Papers

Learn more about AI2's Lasting Impact Award
Viewing 351-360 of 988 papers
  • A Search Engine for Discovery of Scientific Challenges and Directions

    D. Lahav, Jon Saad-Falcon, Bailey Kuehl, Sophie Johnson, S. Parasa, N. Shomron, Duen Horng Chau, Diyi Yang, E. Horvitz, Daniel S. Weld, Tom HopeAAAI2022 Keeping track of scientific challenges, advances and emerging directions is a fundamental part of research. However, researchers face a flood of papers that hinders discovery of important knowledge. In biomedicine, this directly impacts human lives. To…
  • Knowledge is Power: Symbolic Knowledge Distillation, Commonsense Morality, & Multimodal Script Knowledge

    Yejin ChoiWSDM2022 Scale appears to be the winning recipe in today's AI leaderboards. And yet, extreme-scale neural models are still brittle to make errors that are often nonsensical and even counterintuitive. In this talk, I will argue for the importance of knowledge…
  • A Controllable Model of Grounded Response Generation

    Zeqiu Wu, Michel Galley, Chris Brockett, Yizhe Zhang, Xiang Gao, Chris Quirk, Rik Koncel-Kedziorski, Jianfeng Gao, Hannaneh Hajishirzi, Mari Ostendorf, Bill DolanAAAI 2022 Current end-to-end neural conversation models inherently lack the flexibility to impose semantic control in the response generation process. This control is essential to ensure that users' semantic intents are satisfied and to impose a degree of specificity…
  • Interactron: Embodied Adaptive Object Detection

    Klemen Kotar, Roozbeh MottaghiCVPR2022 Over the years various methods have been proposed for the problem of object detection. Recently, we have wit-nessed great strides in this domain owing to the emergence of powerful deep neural networks. However, there are typically two main assumptions common…
  • Multi-Modal Answer Validation for Knowledge-Based VQA

    Jialin Wu, Jiasen Lu, Ashish Sabharwal, R. MottaghiAAAI2022 The problem of knowledge-based visual question answering involves answering questions that require external knowledge in addition to the content of the image. Such knowledge typically comes in a variety of forms, including visual, textual, and commonsense…
  • Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability

    Kyle Richardson, Ashish SabharwalAAAI2022 Investigating the reasoning abilities of transformer models, and discovering new challenging tasks for them, has been a topic of much interest. Recent studies have found these models to be surprisingly strong at performing deductive reasoning over formal…
  • MuSiQue: Multihop Questions via Single-hop Question Composition

    Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal TACL2022 Multihop reasoning remains an elusive goal as existing multihop benchmarks are known to be largely solvable via shortcuts. Can we create a question answering (QA) dataset that, by construction, \emph{requires} proper multihop reasoning? To this end, we…
  • Correcting Coarse-Grid Weather and Climate Models by Machine Learning From Global Storm-Resolving Simulations

    Bretherton, C. S., B. Henn, A. Kwa, N. D. Brenowitz, O. Watt-Meyer, J. McGibbon, W. A. Perkins, S. K. Clark, and L. HarrisJournal of Advances in Modeling Earth Systems2022 Global atmospheric `storm-resolving' models with horizontal grid spacing of less than 5~km resolve deep cumulus convection and flow in complex terrain. They promise to be reference models that could be used to improve computationally affordable coarse-grid…
  • SCROLLS: Standardized CompaRison Over Long Language Sequences

    Uri Shaham, Elad Segal, Maor Ivgi, Avia Efrat, Ori Yoran, Adi Haviv, Ankit Gupta, Wenhan Xiong, Mor Geva, Jonathan Berant, Omer LevyarXiv2022 NLP benchmarks have largely focused on short texts, such as sentences and paragraphs, even though long texts comprise a considerable amount of natural language in the wild. We introduce SCROLLS, a suite of tasks that require reasoning over long texts. We…
  • Computational Lens on Cognition: Study Of Autobiographical Versus Imagined Stories With Large-Scale Language Models

    Maarten Sap, A. Jafarpour, Yejin Choi, Noah A. Smith, J. Pennebaker, E. HorvitzarXiv2022 Lifelong experiences and learned knowledge lead to shared expectations about how common situations tend to unfold. Such knowledge enables people to interpret story narratives and identify salient events effortlessly. We study differences in the narrative flow…