Papers by Alvin C Grissom II

2 papers
Disentangling Linguistic Relatedness from Task Alignment in Cross-Lingual Transfer (2026.acl-srw)

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Challenge: Large language models (LLMs) have advanced natural language processing, yet their benefits remain concentrated in English and a small number of high-resource languages.
Approach: They fine-tuned large language models (4B–671B parameters) on Arabic and evaluated zero-shot reading comprehension on Semitic languages and non-Semitic controls.
Outcome: The results show that models with weak baselines improve across all languages, whereas strong-baseline models show only marginal gains regardless of language family.
An Interdisciplinary Approach to Human-Centered Machine Translation (2025.emnlp-main)

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Challenge: Despite progress in MT, a gap persists between how the technology is developed and how it is used in real-world contexts.
Approach: They propose a human-centered approach to machine translation (MT) they argue that MT should be evaluated with diverse goals and contexts of use .
Outcome: The proposed approach emphasizes alignment of evaluation and design with diverse communicative goals and contexts of use.

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