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Position Encoding with Random Float Sampling Enhances Length Generalization of Transformers

Year: 2026

Type: conference-paper

Source: Findings of the Association for Computational Linguistics: EACL

DOI: 10.18653/v1/2026.findings-eacl.261

Authors: Atsushi Shimizu, Shohei Taniguchi, Yutaka Matsuo

Language: English

Topic: Topic Modeling

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: hybrid

OpenAlex ID: W7140081622

FWCI:

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