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Jonathan Rubin

2 accepted papers

2026

LinguaMap: Which Layers of LLMs Speak Your Language and How to Tune Them?

ICLR 2026poster

Despite multilingual pretraining, large language models often struggle with non-English tasks, particularly in language control--the ability to respond in the intended language. We identify and characterize two key failure modes: the *multilingual transfer bottleneck* (correct language, incorrect ta…

Cited by 0SourceScholar
2023

Entity Contrastive Learning in a Large-Scale Virtual Assistant System

ACL 2023industry

Conversational agents are typically made up of domain (DC) and intent classifiers (IC) that identify the general subject an utterance belongs to and the specific action a user wishes to achieve. In addition, named entity recognition (NER) performs per token labeling to identify specific entities of…

Cited by 1SourcePDFScholar