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  • Visual Room Rearrangement

    Luca Weihs, Matt Deitke, Aniruddha Kembhavi, R. MottaghiarXiv • 2021 There has been a significant recent progress in the field of Embodied AI with researchers developing models and algorithms enabling embodied agents to navigate and interact within completely unseen environments. In this paper, we propose a new dataset and…

  • LayoutParser: A Unified Toolkit for Deep Learning Based Document Image Analysis

    Zejiang Shen, Ruochen Zhang, Melissa Dell, B. Lee, Jacob Carlson, Weining LiarXiv • 2021 Recent advances in document image analysis (DIA) have been primarily driven by the application of neural networks. Ideally, research outcomes could be easily deployed in production and extended for further investigation. However, various factors like loosely…

  • Thinking Aloud: Dynamic Context Generation Improves Zero-Shot Reasoning Performance of GPT-2

    G. Betz, Kyle Richardson, Christian VoigtarXiv • 2021 Thinking aloud is an effective meta-cognitive strategy human reasoners apply to solve difficult problems. We suggest to improve the reasoning ability of pre-trained neural language models in a similar way, namely by expanding a task’s context with problem…

  • Information to Wisdom: Commonsense Knowledge Extraction and Compilation

    Simon Razniewski, Niket Tandon, Aparna S. Varde WSDM '21: Proceedings of the 14th ACM International Conference on Web Search and Data Mining • 2021 Commonsense knowledge is a foundational cornerstone of artificial intelligence applications. Whereas information extraction and knowledge base construction for instance-oriented assertions, such as Brad Pitt's birth date, or Angelina Jolie's movie awards, has…

  • What Can You Learn from Your Muscles? Learning Visual Representation from Human Interactions

    Kiana Ehsani, Daniel Gordon, T. Nguyen, R. Mottaghi, A. FarhadiICLR • 2021 Learning effective representations of visual data that generalize to a variety of downstream tasks has been a long quest for computer vision. Most representation learning approaches rely solely on visual data such as images or videos. In this paper, we…

  • Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI

    Alon Jacovi, Ana Marasović, Tim Miller, Yoav GoldbergFAccT • 2021 Trust is a central component of the interaction between people and AI, in that 'incorrect' levels of trust may cause misuse, abuse or disuse of the technology. But what, precisely, is the nature of trust in AI? What are the prerequisites and goals of the…

  • Gender trends in computer science authorship

    Lucy Lu Wang, Gabriel Stanovsky, Luca Weihs, Oren EtzioniCACM • 2021 A comprehensive and up-to-date analysis of Computer Science literature (2.87 million papers through 2018) reveals that, if current trends continue, parity between the number of male and female authors will not be reached in this century. Under our most…

  • Learning Generalizable Visual Representations via Interactive Gameplay

    Luca Weihs, Aniruddha Kembhavi, Kiana Ehsani, Sarah M Pratt, Winson Han, Alvaro Herrasti, Eric Kolve, Dustin Schwenk, R. Mottaghi, A. FarhadiICLR • 2021 A growing body of research suggests that embodied gameplay, prevalent not just in human cultures but across a variety of animal species including turtles and ravens, is critical in developing the neural flexibility for creative problem solving, decision…

  • Think you have Solved Direct-Answer Question Answering? Try ARC-DA, the Direct-Answer AI2 Reasoning Challenge

    Sumithra Bhakthavatsalam, Daniel Khashabi, Tushar Khot, B. D. Mishra, Kyle Richardson, Ashish Sabharwal, Carissa Schoenick, Oyvind Tafjord, P. ClarkarXiv • 2021 We present the ARC-DA dataset, a direct-answer (“open response”, “freeform”) version of the ARC (AI2 Reasoning Challenge) multiple-choice dataset. While ARC has been influential in the community, its multiple-choice format is unrepresentative of real-world…

  • COMET-ATOMIC 2020: On Symbolic and Neural Commonsense Knowledge Graphs

    Jena D. Hwang, Chandra Bhagavatula, Ronan Le Bras, Jeff Da, Keisuke Sakaguchi, Antoine Bosselut, Yejin ChoiAAAI • 2021 Recent years have brought about a renewed interest in commonsense representation and reasoning in the field of natural language understanding. The development of new commonsense knowledge graphs (CSKG) has been central to these advances as their diverse facts…
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