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检索条件"机构=Computer Science and Intelligent Systems Program"
214 条 记 录,以下是101-110 订阅
排序:
Can GPT-4 Support Analysis of Textual Data in Tasks Requiring Highly Specialized Domain Expertise?  6
Can GPT-4 Support Analysis of Textual Data in Tasks Requirin...
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6th Workshop on Automated Semantic Analysis of Information in Legal Text, ASAIL 2023
作者: Savelka, Jaromir Ashley, Kevin D. Gray, Morgan A. Westermann, Hannes Xu, Huihui Computer Science Department Carnegie Mellon University PittsburghPA United States Intelligent Systems Program University of Pittsburgh PA United States Cyberjustice Laboratory Faculté de Droit Université de Montréal Montréal Canada
We evaluated the capability of generative pre-trained transformers (GPT-4) in analysis of textual data in tasks that require highly specialized domain expertise. Specifically, we focused on the task of analyzing court... 详细信息
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Opinionfinder: A system for subjectivity analysis
Opinionfinder: A system for subjectivity analysis
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Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, HLT/EMNLP 2005, Co-located with the 2005 Document Understanding Conference, DUC and the 9th International Workshop on Parsing Technologies, IWPT
作者: Wilson, Theresa Hoffmann, Paul Somasundaran, Swapna Kessler, Jason Wiebe, Janyce Choi, Yejin Cardie, Claire Riloff, Ellen Patwardhan, Siddharth Intelligent Systems Program University of Pittsburgh Pittsburgh PA 15260 United States Department of Computer Science University of Pittsburgh Pittsburgh PA 15260 United States Department of Computer Science Cornell University Ithaca NY 14853 United States School of Computing University of Utah Salt Lake City UT 84112 United States
来源: 评论
LEATHER: A Framework for Learning to Generate Human-like Text in Dialogue
arXiv
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arXiv 2022年
作者: Sicilia, Anthony Alikhani, Malihe Intelligent Systems Program United States Computer Science Department University of Pittsburgh PittsburghPA United States
Algorithms for text-generation in dialogue can be misguided. For example, in task-oriented settings, reinforcement learning that optimizes only task-success can lead to abysmal lexical diversity. We hypothesize this i... 详细信息
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Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth
arXiv
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arXiv 2023年
作者: Gungor, Cagri Kovashka, Adriana Intelligent Systems Program University of Pittsburgh United States Department of Computer Science University of Pittsburgh United States
Despite recent attention to depth for various tasks, it is still an unexplored modality for weakly-supervised object detection (WSOD). We propose an amplifier method for enhancing the performance of WSOD by integratin... 详细信息
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Strategies to Leverage Foundational Model Knowledge in Object Affordance Grounding
Strategies to Leverage Foundational Model Knowledge in Objec...
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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)
作者: Arushi Rai Kyle Buettner Adriana Kovashka Department of Computer Science University of Pittsburgh PA USA Intelligent Systems Program University of Pittsburgh PA USA
An important task for intelligent systems is affordance grounding, where the goal is to locate regions on an object where an action can be performed. Past weakly supervised approaches learn from human-object interacti... 详细信息
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Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection
Investigating the Role of Attribute Context in Vision-Langua...
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IEEE Workshop on Applications of computer Vision (WACV)
作者: Kyle Buettner Adriana Kovashka Intelligent Systems Program University of Pittsburgh PA USA Department of Computer Science University of Pittsburgh PA USA
Vision-language alignment learned from image-caption pairs has been shown to benefit tasks like object recognition and detection. Methods are mostly evaluated in terms of how well object class names are learned, but c...
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Keyword annotation of biomedicai documents with graph-based similarity methods
Keyword annotation of biomedicai documents with graph-based ...
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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
作者: Shuguang Wang Milos Hauskrecht Intelligent Systems Program University of Pittsburgh Pittsburgh USA Department of Computer Science University of Pittsburgh Pittsburgh USA
In this paper, we present a new approach that lets us extract, and represent relations among terms (concepts) in the documents and uses these relations to support various document analysis applications. Our approach w... 详细信息
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Learning by diagramming Supreme Court oral arguments  07
Learning by diagramming Supreme Court oral arguments
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11th International Conference on Artificial Intelligence and Law
作者: Ashley, Kevin Pinkwart, Niels Lynch, Collin Aleven, Vincent LRDC School of Law University of Pittsburgh Pittsburgh PA United States Computer Science Institute Clausthal University of Technology Germany Intelligent Systems Program University of Pittsburgh Pittsburgh PA United States Human-Computer Interaction Institute Carnegie Mellon University Pittsburgh PA United States
This paper describes an intelligent tutoring system, LARGO, that helps students learn skills of legal reasoning with hypotheticals by analyzing oral arguments before the US Supreme Court. The skills involve proposing ... 详细信息
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Incorporating coherence of topics as a criterion in automatic response-to-text assessment of the organization of writing  10
Incorporating coherence of topics as a criterion in automati...
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10th Workshop on Innovative Use of NLP for Building Educational Applications, BEA 2015 at the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2015
作者: Rahimi, Zahra Litman, Diane Wang, Elaine Correnti, Richard Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Department of Computer Science University of Pittsburgh PittsburghPA15260 United States Learning Research and Development Center University of Pittsburgh PittsburghPA15260 United States
This paper presents an investigation of score prediction for the Organization dimension of an assessment of analytical writing in response to text. With the long-term goal of producing feedback for students and teache... 详细信息
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Decomposition and Causality in Partial-Order Planning  2
Decomposition and Causality in Partial-Order Planning
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2nd International Conference on Artificial Intelligence Planning systems, AIPS 1994
作者: Young, R. Michael Pollack, Martha E. Moore, Johanna D. Intelligent Systems Program University of Pittsburgh PittsburghPA15260 United States Department of Computer Science University of Pittsburgh PittsburghPA15260 United States Learning Research and Development Center University of Pittsburgh PittsburghPA15260 United States
We describe DPOCL, a partial-order causal link planner that includes action decomposition. DPOCL builds directly on the SNLP algorithm (McAllester & Rosenblitt 1991), and hence is clear and simple, and can readily... 详细信息
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