Papers
See AI2's Award Winning Papers
Learn more about AI2's Lasting Impact Award
Viewing 511-520 of 996 papers
GridToPix: Training Embodied Agents with Minimal Supervision
Unnat Jain, Iou-Jen Liu, S. Lazebnik, Aniruddha Kembhavi, Luca Weihs, A. SchwingICCV • 2021 While deep reinforcement learning (RL) promises freedom from hand-labeled data, great successes, especially for Embodied AI, require significant work to create supervision via carefully shaped rewards. Indeed, without shaped rewards, i.e., with only terminal…“I’m Not Mad”: Commonsense Implications of Negation and Contradiction
Liwei Jiang, Antoine Bosselut, Chandra Bhagavatula, Yejin ChoiNAACL • 2021 Natural language inference requires reasoning about contradictions, negations, and their commonsense implications. Given a simple premise (e.g., “I’m mad at you”), humans can reason about the varying shades of contradictory statements ranging from…Learning Curves for Analysis of Deep Networks
Derek Hoiem, Tanmay Gupta, Zhizhong Li, Michal Shlapentokh-Rothman arXiv • 2021 A learning curve models a classifier's test error as a function of the number of training samples. Prior works show that learning curves can be used to select model parameters and extrapolate performance. We investigate how to use learning curves to analyze…Visual Semantic Role Labeling for Video Understanding
Arka Sadhu, Tanmay Gupta, Mark Yatskar, R. Nevatia, Aniruddha Kembhavi CVPR • 2021 We propose a new framework for understanding and representing related salient events in a video using visual semantic role labeling. We represent videos as a set of related events, wherein each event consists of a verb and multiple entities that fulfill…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…