Stop Jostling: Adaptive Negative Sampling Reduces the Marginalization of Low-Resource Language Tokens by Cross-Entropy Loss
停止推搡：自适应负采样减少交叉熵损失对低资源语言标记的边缘化
AI总结 本文提出自适应负采样技术，通过减少交叉熵损失对低资源语言标记的边缘化影响，提升模型对低资源语言的表示能力。
Comments Accepted at LoResLM 2025 (COLING 2025 workshop). Oral presentation
Journal ref In Proceedings of the First Workshop on Language Models for Low-Resource Languages (LoResLM 2025), pages 373-386, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics
