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cs.CL2025
When Alignment Hurts: Decoupling Representational Spaces in Multilingual Models
Ahmed Elshabrawy, Hour Kaing, Haiyue Song +4
Alignment with high-resource standard languages is often assumed to aid the modeling of related low-resource varieties. We challenge this assumption by demonstrating that excessive…
cs.CL2025
Statement-Tuning Enables Efficient Cross-lingual Generalization in Encoder-only Models
Ahmed Elshabrawy, Thanh-Nhi Nguyen, Yeeun Kang +8
Large Language Models (LLMs) excel in zero-shot and few-shot tasks, but achieving similar performance with encoder-only models like BERT and RoBERTa has been challenging due to the…
cs.CL2025
Illusion or Algorithm? Investigating Memorization, Emergence, and Symbolic Processing in In-Context Learning
Jingcheng Niu, Subhabrata Dutta, Ahmed Elshabrawy +2
Large-scale Transformer language models (LMs) trained solely on next-token prediction with web-scale data can solve a wide range of tasks after seeing just a few examples. The mech…