1 code implementation • 17 Apr 2024 • Yue Wu, Yewen Fan, So Yeon Min, Shrimai Prabhumoye, Stephen Mcaleer, Yonatan Bisk, Ruslan Salakhutdinov, Yuanzhi Li, Tom Mitchell
The chains of nodes can be designed to explicitly enforce a naturally structured "thought process".
no code implementations • 1 Apr 2024 • Casey Kennington, Malihe Alikhani, Heather Pon-Barry, Katherine Atwell, Yonatan Bisk, Daniel Fried, Felix Gervits, Zhao Han, Mert Inan, Michael Johnston, Raj Korpan, Diane Litman, Matthew Marge, Cynthia Matuszek, Ross Mead, Shiwali Mohan, Raymond Mooney, Natalie Parde, Jivko Sinapov, Angela Stewart, Matthew Stone, Stefanie Tellex, Tom Williams
The ability to interact with machines using natural human language is becoming not just commonplace, but expected.
1 code implementation • 1 Apr 2024 • Ruohong Zhang, Liangke Gui, Zhiqing Sun, Yihao Feng, Keyang Xu, Yuanhan Zhang, Di Fu, Chunyuan Li, Alexander Hauptmann, Yonatan Bisk, Yiming Yang
Preference modeling techniques, such as direct preference optimization (DPO), has shown effective in enhancing the generalization abilities of large language model (LLM).
no code implementations • 25 Mar 2024 • Yingshan Chang, Yasi Zhang, Zhiyuan Fang, YingNian Wu, Yonatan Bisk, Feng Gao
We hypothesize that the underlying phenomenological coverage has not been proportionally scaled up, leading to a skew of the presented phenomenon which harms generalization.
no code implementations • 19 Mar 2024 • Vidhi Jain, Maria Attarian, Nikhil J Joshi, Ayzaan Wahid, Danny Driess, Quan Vuong, Pannag R Sanketi, Pierre Sermanet, Stefan Welker, Christine Chan, Igor Gilitschenski, Yonatan Bisk, Debidatta Dwibedi
Given a video demonstration of a manipulation task and current visual observations, Vid2Robot directly produces robot actions.
1 code implementation • 13 Mar 2024 • Ruiyi Wang, Haofei Yu, Wenxin Zhang, Zhengyang Qi, Maarten Sap, Graham Neubig, Yonatan Bisk, Hao Zhu
Motivated by this gap, we propose an interactive learning method, SOTOPIA-$\pi$, improving the social intelligence of language agents.
no code implementations • 23 Feb 2024 • Syeda Nahida Akter, Sangwu Lee, Yingshan Chang, Yonatan Bisk, Eric Nyberg
The unique feature of this task, validating question answerability with respect to an image before answering, and the poor performance of state-of-the-art models inspired the design of a new modular baseline, LOGIC2VISION that reasons by producing and executing pseudocode without any external modules to generate the answer.
no code implementations • 14 Dec 2023 • Yafei Hu, Quanting Xie, Vidhi Jain, Jonathan Francis, Jay Patrikar, Nikhil Keetha, Seungchan Kim, Yaqi Xie, Tianyi Zhang, Shibo Zhao, Yu Quan Chong, Chen Wang, Katia Sycara, Matthew Johnson-Roberson, Dhruv Batra, Xiaolong Wang, Sebastian Scherer, Zsolt Kira, Fei Xia, Yonatan Bisk
Motivated by the impressive open-set performance and content generation capabilities of web-scale, large-capacity pre-trained models (i. e., foundation models) in research fields such as Natural Language Processing (NLP) and Computer Vision (CV), we devote this survey to exploring (i) how these existing foundation models from NLP and CV can be applied to the field of robotics, and also exploring (ii) what a robotics-specific foundation model would look like.
1 code implementation • 18 Oct 2023 • Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap
We present SOTOPIA, an open-ended environment to simulate complex social interactions between artificial agents and evaluate their social intelligence.
1 code implementation • 18 Sep 2023 • Quanting Xie, Tianyi Zhang, Kedi Xu, Matthew Johnson-Roberson, Yonatan Bisk
We introduce a new task OUTDOOR, a new mechanism for Large Language Models (LLMs) to accurately hallucinate possible futures, and a new computationally aware success metric for pushing research forward in this more complex domain.
1 code implementation • 25 Jul 2023 • Shuyan Zhou, Frank F. Xu, Hao Zhu, Xuhui Zhou, Robert Lo, Abishek Sridhar, Xianyi Cheng, Tianyue Ou, Yonatan Bisk, Daniel Fried, Uri Alon, Graham Neubig
Building upon our environment, we release a set of benchmark tasks focusing on evaluating the functional correctness of task completions.
no code implementations • 25 Jul 2023 • Vidhi Jain, Jayant Sravan Tamarapalli, Sahiti Yerramilli, Yonatan Bisk
Understanding multimodal perception for embodied AI is an open question because such inputs may contain highly complementary as well as redundant information for the task.
no code implementations • NeurIPS 2023 • Lijun Yu, Yong Cheng, Zhiruo Wang, Vivek Kumar, Wolfgang Macherey, Yanping Huang, David A. Ross, Irfan Essa, Yonatan Bisk, Ming-Hsuan Yang, Kevin Murphy, Alexander G. Hauptmann, Lu Jiang
In this work, we introduce Semantic Pyramid AutoEncoder (SPAE) for enabling frozen LLMs to perform both understanding and generation tasks involving non-linguistic modalities such as images or videos.
no code implementations • 20 Jun 2023 • Sriram Yenamandra, Arun Ramachandran, Karmesh Yadav, Austin Wang, Mukul Khanna, Theophile Gervet, Tsung-Yen Yang, Vidhi Jain, Alexander William Clegg, John Turner, Zsolt Kira, Manolis Savva, Angel Chang, Devendra Singh Chaplot, Dhruv Batra, Roozbeh Mottaghi, Yonatan Bisk, Chris Paxton
HomeRobot (noun): An affordable compliant robot that navigates homes and manipulates a wide range of objects in order to complete everyday tasks.
1 code implementation • 24 May 2023 • Yue Wu, Shrimai Prabhumoye, So Yeon Min, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Tom Mitchell, Yuanzhi Li
Finally, we show the potential of games as a test bed for LLMs.
no code implementations • 3 May 2023 • Yue Wu, So Yeon Min, Yonatan Bisk, Ruslan Salakhutdinov, Amos Azaria, Yuanzhi Li, Tom Mitchell, Shrimai Prabhumoye
We propose the Plan, Eliminate, and Track (PET) framework.
no code implementations • 21 Apr 2023 • Priyam Parashar, Vidhi Jain, Xiaohan Zhang, Jay Vakil, Sam Powers, Yonatan Bisk, Chris Paxton
We see a 4x improvement over baseline in mobile manipulation setting.
1 code implementation • 2 Mar 2023 • Andy Liu, Hao Zhu, Emmy Liu, Yonatan Bisk, Graham Neubig
We also find some evidence that increasing task difficulty in the training process results in more fluent and precise utterances in evaluation.
1 code implementation • 13 Feb 2023 • Jared Fernandez, Jacob Kahn, Clara Na, Yonatan Bisk, Emma Strubell
In this work, we examine this phenomenon through a series of case studies analyzing the effects of model design decisions, framework paradigms, and hardware platforms on total model latency.
no code implementations • CVPR 2023 • Hao Zhu, Raghav Kapoor, So Yeon Min, Winson Han, Jiatai Li, Kaiwen Geng, Graham Neubig, Yonatan Bisk, Aniruddha Kembhavi, Luca Weihs
Humans constantly explore and learn about their environment out of curiosity, gather information, and update their models of the world.
no code implementations • 9 Dec 2022 • So Yeon Min, Yao-Hung Hubert Tsai, Wei Ding, Ali Farhadi, Ruslan Salakhutdinov, Yonatan Bisk, Jian Zhang
In contrast, our LocCon shows the most robust transfer in the real world among the set of models we compare to, and that the real-world performance of all models can be further improved with self-supervised LocCon in-situ training.
no code implementations • 10 Nov 2022 • Evangelia Spiliopoulou, Artidoro Pagnoni, Yonatan Bisk, Eduard Hovy
This paper investigates models of event implications.
no code implementations • 13 Oct 2022 • Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X. Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B. Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu
We present a retrospective on the state of Embodied AI research.
1 code implementation • 10 Oct 2022 • So Yeon Min, Hao Zhu, Ruslan Salakhutdinov, Yonatan Bisk
We provide empirical comparisons of metrics, analysis of three models, and make suggestions for how the field might best progress.
no code implementations • 6 Jul 2022 • Vidhi Jain, Yixin Lin, Eric Undersander, Yonatan Bisk, Akshara Rai
Every home is different, and every person likes things done in their particular way.
no code implementations • 24 May 2022 • Shruti Palaskar, Akshita Bhagia, Yonatan Bisk, Florian Metze, Alan W Black, Ana Marasović
Combining the visual modality with pretrained language models has been surprisingly effective for simple descriptive tasks such as image captioning.
1 code implementation • 19 May 2022 • Liangke Gui, Yingshan Chang, Qiuyuan Huang, Subhojit Som, Alex Hauptmann, Jianfeng Gao, Yonatan Bisk
Vision-Language Transformers can be learned without low-level human labels (e. g. class labels, bounding boxes, etc).
3 code implementations • 6 Mar 2022 • Joseph Turian, Jordie Shier, Humair Raj Khan, Bhiksha Raj, Björn W. Schuller, Christian J. Steinmetz, Colin Malloy, George Tzanetakis, Gissel Velarde, Kirk McNally, Max Henry, Nicolas Pinto, Camille Noufi, Christian Clough, Dorien Herremans, Eduardo Fonseca, Jesse Engel, Justin Salamon, Philippe Esling, Pranay Manocha, Shinji Watanabe, Zeyu Jin, Yonatan Bisk
The aim of the HEAR benchmark is to develop a general-purpose audio representation that provides a strong basis for learning in a wide variety of tasks and scenarios.
1 code implementation • NAACL 2022 • Liangke Gui, Borui Wang, Qiuyuan Huang, Alex Hauptmann, Yonatan Bisk, Jianfeng Gao
The primary focus of recent work with largescale transformers has been on optimizing the amount of information packed into the model's parameters.
no code implementations • 14 Oct 2021 • Khanh Nguyen, Yonatan Bisk, Hal Daumé III
We show that the agent can take advantage of different types of information depending on the context, and analyze the benefits and challenges of learning the assistance-requesting policy when the assistant can recursively decompose tasks into subtasks.
1 code implementation • ICLR 2022 • So Yeon Min, Devendra Singh Chaplot, Pradeep Ravikumar, Yonatan Bisk, Ruslan Salakhutdinov
In contrast, we propose a modular method with structured representations that (1) builds a semantic map of the scene and (2) performs exploration with a semantic search policy, to achieve the natural language goal.
no code implementations • 29 Sep 2021 • Khanh Xuan Nguyen, Yonatan Bisk, Hal Daumé III
Results on a simulated human-assisted navigation problem demonstrate the effectiveness of our framework: aided with an interaction policy learned by our method, a navigation policy achieves up to a 7× improvement in task success rate compared to performing tasks only by itself.
Hierarchical Reinforcement Learning reinforcement-learning +1
no code implementations • 29 Sep 2021 • Brendon Boldt, Yonatan Bisk, David R Mortensen
The second is shaped rewards which are designed specifically to make the task easier to learn by introducing biases in the learning process.
no code implementations • 29 Sep 2021 • Melanie Sclar, Graham Neubig, Yonatan Bisk
Theory of mind (ToM), the ability to understand others' thoughts and desires, is a cornerstone of human intelligence.
1 code implementation • CoNLL (EMNLP) 2021 • Ruisi Su, Shruti Rijhwani, Hao Zhu, Junxian He, Xinyu Wang, Yonatan Bisk, Graham Neubig
Our experiments find that concreteness is a strong indicator for learning dependency grammars, improving the direct attachment score (DAS) by over 50\% as compared to state-of-the-art models trained on pure text.
2 code implementations • CVPR 2022 • Yingshan Chang, Mridu Narang, Hisami Suzuki, Guihong Cao, Jianfeng Gao, Yonatan Bisk
Scaling Visual Question Answering (VQA) to the open-domain and multi-hop nature of web searches, requires fundamental advances in visual representation learning, knowledge aggregation, and language generation.
no code implementations • ICCV 2021 • Jianwei Yang, Yonatan Bisk, Jianfeng Gao
This is motivated by the observation that for a video-text pair, the content words in the text, such as nouns and verbs, are more likely to be aligned with the visual contents in the video than the function words.
Ranked #3 on Temporal Action Localization on CrossTask (using extra training data)
2 code implementations • 26 Jul 2021 • Jesse Thomason, Mohit Shridhar, Yonatan Bisk, Chris Paxton, Luke Zettlemoyer
We introduce several CLIP-based models for distinguishing objects and demonstrate that while recent advances in jointly modeling vision and language are useful for robotic language understanding, it is still the case that these image-based models are weaker at understanding the 3D nature of objects -- properties which play a key role in manipulation.
no code implementations • 12 Jul 2021 • Hao Zhu, Graham Neubig, Yonatan Bisk
Positive results from our experiments hint at the importance of explicitly modeling communication as a socio-pragmatic progress.
no code implementations • 4 Jun 2021 • Khyathi Raghavi Chandu, Yonatan Bisk, Alan W Black
And finally, (3) How to advance our current definition to bridge the gap with Cognitive Science?
no code implementations • NAACL (GeBNLP) 2022 • Tejas Srinivasan, Yonatan Bisk
Numerous works have analyzed biases in vision and pre-trained language models individually - however, less attention has been paid to how these biases interact in multimodal settings.
no code implementations • EACL 2021 • Alessandro Suglia, Yonatan Bisk, Ioannis Konstas, Antonio Vergari, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
Guessing games are a prototypical instance of the "learning by interacting" paradigm.
no code implementations • ICLR 2021 • Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Cote, Yonatan Bisk, Adam Trischler, Matthew Hausknecht
ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions.
no code implementations • 1 Jan 2021 • Jianwei Yang, Yonatan Bisk, Jianfeng Gao
Building video and language understanding models requires grounding linguistic concepts and video contents into a shared space.
1 code implementation • 7 Nov 2020 • Kaixin Ma, Filip Ilievski, Jonathan Francis, Yonatan Bisk, Eric Nyberg, Alessandro Oltramari
Guided by a set of hypotheses, the framework studies how to transform various pre-existing knowledge resources into a form that is most effective for pre-training models.
no code implementations • COLING 2020 • Alessandro Suglia, Antonio Vergari, Ioannis Konstas, Yonatan Bisk, Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
However, as shown by Suglia et al. (2020), existing models fail to learn truly multi-modal representations, relying instead on gold category labels for objects in the scene both at training and inference time.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, Jianfeng Gao
In this paper, we go beyond instruction following and introduce a two-agent task where one agent navigates and asks questions that a second, guiding agent answers.
1 code implementation • 8 Oct 2020 • Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew Hausknecht
ALFWorld enables the creation of a new BUTLER agent whose abstract knowledge, learned in TextWorld, corresponds directly to concrete, visually grounded actions.
3 code implementations • 29 Jul 2020 • Hao Zhu, Yonatan Bisk, Graham Neubig
In this paper we demonstrate that $\textit{context free grammar (CFG) based methods for grammar induction benefit from modeling lexical dependencies}$.
1 code implementation • EMNLP (nlpbt) 2020 • Frank F. Xu, Lei Ji, Botian Shi, Junyi Du, Graham Neubig, Yonatan Bisk, Nan Duan
Watching instructional videos are often used to learn about procedures.
1 code implementation • 2 May 2020 • Homero Roman Roman, Yonatan Bisk, Jesse Thomason, Asli Celikyilmaz, Jianfeng Gao
In this paper, we go beyond instruction following and introduce a two-agent task where one agent navigates and asks questions that a second, guiding agent answers.
no code implementations • EMNLP 2020 • Yonatan Bisk, Ari Holtzman, Jesse Thomason, Jacob Andreas, Yoshua Bengio, Joyce Chai, Mirella Lapata, Angeliki Lazaridou, Jonathan May, Aleksandr Nisnevich, Nicolas Pinto, Joseph Turian
Language understanding research is held back by a failure to relate language to the physical world it describes and to the social interactions it facilitates.
no code implementations • 2 Mar 2020 • Qiaolin Xia, Xiujun Li, Chunyuan Li, Yonatan Bisk, Zhifang Sui, Jianfeng Gao, Yejin Choi, Noah A. Smith
Learning to navigate in a visual environment following natural language instructions is a challenging task because natural language instructions are highly variable, ambiguous, and under-specified.
7 code implementations • CVPR 2020 • Mohit Shridhar, Jesse Thomason, Daniel Gordon, Yonatan Bisk, Winson Han, Roozbeh Mottaghi, Luke Zettlemoyer, Dieter Fox
We present ALFRED (Action Learning From Realistic Environments and Directives), a benchmark for learning a mapping from natural language instructions and egocentric vision to sequences of actions for household tasks.
2 code implementations • 26 Nov 2019 • Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, Yejin Choi
Questions requiring this kind of physical commonsense pose a challenge to today's natural language understanding systems.
Ranked #36 on Question Answering on PIQA
Natural Language Understanding Physical Commonsense Reasoning +1
1 code implementation • IJCNLP 2019 • Xiujun Li, Chunyuan Li, Qiaolin Xia, Yonatan Bisk, Asli Celikyilmaz, Jianfeng Gao, Noah Smith, Yejin Choi
Core to the vision-and-language navigation (VLN) challenge is building robust instruction representations and action decoding schemes, which can generalize well to previously unseen instructions and environments.
1 code implementation • NAACL 2019 • Yonatan Bisk, Jan Buys, Karl Pichotta, Yejin Choi
Understanding procedural language requires reasoning about both hierarchical and temporal relations between events.
no code implementations • NAACL 2019 • Jesse Thomason, Daniel Gordon, Yonatan Bisk
We demonstrate the surprising strength of unimodal baselines in multimodal domains, and make concrete recommendations for best practices in future research.
4 code implementations • NeurIPS 2019 • Rowan Zellers, Ari Holtzman, Hannah Rashkin, Yonatan Bisk, Ali Farhadi, Franziska Roesner, Yejin Choi
We find that best current discriminators can classify neural fake news from real, human-written, news with 73% accuracy, assuming access to a moderate level of training data.
Ranked #2 on Fake News Detection on Grover-Mega
2 code implementations • ACL 2019 • Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, Yejin Choi
In this paper, we show that commonsense inference still proves difficult for even state-of-the-art models, by presenting HellaSwag, a new challenge dataset.
Ranked #67 on Sentence Completion on HellaSwag
1 code implementation • 2 Apr 2019 • Rosario Scalise, Jesse Thomason, Yonatan Bisk, Siddhartha Srinivasa
We collect over 13 hours of egocentric manipulation data for training a model to reason about whether a robot successfully placed unseen objects in or on one another.
no code implementations • 20 Mar 2019 • Chris Paxton, Yonatan Bisk, Jesse Thomason, Arunkumar Byravan, Dieter Fox
High-level human instructions often correspond to behaviors with multiple implicit steps.
1 code implementation • CVPR 2019 • Liyiming Ke, Xiujun Li, Yonatan Bisk, Ari Holtzman, Zhe Gan, Jingjing Liu, Jianfeng Gao, Yejin Choi, Siddhartha Srinivasa
We present the Frontier Aware Search with backTracking (FAST) Navigator, a general framework for action decoding, that achieves state-of-the-art results on the Room-to-Room (R2R) Vision-and-Language navigation challenge of Anderson et.
Ranked #3 on Vision-Language Navigation on Room2Room
no code implementations • 2 Feb 2019 • Michael Hahn, Frank Keller, Yonatan Bisk, Yonatan Belinkov
Also, transpositions are more difficult than misspellings, and a high error rate increases difficulty for all words, including correct ones.
4 code implementations • CVPR 2019 • Rowan Zellers, Yonatan Bisk, Ali Farhadi, Yejin Choi
While this task is easy for humans, it is tremendously difficult for today's vision systems, requiring higher-order cognition and commonsense reasoning about the world.
Multiple-choice Multiple Choice Question Answering (MCQA) +1
no code implementations • 21 Nov 2018 • Aaron Walsman, Yonatan Bisk, Saadia Gabriel, Dipendra Misra, Yoav Artzi, Yejin Choi, Dieter Fox
Building perceptual systems for robotics which perform well under tight computational budgets requires novel architectures which rethink the traditional computer vision pipeline.
no code implementations • 1 Nov 2018 • Jesse Thomason, Daniel Gordon, Yonatan Bisk
We demonstrate the surprising strength of unimodal baselines in multimodal domains, and make concrete recommendations for best practices in future research.
1 code implementation • EMNLP 2018 • Rowan Zellers, Yonatan Bisk, Roy Schwartz, Yejin Choi
Given a partial description like "she opened the hood of the car," humans can reason about the situation and anticipate what might come next ("then, she examined the engine").
Ranked #4 on Common Sense Reasoning on SWAG
no code implementations • ACL 2018 • Ke Tran, Yonatan Bisk
To address both of these issues we introduce a model that simultaneously translates while inducing dependency trees.
no code implementations • 20 May 2018 • Rosario Scalise, Yonatan Bisk, Maxwell Forbes, Daqing Yi, Yejin Choi, Siddhartha Srinivasa
Robotic agents that share autonomy with a human should leverage human domain knowledge and account for their preferences when completing a task.
2 code implementations • 23 Jan 2018 • Claudia Yan, Dipendra Misra, Andrew Bennnett, Aaron Walsman, Yonatan Bisk, Yoav Artzi
We present CHALET, a 3D house simulator with support for navigation and manipulation.
no code implementations • 10 Dec 2017 • Yonatan Bisk, Kevin J. Shih, Yejin Choi, Daniel Marcu
In this paper, we study the problem of mapping natural language instructions to complex spatial actions in a 3D blocks world.
3 code implementations • ICLR 2018 • Yonatan Belinkov, Yonatan Bisk
Character-based neural machine translation (NMT) models alleviate out-of-vocabulary issues, learn morphology, and move us closer to completely end-to-end translation systems.
no code implementations • IJCNLP 2017 • Alice Lai, Yonatan Bisk, Julia Hockenmaier
We define a novel textual entailment task that requires inference over multiple premise sentences.
1 code implementation • EMNLP 2016 • Yonatan Bisk, Siva Reddy, John Blitzer, Julia Hockenmaier, Mark Steedman
We compare the effectiveness of four different syntactic CCG parsers for a semantic slot-filling task to explore how much syntactic supervision is required for downstream semantic analysis.
2 code implementations • WS 2016 • Ke Tran, Yonatan Bisk, Ashish Vaswani, Daniel Marcu, Kevin Knight
In this work, we present the first results for neuralizing an Unsupervised Hidden Markov Model.
no code implementations • TACL 2013 • Yonatan Bisk, Julia Hockenmaier
We introduce a novel nonparametric Bayesian model for the induction of Combinatory Categorial Grammars from POS-tagged text.