Jacob Andreas @ MIT

Papers

See my research group's page for a more frequently updated list.

2021
How do neural sequence models generalize? Local and global context cues for out-of-distribution generalization. Anthony Bau and Jacob Andreas. EMNLP 2021.
The low-dimensional linear geometry of contextualized word representations. Evan Hernandez and Jacob Andreas. CoNLL 2021.
Toward a visual concept vocabulary for generative adversarial networks. Sarah Schwettmann, Evan Hernandez, David Bau, Samuel Klein, Jacob Andreas and Antonio Torralba. ICCV 2021.
Leveraging language to learn program abstractions and search heuristics. Catherine Wong, Kevin Ellis, Josh Tenenbaum and Jacob Andreas. ICML 2021. paper [arxiv]
Implicit representations of meaning in neural language models. Belinda Z. Li, Maxwell Nye and Jacob Andreas. ACL 2021. paper [arxiv], code [github], video [underline]
What context features can transformer language models use? Joe O'Connor and Jacob Andreas. ACL 2021. paper [arxiv],
Lexicon learning for few-shot sequence modeling. Ekin Akyürek and Jacob Andreas. ACL 2021. paper [arxiv], code [github]
Value-agnostic conversational semantic parsing. Emmanouil Antonios Platanios, Adam Pauls, Subhro Roy, Yuchen Zhang, Alexander Kyte, Alan Guo, Sam Thomson, Jayant Krishnamurthy, Jason Wolfe, Jacob Andreas and Dan Klein. ACL 2021. paper [arxiv]
Multitasking inhibits semantic drift. Athul Paul Jacob, Mike Lewis and Jacob Andreas. NAACL 2021 (talk). paper [arxiv]
Compositional generalization for neural semantic parsing via span-level supervised attention. Pengcheng Yin, Hao Fang, Graham Neubig, Adam Pauls, Anthony Platanios, Yu Su, Sam Thomson and Jacob Andreas. NAACL 2021 (talk). paper [arxiv]
Representing partial programs with blended abstract semantics. Maxwell Nye, Yewen Pu, Matthew Bowers, Jacob Andreas, Joshua B. Tenenbaum and Armando Solar-Lezama. ICLR 2021 (poster). paper [arxiv]
Learning to recombine and resample data for compositional generalization. Ekin Akyürek, Afra Feyza Akyürek and Jacob Andreas. ICLR 2021 (poster). paper [arxiv]
2020
Compositional explanations of neurons. Jesse Mu and Jacob Andreas. NeurIPS 2020 (talk). paper [arxiv], code [git]
A benchmark for systematic generalization in grounded language understanding. Laura Ruis, Jacob Andreas, Marco Baroni, Diane Bouchacourt and Brenden Lake. NeurIPS 2020 (poster). paper [arxiv], code [git]
Experience Grounds Language. Yonatan Bisk*, Ari Holtzman*, Jesse Thomason*, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto and Joseph Turian. EMNLP 2020 (poster). paper [arxiv]
Joint modeling of chest radiographs and radiology reports for pulmonary edema assessment. Geeticka Chauhan, Ruizhi Liao, William Wells, Jacob Andreas, Xin Wang, Seth Berkowitz, Steven Horng, Peter Szolovits and Polina Golland. MICCAI 2020. paper [arxiv]
Task-Oriented Dialogue as Dataflow Synthesis. Semantic Machines. TACL 2020 (EMNLP talk). project page
Good-enough compositional data augmentation. Jacob Andreas. ACL 2020. paper [arxiv], code [git]
2019
A survey of reinforcement learning informed by natural language. Jelena Luketina, Nantas Nardelli, Gregory Farquhar, Jakob Foerster, Jacob Andreas, Edward Grefenstette, Shimon Whiteson and Tim Rocktäschel. IJCAI 2019 (survey). paper [arxiv]
Pragmatically informative text generation. Sheng Shen, Daniel Fried, Jacob Andreas and Dan Klein. NAACL 2019 (talk). paper [arxiv], code [git]
Measuring compositionality in representation learning. Jacob Andreas. ICLR 2019 (poster). paper [arxiv], code [git]
Guiding policies with language via meta-learning. John D Co-Reyes, Abhishek Gupta, Suvansh Sanjeev, Nick Altieri, Jacob Andreas, John DeNero, Pieter Abbeel, Sergey Levine. ICLR 2019 (poster). paper [arxiv]
2018
Speaker–follower models for vision-and-language navigation. Daniel Fried*, Ronghang Hu*, Volkan Cirik*, Anna Rohrbach, Jacob Andreas, Louis-Philippe Morency, Taylor Berg-Kirkpatrick, Kate Saenko, Trevor Darrell and Dan Klein. NeurIPS 2018 (poster). paper [arxiv], project page
Explainable neural computation via stack neural module networks. Ronghang Hu, Jacob Andreas, Kate Saenko and Trevor Darrell. ECCV 2018. paper [arxiv], proect page
Can deep reinforcement learning solve Erdos–Selfridge–Spencer games? Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc Le and Jon Kleinberg. ICML 2018 (talk). paper [arxiv]
Learning with latent language. Jacob Andreas, Dan Klein and Sergey Levine. NAACL 2018 (poster). paper [arxiv], code [git]
Unified pragmatic models for generating and following instructions. Daniel Fried, Jacob Andreas and Dan Klein. NAACL 2018 (talk). paper [arxiv], video [vimeo]
2017
Learning to reason: End-to-end module networks for visual question answering. Ronghang Hu, Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Kate Saenko. ICCV 2017 (spotlight). paper [arxiv], code [git]
Analogs of linguistic structure in deep representations. Jacob Andreas and Dan Klein. EMNLP 2017 (talk). paper [arxiv], code [git], slides [pdf]
Modular multitask reinforcement learning with policy sketches. Jacob Andreas, Dan Klein and Sergey Levine. ICML 2017 (best paper honorable mention). paper [arxiv], code [git], slides [pdf]
Translating neuralese. Jacob Andreas, Anca Dragan and Dan Klein. ACL 2017 (talk). paper [arxiv], code [git], slides [pdf]
A minimal span-based neural constituency parser. Mitchell Stern, Jacob Andreas and Dan Klein. ACL 2017 (talk). paper [arxiv]
Modeling relationships in referential expressions with compositional modular networks. Ronghang Hu, Marcus Rohrbach, Jacob Andreas, Trevor Darrell and Kate Saenko. CVPR 2017 (spotlight). paper [arxiv] code [git]
2016
Reasoning about pragmatics with neural listeners and speakers. Jacob Andreas and Dan Klein. EMNLP 2016 (talk). paper [arxiv], code [git], slides [pdf]
Learning to compose neural networks for question answering. Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein. NAACL 2016 (best paper). paper [arxiv], code [git], slides [pdf], video [youtube]
Neural module networks. Jacob Andreas, Marcus Rohrbach, Trevor Darrell and Dan Klein. CVPR 2016 (talk). paper [arxiv], code [git], slides [pdf], video [youtube]
2015
On the accuracy of self-normalized log-linear models. Jacob Andreas*, Maxim Rabinovich*, Dan Klein and Michael I. Jordan. NeurIPS 2015 (poster). paper [arxiv]
Alignment-based compositional semantics for instruction following. Jacob Andreas and Dan Klein. EMNLP 2015 (talk). paper [arxiv], code [git], slides [pdf], video [vimeo]
When and why are log-linear models self-normalizing? Jacob Andreas and Dan Klein. NAACL 2015 (talk). paper [pdf], code [git],
2014
Unsupervised transcription of piano music. Taylor Berg-Kirkpatrick, Jacob Andreas and Dan Klein. NeurIPS 2014 (spotlight & demo). paper [pdf]
Grounding language with points and paths in continuous spaces. Jacob Andreas and Dan Klein. CoNLL 2014 (talk). paper [pdf], code [tgz], slides [pptx]
How much do word embeddings encode about syntax? Jacob Andreas and Dan Klein. ACL 2014 (talk). paper [pdf], code [tgz], slides [pptx]
2013
Semantic parsing as machine translation. Jacob Andreas, Andreas Vlachos and Stephen Clark. ACL 2013 (talk). paper [pdf], code [git]
Parsing graphs with hyperedge replacement grammars. David Chiang, Jacob Andreas, Daniel Bauer, Karl Moritz Hermann, Bevan Jones and Kevin Knight. ACL 2013 (poster). paper [pdf]
Earlier
A generative model of vector space semantics. Jacob Andreas and Zoubin Ghahramani. ACL 2013 Workshop on continuous vector space models and their compositionality.
paper [pdf], code [git]
Semantics-based machine translation with hyperedge replacement grammars. Bevan Jones*, Jacob Andreas*, Daniel Bauer*, Karl Moritz Hermann* and Kevin Knight. COLING 2012. paper [pdf], code [git]
Detecting influencers in written online conversations. Or Biran, Sara Rosenthal, Jacob Andreas, Kathleen McKeown and Owen Rambow. NAACL 2012 Workshop on language and social media.
paper [pdf]
Fuzzy syntactic reordering for phrase-based statistical machine translation. Jacob Andreas, Nizar Habash and Owen Rambow. WMT 2011. paper [pdf]
Resources & annotation
Annotating agreement and disagreement in threaded discussion. Jacob Andreas, Sara Rosenthal and Kathleen McKeown. LREC 2012. paper [pdf], slides [pdf], data
Corpus creation for new genres: a crowdsourced approach to PP attachment. Mukund Jha, Jacob Andreas, Kapil Thadani, Sara Rosenthal and Kathleen McKeown. NAACL 2010 Workshop on creating speech and language data with Mechanical Turk.
paper [pdf]
Towards semi-automated annotation for prepositional phrase attachment. Sara Rosenthal, William J. Lipovsky, Kathleen McKeown, Kapil Thadani and Jacob Andreas. LREC 2010. paper [pdf]

[*Authors are listed in arbitrary order.]

Collaborators: Mitchell Stern, Anca Dragan, Ronghang Hu, Kate Saenko, Sergey Levine, Trevor Darrell, Marcus Rohrbach, Mike Jordan, Max Rabinovich, Taylor Berg-Kirkpatrick, Dan Klein, Zoubin Ghahramani, Stephen Clark, Andreas Vlachos, Kevin Knight, Bevan Jones, Daniel Bauer, Karl Moritz Hermann, David Chiang, Michael Collins, Nizar Habash, Owen Rambow, Or Biran, Kathy McKeown, Kapil Thadani, Mukund Jha, Sara Rosenthal, William Lipovsky.