3 papers
cs.CL2026
Why Better Cross-Lingual Alignment Fails for Better Cross-Lingual Transfer: Case of Encoders
Yana Veitsman, Yihong Liu, Hinrich Schütze
Better cross-lingual alignment is often assumed to yield better cross-lingual transfer. However, explicit alignment techniques -- despite increasing embedding similarity -- frequen…
cs.LG2025
Born a Transformer -- Always a Transformer? On the Effect of Pretraining on Architectural Abilities
Mayank Jobanputra, Yana Veitsman, Yash Sarrof +4
Transformers have theoretical limitations in modeling certain sequence-to-sequence tasks, yet it remains largely unclear if these limitations play a role in large-scale pretrained…
cs.CL2025
Contextualize-then-Aggregate: Circuits for In-Context Learning in Gemma-2 2B
Aleksandra Bakalova, Yana Veitsman, Xinting Huang +1
In-Context Learning (ICL) is an intriguing ability of large language models (LLMs). Despite a substantial amount of work on its behavioral aspects and how it emerges in miniature s…