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AutoL2S: Auto Long-Short Reasoning for Efficient Large Language Models

Year: 2026

Type: conference-paper

Abstract: Feng Luo, Yu-Neng Chuang, Guanchu Wang, Hoang Anh Duy Le, Shaochen Zhong, Hongyi Liu, Jiayi Yuan, Yang Sui, Vladimir Braverman, Vipin Chaudhary, Xia Hu. Findings of the Association for Computational Linguistics: ACL 2026. 2026.

Source: Findings of the Association for Computational Linguistics: ACL (Findings of ACL)

DOI: 10.18653/v1/2026.findings-acl.831

Authors: Feng Luo, Yu-Neng Chuang, Guanchu Wang, Hoang Anh Duy Le, Shaochen Zhong, Hongyi Liu, Jiayi Yuan, Yang Sui, Vladimir Braverman, Vipin Chaudhary, Xia Hu

Institutions: Rice University, University of North Carolina at Charlotte, Johns Hopkins University, Case Western Reserve University

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

Funders: National Science Foundation, U.S. Department of Transportation, Case Western Reserve University

Awards: AI Institute for Intelligent CyberInfrastructure with Computational Learning in the Environment (ICICLE), MRI: Acquisition of Artificial Intelligence Super Computer (AISC) for Accelerating Scientific Discovery, G2511287653, Collaborative Research: SCIPE: Interdisciplinary Research Support Community for Artificial Intelligence and Data Sciences

OpenAlex ID: W4416048746

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