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of 43
pro vyhledávání: '"Norouzi, Narges"'
This work presents Adaptive Local-then-Global Merging (ALGM), a token reduction method for semantic segmentation networks that use plain Vision Transformers. ALGM merges tokens in two stages: (1) In the first network layer, it merges similar tokens w
Externí odkaz:
http://arxiv.org/abs/2406.09936
Chatbot interfaces for LLMs enable students to get immediate, interactive help on homework assignments, but even a thoughtfully-designed bot may not serve all pedagogical goals. In this paper, we report on the development and deployment of a GPT-4-ba
Externí odkaz:
http://arxiv.org/abs/2406.05600
Autor:
Qi, Laryn, Zamfirescu-Pereira, J. D., Kim, Taehan, Hartmann, Björn, DeNero, John, Norouzi, Narges
We evaluate an automatic hint generator for CS1 programming assignments powered by GPT-4, a large language model. This system provides natural language guidance about how students can improve their incorrect solutions to short programming exercises.
Externí odkaz:
http://arxiv.org/abs/2406.05603
In today's rapidly evolving educational landscape, traditional modes of passive information delivery are giving way to transformative pedagogical approaches that prioritize active student engagement. Within the context of large-scale hybrid classroom
Externí odkaz:
http://arxiv.org/abs/2311.10746
Autor:
Schwartz, Jordan, Bohannan, Madison, Yim, Jacob, Tang, Yuerou, Benedicto, Dana, Liu, Charisse, Fox, Armando, Yan, Lisa, Norouzi, Narges
In this work, we present the development of an automated extension tool to assist educators and increase the success and well-being of students by implementing flexible extension policies. Flexible extension policies materialize in many ways, yet the
Externí odkaz:
http://arxiv.org/abs/2311.00152
Autor:
Carrión, Héctor, Norouzi, Narges
Skin diseases affect millions of people worldwide, across all ethnicities. Increasing diagnosis accessibility requires fair and accurate segmentation and classification of dermatology images. However, the scarcity of annotated medical images, especia
Externí odkaz:
http://arxiv.org/abs/2307.11654
Autor:
Carrión, Héctor, Jafari, Mohammad, Yang, Hsin-Ya, Isseroff, Roslyn Rivkah, Rolandi, Marco, Gomez, Marcella, Norouzi, Narges
Identifying, tracking, and predicting wound heal-stage progression is a fundamental task towards proper diagnosis, effective treatment, facilitating healing, and reducing pain. Traditionally, a medical expert might observe a wound to determine the cu
Externí odkaz:
http://arxiv.org/abs/2206.10536
Fashion is now among the largest industries worldwide, for it represents human history and helps tell the worlds story. As a result of the Fourth Industrial Revolution, the Internet has become an increasingly important source of fashion information.
Externí odkaz:
http://arxiv.org/abs/2204.03998
The automatic analysis of subtle changes between longitudinal MR images is an important task as it is still a challenging issue in scope of the breast medical image processing. In this paper we propose an effective automatic change detection framewor
Externí odkaz:
http://arxiv.org/abs/2110.10242
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