Papers
See AI2's Award Winning Papers
Learn more about AI2's Lasting Impact Award
Viewing 781-790 of 991 papers
Value-based Search in Execution Space for Mapping Instructions to Programs
Dor Muhlgay, Jonathan Herzig, Jonathan BerantNAACL • 2019 Training models to map natural language instructions to programs given target world supervision only requires searching for good programs at training time. Search is commonly done using beam search in the space of partial programs or program trees, but as the…White-to-Black: Efficient Distillation of Black-Box Adversarial Attacks
Or Gorodissky, Yoav Chai, Yotam Gil, Jonathan BerantNAACL • 2019 We show that a neural network can learn to imitate the optimization process performed by white-box attack in a much more efficient manner. We train a black-box attack through this imitation process and show our attack is 19x-39x faster than the white-box…FlowQA: Grasping Flow in History for Conversational Machine Comprehension
Hsin-Yuan Huang, Eunsol Choi, Wen-tau YihICLR • 2019 Conversational machine comprehension requires a deep understanding of the conversation history. To enable traditional, single-turn models to encode the history comprehensively, we introduce Flow, a mechanism that can incorporate intermediate representations…Neural network gradient-based learning of black-box function interfaces
Alon Jacovi, Guy Hadash, Einat Kermany, Boaz Carmeli, Ofer Lavi, George Kour, Jonathan BerantICLR • 2019 Deep neural networks work well at approximating complicated functions when provided with data and trained by gradient descent methods. At the same time, there is a vast amount of existing functions that programmatically solve different tasks in a precise…Visual Semantic Navigation using Scene Priors
Wei Yang, Xiaolong Wang, Ali Farhadi, Abhinav Gupta, Roozbeh MottaghiICLR • 2019 How do humans navigate to target objects in novel scenes? Do we use the semantic/functional priors we have built over years to efficiently search and navigate? For example, to search for mugs, we search cabinets near the coffee machine and for fruits we try…The Curious Case of Neural Text Degeneration
Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, Yejin ChoiICLR • 2019 Despite considerable advances in neural language modeling, it remains an open question what the best decoding strategy is for text generation from a language model (e.g. to generate a story). The counter-intuitive empirical observation is that even though the…Tactical Rewind: Self-Correction via Backtracking in Vision-And-Language Navigation
Liyiming Ke, Xiujun Li, Yonatan Bisk, Ari Holtzman, Zhe Gan, Jingjing Liu, Jianfeng Gao, Yejin Choi, S. SrinivasaCVPR • 2019 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 2018 Room-to-Room (R2R) Vision-and-Language navigation challenge. Given a natural language…DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, Claire CardieTACL • 2019 We present DREAM, the first dialogue-based multiple-choice reading comprehension data set. Collected from English as a Foreign Language examinations designed by human experts to evaluate the comprehension level of Chinese learners of English, our data set…ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A. Smith, Yejin ChoiAAAI • 2019 We present ATOMIC, an atlas of everyday commonsense reasoning, organized through 877k textual descriptions of inferential knowledge. Compared to existing resources that center around taxonomic knowledge, ATOMIC focuses on inferential knowledge organized as…Declarative Question Answering over Knowledge Bases containing Natural Language Text with Answer Set Programming
Arindam Mitra, Peter Clark, Oyvind Tafjord, Chitta BaralAAAI • 2019 While in recent years machine learning (ML) based approaches have been the popular approach in developing end-to-end question answering systems, such systems often struggle when additional knowledge is needed to correctly answer the questions. Proposed…