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New Research Questions Source Language Effectiveness in Cross-Lingual ICL

By PulseAugur Editorial · [2 sources] ·

A new paper on arXiv explores the effectiveness of source languages in cross-lingual in-context learning (ICL). The study challenges the assumption that insights from traditional supervised fine-tuning directly apply to ICL, finding that conventional heuristics for selecting source languages may not be optimal. The research analyzes language confusion as a key obstacle for generative tasks in cross-lingual ICL and proposes alternative methods for effective source language selection. AI

IMPACT Challenges existing assumptions about cross-lingual transfer in few-shot learning, potentially guiding future research and model development.

RANK_REASON The cluster contains a research paper submitted to arXiv detailing empirical study results.

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

New Research Questions Source Language Effectiveness in Cross-Lingual ICL

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · Fred Philippy, Siwen Guo, Jacques Klein, Tegawend\'e F. Bissyand\'e ·

    When English Isn't the Best Teacher: Source Language Effects in Cross-Lingual In-Context Learning

    arXiv:2606.18033v1 Announce Type: cross Abstract: Cross-lingual transfer in multilingual NLP has been widely explored in supervised fine-tuning contexts, where factors like data availability and linguistic similarity largely determine transfer quality. As the field shifts toward …

  2. arXiv cs.AI TIER_1 English(EN) · Tegawendé F. Bissyandé ·

    When English Isn't the Best Teacher: Source Language Effects in Cross-Lingual In-Context Learning

    Cross-lingual transfer in multilingual NLP has been widely explored in supervised fine-tuning contexts, where factors like data availability and linguistic similarity largely determine transfer quality. As the field shifts toward few-shot In-Context Learning (ICL), it is often pr…

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