c52]Joe O'Connor, Jacob Andreas:
What Context Features Can Transformer Language Models Use? ACL/IJCNLP (1) 2021: 851-864 - [c51]Belinda Z. Li, Maxwell I. Nye, Jacob Andreas:
Implicit Representations of Meaning in Neural Language Models. ACL/IJCNLP (1) 2021: 1813-1827 - [c50]Emmanouil Antonios Platanios, Adam Pauls, Subhro Roy, Yuchen Zhang, Alexander Kyte, Alan Guo, Sam Thomson, Jayant Krishnamurthy, Jason Andrew Wolfe, Jacob Andreas, Dan Klein:
Value-Agnostic Conversational Semantic Parsing. ACL/IJCNLP (1) 2021: 3666-3681 - [c49]Ekin Akyürek, Jacob Andreas:
Lexicon Learning for Few Shot Sequence Modeling. ACL/IJCNLP (1) 2021: 4934-4946 - [c48]Catherine Wong, Yoni Friedman, Jacob Andreas, Josh Tenenbaum:
Language as a bootstrap for compositional visual reasoning. CogSci 2021 - [c47]Evan Hernandez, Jacob Andreas:
The Low-Dimensional Linear Geometry of Contextualized Word Representations. CoNLL 2021: 82-93 - [c46]D. Anthony Bau, Jacob Andreas:
How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction. EMNLP (1) 2021: 5513-5526 - [c45]Sarah Schwettmann, Evan Hernandez, David Bau, Samuel Klein, Jacob Andreas, Antonio Torralba:
Toward a Visual Concept Vocabulary for GAN Latent Space. ICCV 2021: 6784-6792 - [c44]Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas:
Learning to Recombine and Resample Data For Compositional Generalization. ICLR 2021 - [c43]Maxwell I. Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum, Armando Solar-Lezama:
Representing Partial Programs with Blended Abstract Semantics. ICLR 2021 - [c42]Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas:
Leveraging Language to Learn Program Abstractions and Search Heuristics. ICML 2021: 11193-11204 - [c41]Pengcheng Yin, Hao Fang, Graham Neubig, Adam Pauls, Emmanouil Antonios Platanios, Yu Su, Sam Thomson, Jacob Andreas:
Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention. NAACL-HLT 2021: 2810-2823 - [c40]Athul Paul Jacob, Mike Lewis, Jacob Andreas:
Multitasking Inhibits Semantic Drift. NAACL-HLT 2021: 5351-5366 - [c39]Olivia Watkins, Abhishek Gupta, Trevor Darrell, Pieter Abbeel, Jacob Andreas:
Teachable Reinforcement Learning via Advice Distillation. NeurIPS 2021: 6920-6933 - [i44]Athul Paul Jacob, Mike Lewis, Jacob Andreas:
Multitasking Inhibits Semantic Drift. CoRR abs/2104.07219 (2021) - [i43]Jacob Andreas, Gasper Begus, Michael M. Bronstein, Roee Diamant, Denley Delaney, Shane Gero, Shafi Goldwasser, David F. Gruber, Sarah de Haas, Peter Malkin, Roger Payne, Giovanni Petri, Daniela Rus, Pratyusha Sharma, Dan Tchernov, Pernille Tønnesen, Antonio Torralba, Daniel M. Vogt, Robert J. Wood:
Cetacean Translation Initiative: a roadmap to deciphering the communication of sperm whales. CoRR abs/2104.08614 (2021) - [i42]Evan Hernandez, Jacob Andreas:
The Low-Dimensional Linear Geometry of Contextualized Word Representations. CoRR abs/2105.07109 (2021) - [i41]Belinda Z. Li, Maxwell I. Nye, Jacob Andreas:
Implicit Representations of Meaning in Neural Language Models. CoRR abs/2106.00737 (2021) - [i40]Ekin Akyürek, Jacob Andreas:
Lexicon Learning for Few-Shot Neural Sequence Modeling. CoRR abs/2106.03993 (2021) - [i39]Joe O'Connor, Jacob Andreas:
What Context Features Can Transformer Language Models Use? CoRR abs/2106.08367 (2021) - [i38]Catherine Wong, Kevin Ellis, Joshua B. Tenenbaum, Jacob Andreas:
Leveraging Language to Learn Program Abstractions and Search Heuristics. CoRR abs/2106.11053 (2021) - [i37]Eden Bensaid, Mauro Martino, Benjamin Hoover, Jacob Andreas, Hendrik Strobelt:
FairyTailor: A Multimodal Generative Framework for Storytelling. CoRR abs/2108.04324 (2021) - [i36]Pratyusha Sharma, Antonio Torralba, Jacob Andreas:
Skill Induction and Planning with Latent Language. CoRR abs/2110.01517 (2021) - [i35]Sarah Schwettmann, Evan Hernandez, David Bau, Samuel Klein, Jacob Andreas, Antonio Torralba:
Toward a Visual Concept Vocabulary for GAN Latent Space. CoRR abs/2110.04292 (2021) - [i34]Afra Feyza Akyürek, Ekin Akyürek, Derry Wijaya, Jacob Andreas:
Subspace Regularizers for Few-Shot Class Incremental Learning. CoRR abs/2110.07059 (2021) - [i33]D. Anthony Bau, Jacob Andreas:
How Do Neural Sequence Models Generalize? Local and Global Context Cues for Out-of-Distribution Prediction. CoRR abs/2111.03108 (2021) - [i32]Belinda Z. Li, Jane A. Yu, Madian Khabsa, Luke Zettlemoyer, Alon Y. Halevy, Jacob Andreas:
Quantifying Adaptability in Pre-trained Language Models with 500 Tasks. CoRR abs/2112.03204 (2021) - [i31]Athul Paul Jacob, David J. Wu, Gabriele Farina, Adam Lerer, Anton Bakhtin, Jacob Andreas, Noam Brown:
Modeling Strong and Human-Like Gameplay with KL-Regularized Search. CoRR abs/2112.07544 (2021) - 2020
- [j1]Jacob Andreas, John Bufe, David Burkett, Charles Chen, Josh Clausman, Jean Crawford, Kate Crim, Jordan DeLoach, Leah Dorner, Jason Eisner, Hao Fang, Alan Guo, David Hall, Kristin Hayes, Kellie Hill, Diana Ho, Wendy Iwaszuk, Smriti Jha, Dan Klein, Jayant Krishnamurthy, Theo Lanman, Percy Liang, Christopher H. Lin, Ilya Lintsbakh, Andy McGovern, Aleksandr Nisnevich, Adam Pauls, Dmitrij Petters, Brent Read, Dan Roth, Subhro Roy, Jesse Rusak, Beth Short, Div Slomin, Ben Snyder, Stephon Striplin, Yu Su, Zachary Tellman, Sam Thomson, Andrei Vorobev, Izabela Witoszko, Jason Andrew Wolfe, Abby Wray, Yuchen Zhang, Alexander Zotov:
Task-Oriented Dialogue as Dataflow Synthesis. Trans. Assoc. Comput. Linguistics 8: 556-571 (2020) - [c38]Jacob Andreas:
Good-Enough Compositional Data Augmentation. ACL 2020: 7556-7566 - [c37]Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, Joseph P. Turian:
Experience Grounds Language. EMNLP (1) 2020: 8718-8735 - [c36]Geeticka Chauhan, Ruizhi Liao, William M. Wells III, Jacob Andreas, Xin Wang, Seth J. Berkowitz, Steven Horng, Peter Szolovits, Polina Golland:
Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment. MICCAI (2) 2020: 529-539 - [c35]Jesse Mu, Jacob Andreas:
Compositional Explanations of Neurons. NeurIPS 2020 - [c34]Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, Brenden M. Lake:
A Benchmark for Systematic Generalization in Grounded Language Understanding. NeurIPS 2020 - [i30]Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt, Brenden M. Lake:
A Benchmark for Systematic Generalization in Grounded Language Understanding. CoRR abs/2003.05161 (2020) - [i29]Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, Joseph P. Turian:
Experience Grounds Language. CoRR abs/2004.10151 (2020) - [i28]Alana Marzoev, Samuel Madden, M. Frans Kaashoek, Michael J. Cafarella, Jacob Andreas:
Unnatural Language Processing: Bridging the Gap Between Synthetic and Natural Language Data. CoRR abs/2004.13645 (2020) - [i27]Jesse Mu, Jacob Andreas:
Compositional Explanations of Neurons. CoRR abs/2006.14032 (2020) - [i26]Eric Chu, Deb Roy, Jacob Andreas:
Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction. CoRR abs/2007.12248 (2020) - [i25]Geeticka Chauhan, Ruizhi Liao, William M. Wells III, Jacob Andreas, Xin Wang, Seth J. Berkowitz, Steven Horng, Peter Szolovits, Polina Golland:
Joint Modeling of Chest Radiographs and Radiology Reports for Pulmonary Edema Assessment. CoRR abs/2008.09884 (2020) - [i24]Jacob Andreas, John Bufe, David Burkett, Charles Chen, Josh Clausman, Jean Crawford, Kate Crim, Jordan DeLoach, Leah Dorner, Jason Eisner, Hao Fang, Alan Guo, David Hall, Kristin Hayes, Kellie Hill, Diana Ho, Wendy Iwaszuk, Smriti Jha, Dan Klein, Jayant Krishnamurthy, Theo Lanman, Percy Liang, Christopher H. Lin, Ilya Lintsbakh, Andy McGovern, Aleksandr Nisnevich, Adam Pauls, Dmitrij Petters, Brent Read, Dan Roth, Subhro Roy, Jesse Rusak, Beth Short, Div Slomin, Ben Snyder, Stephon Striplin, Yu Su, Zachary Tellman, Sam Thomson, Andrei Vorobev, Izabela Witoszko, Jason Andrew Wolfe, Abby Wray, Yuchen Zhang, Alexander Zotov:
Task-Oriented Dialogue as Dataflow Synthesis. CoRR abs/2009.11423 (2020) - [i23]Ekin Akyürek, Afra Feyza Akyürek, Jacob Andreas:
Learning to Recombine and Resample Data for Compositional Generalization. CoRR abs/2010.03706 (2020) - [i22]Maxwell I. Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum, Armando Solar-Lezama:
Representing Partial Programs with Blended Abstract Semantics. CoRR abs/2012.12964 (2020)
2010 – 2019
- 2019
- [c33]Jacob Andreas:
Measuring Compositionality in Representation Learning. ICLR (Poster) 2019 - [c32]John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine:
Guiding Policies with Language via Meta-Learning. ICLR (Poster) 2019 - [c31]Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel:
A Survey of Reinforcement Learning Informed by Natural Language. IJCAI 2019: 6309-6317 - [c30]Sheng Shen, Daniel Fried, Jacob Andreas, Dan Klein:
Pragmatically Informative Text Generation. NAACL-HLT (1) 2019: 4060-4067 - [i21]Jacob Andreas:
Measuring Compositionality in Representation Learning. CoRR abs/1902.07181 (2019) - [i20]Sheng Shen, Daniel Fried, Jacob Andreas, Dan Klein:
Pragmatically Informative Text Generation. CoRR abs/1904.01301 (2019) - [i19]Jacob Andreas:
Good-Enough Compositional Data Augmentation. CoRR abs/1904.09545 (2019) - [i18]Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob N. Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson, Tim Rocktäschel:
A Survey of Reinforcement Learning Informed by Natural Language. CoRR abs/1906.03926 (2019) - 2018
- [b1]Jacob Andreas:
Learning from Language. University of California, Berkeley, USA, 2018 - [c29]Ronghang Hu, Jacob Andreas, Trevor Darrell, Kate Saenko:
Explainable Neural Computation via Stack Neural Module Networks. ECCV (7) 2018: 55-71 - [c28]Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg:
Can Deep Reinforcement Learning solve Erdos-Selfridge-Spencer Games? ICLR (Workshop) 2018 - [c27]Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg:
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? ICML 2018: 4235-4243 - [c26]Daniel Fried, Jacob Andreas, Dan Klein:
Unified Pragmatic Models for Generating and Following Instructions. NAACL-HLT 2018: 1951-1963 - [c25]Jacob Andreas, Dan Klein, Sergey Levine:
Learning with Latent Language. NAACL-HLT 2018: 2166-2179 - [c24]Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, Trevor Darrell:
Speaker-Follower Models for Vision-and-Language Navigation. NeurIPS 2018: 3318-3329 - [i17]Daniel Fried, Ronghang Hu, Volkan Cirik, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Dan Klein, Trevor Darrell:
Speaker-Follower Models for Vision-and-Language Navigation. CoRR abs/1806.02724 (2018) - [i16]Ronghang Hu, Jacob Andreas, Trevor Darrell, Kate Saenko:
Explainable Neural Computation via Stack Neural Module Networks. CoRR abs/1807.08556 (2018) - 2017
- [c23]Jacob Andreas, Anca D. Dragan, Dan Klein:
Translating Neuralese. ACL (1) 2017: 232-242 - [c22]Mitchell Stern, Jacob Andreas, Dan Klein:
A Minimal Span-Based Neural Constituency Parser. ACL (1) 2017: 818-827 - [c21]Ronghang Hu, Marcus Rohrbach, Jacob Andreas, Trevor Darrell, Kate Saenko:
Modeling Relationships in Referential Expressions with Compositional Modular Networks. CVPR 2017: 4418-4427 - [c20]Jacob Andreas, Dan Klein:
Analogs of Linguistic Structure in Deep Representations. EMNLP 2017: 2893-2897 - [c19]Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Kate Saenko:
Learning to Reason: End-to-End Module Networks for Visual Question Answering. ICCV 2017: 804-813 - [c18]Jacob Andreas, Dan Klein, Sergey Levine:
Modular Multitask Reinforcement Learning with Policy Sketches. ICML 2017: 166-175 - [e1]Mohit Bansal, Cynthia Matuszek, Jacob Andreas, Yoav Artzi, Yonatan Bisk:
Proceedings of the First Workshop on Language Grounding for Robotics, RoboNLP@ACL 2017, Vancouver, Canada, August 3, 2017. Association for Computational Linguistics 2017, ISBN 978-1-945626-64-7 [contents] - [i15]Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Kate Saenko:
Learning to Reason: End-to-End Module Networks for Visual Question Answering. CoRR abs/1704.05526 (2017) - [i14]Jacob Andreas, Anca D. Dragan, Dan Klein:
Translating Neuralese. CoRR abs/1704.06960 (2017) - [i13]Mitchell Stern, Jacob Andreas, Dan Klein:
A Minimal Span-Based Neural Constituency Parser. CoRR abs/1705.03919 (2017) - [i12]Jacob Andreas, Dan Klein:
Analogs of Linguistic Structure in Deep Representations. CoRR abs/1707.08139 (2017) - [i11]Jacob Andreas, Dan Klein, Sergey Levine:
Learning with Latent Language. CoRR abs/1711.00482 (2017) - [i10]Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon M. Kleinberg:
Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games? CoRR abs/1711.02301 (2017) - [i9]Daniel Fried, Jacob Andreas, Dan Klein:
Unified Pragmatic Models for Generating and Following Instructions. CoRR abs/1711.04987 (2017) - 2016
- [c17]Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein:
Neural Module Networks. CVPR 2016: 39-48 - [c16]Jacob Andreas, Dan Klein:
Reasoning about Pragmatics with Neural Listeners and Speakers. EMNLP 2016: 1173-1182 - [c15]Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein:
Learning to Compose Neural Networks for Question Answering. HLT-NAACL 2016: 1545-1554 - [i8]Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein:
Learning to Compose Neural Networks for Question Answering. CoRR abs/1601.01705 (2016) - [i7]Jacob Andreas, Dan Klein:
Reasoning About Pragmatics with Neural Listeners and Speakers. CoRR abs/1604.00562 (2016) - [i6]Jacob Andreas, Dan Klein, Sergey Levine:
Modular Multitask Reinforcement Learning with Policy Sketches. CoRR abs/1611.01796 (2016) - [i5]Ronghang Hu, Marcus Rohrbach, Jacob Andreas, Trevor Darrell, Kate Saenko:
Modeling Relationships in Referential Expressions with Compositional Modular Networks. CoRR abs/1611.09978 (2016) - 2015
- [c14]Jacob Andreas, Dan Klein:
Alignment-Based Compositional Semantics for Instruction Following. EMNLP 2015: 1165-1174 - [c13]Jacob Andreas, Dan Klein:
When and why are log-linear models self-normalizing? HLT-NAACL 2015: 244-249 - [c12]Jacob Andreas, Maxim Rabinovich, Michael I. Jordan, Dan Klein:
On the Accuracy of Self-Normalized Log-Linear Models. NIPS 2015: 1783-1791 - [i4]Jacob Andreas, Maxim Rabinovich, Dan Klein, Michael I. Jordan:
On the accuracy of self-normalized log-linear models. CoRR abs/1506.04147 (2015) - [i3]Jacob Andreas, Dan Klein:
Alignment-based compositional semantics for instruction following. CoRR abs/1508.06491 (2015) - [i2]Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein:
Deep Compositional Question Answering with Neural Module Networks. CoRR abs/1511.02799 (2015) - 2014
- [c11]Jacob Andreas, Dan Klein:
How much do word embeddings encode about syntax? ACL (2) 2014: 822-827 - [c10]Jacob Andreas, Dan Klein:
Grounding Language with Points and Paths in Continuous Spaces. CoNLL 2014: 58-67 - [c9]Taylor Berg-Kirkpatrick, Jacob Andreas, Dan Klein:
Unsupervised Transcription of Piano Music. NIPS 2014: 1538-1546 - 2013
- [c8]Jacob Andreas, Andreas Vlachos, Stephen Clark:
Semantic Parsing as Machine Translation. ACL (2) 2013: 47-52 - [c7]Jacob Andreas, Zoubin Ghahramani:
A Generative Model of Vector Space Semantics. CVSM@ACL 2013: 91-99 - [c6]David Chiang, Jacob Andreas, Daniel Bauer, Karl Moritz Hermann, Bevan K. Jones, Kevin Knight:
Parsing Graphs with Hyperedge Replacement Grammars. ACL (1) 2013: 924-932 - 2012
- [c5]Bevan K. Jones, Jacob Andreas, Daniel Bauer, Karl Moritz Hermann, Kevin Knight:
Semantics-Based Machine Translation with Hyperedge Replacement Grammars. COLING 2012: 1359-1376 - [c4]Jacob Andreas, Sara Rosenthal, Kathleen R. McKeown:
Annotating Agreement and Disagreement in Threaded Discussion. LREC 2012: 818-822 - [i1]Jacob Andreas:
The Complexity of Learning Principles and Parameters Grammars. CoRR abs/1207.0052 (2012) - 2011
- [c3]Jacob Andreas, Nizar Habash, Owen Rambow:
Fuzzy Syntactic Reordering for Phrase-based Statistical Machine Translation. WMT@EMNLP 2011: 227-236 - 2010
- [c2]Sara Rosenthal, William Lipovsky, Kathleen R. McKeown, Kapil Thadani, Jacob Andreas:
Towards Semi-Automated Annotation for Prepositional Phrase Attachment. LREC 2010 - [c1]Mukund Jha, Jacob Andreas, Kapil Thadani, Sara Rosenthal, Kathleen R. McKeown:
Corpus Creation for New Genres: A Crowdsourced Approach to PP Attachment. Mturk@HLT-NAACL 2010: 13-20
Coauthor Index
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