| KAT: A Knowledge Augmented Transformer for Vision-and-Language | 0 | 0.34 | 2022 |
| A Framework for Learning to Request Rich and Contextually Useful Information from Humans. | 0 | 0.34 | 2022 |
| Symmetric Machine Theory of Mind. | 0 | 0.34 | 2022 |
| Few-shot Language Coordination by Modeling Theory of Mind | 0 | 0.34 | 2021 |
| Dependency Induction Through the Lens of Visual Perception. | 0 | 0.34 | 2021 |
| ALFWorld: Aligning Text and Embodied Environments for Interactive Learning | 0 | 0.34 | 2021 |
| Language Grounding with 3D Objects. | 0 | 0.34 | 2021 |
| Knowledge-Driven Data Construction For Zero-Shot Evaluation In Commonsense Question Answering | 0 | 0.34 | 2021 |
| RMM: A Recursive Mental Model for Dialog Navigation | 0 | 0.34 | 2020 |
| Piqa: Reasoning About Physical Commonsense In Natural Language | 3 | 0.38 | 2020 |
| ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks | 0 | 0.34 | 2020 |
| Experience Grounds Language. | 0 | 0.34 | 2020 |
| Character-based Surprisal as a Model of Human Reading in the Presence of Errors. | 0 | 0.34 | 2019 |
| Character-based Surprisal as a Model of Reading Difficulty in the Presence of Error. | 0 | 0.34 | 2019 |
| Defending Against Neural Fake News. | 8 | 0.44 | 2019 |
| Tactical Rewind: Self-Correction Via Backtracking In Vision-And-Language Navigation | 6 | 0.40 | 2019 |
| Robust Navigation with Language Pretraining and Stochastic Sampling | 3 | 0.43 | 2019 |
| Improving Robot Success Detection Using Static Object Data | 0 | 0.34 | 2019 |
| Benchmarking Hierarchical Script Knowledge | 0 | 0.34 | 2019 |
| Early Fusion For Goal Directed Robotic Vision | 0 | 0.34 | 2019 |
| Balancing Shared Autonomy with Human-Robot Communication. | 0 | 0.34 | 2018 |
| SWAG: A Large-Scale Adversarial Dataset for Grounded Commonsense Inference. | 15 | 0.76 | 2018 |
| From Recognition To Cognition: Visual Commonsense Reasoning | 23 | 0.71 | 2018 |
| Learning Interpretable Spatial Operations in a Rich 3D Blocks World. | 3 | 0.38 | 2018 |
| Inducing Grammars with and for Neural Machine Translation. | 2 | 0.35 | 2018 |
| CHALET: Cornell House Agent Learning Environment. | 9 | 0.48 | 2018 |
| Shifting the Baseline: Single Modality Performance on Visual Navigation & QA. | 4 | 0.38 | 2018 |
| Inducing Grammars with and for Neural Machine Translation. | 0 | 0.34 | 2018 |
| Natural Language Inference from Multiple Premises. | 2 | 0.36 | 2017 |
| Synthetic and Natural Noise Both Break Neural Machine Translation. | 26 | 0.83 | 2017 |
| Evaluating Induced CCG Parsers on Grounded Semantic Parsing. | 3 | 0.36 | 2016 |
| Natural Language Communication with Robots. | 20 | 0.79 | 2016 |
| Towards a Dataset for Human Computer Communication via Grounded Language Acquisition. | 7 | 0.52 | 2016 |
| Unsupervised Neural Hidden Markov Models. | 5 | 0.45 | 2016 |
| Supertagging With LSTMs. | 17 | 0.69 | 2016 |
| Labeled Grammar Induction With Minimal Supervision | 3 | 0.38 | 2015 |
| Probing The Linguistic Strengths And Limitations Of Unsupervised Grammar Induction | 3 | 0.39 | 2015 |
| An HDP Model for Inducing Combinatory Categorial Grammars. | 9 | 0.49 | 2013 |
| Simple Robust Grammar Induction with Combinatory Categorial Grammars. | 13 | 0.56 | 2012 |
| Document-topic hierarchies from document graphs | 7 | 0.45 | 2012 |
| Normal-form parsing for combinatory categorial grammars with generalized composition and type-raising | 5 | 0.46 | 2010 |
