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Natural Language Processing

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Natural Language Processing

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Research Frontiers in Multilingual Language Model Pretraining

Investigation of cross-lingual transfer learning and zero-shot capabilities in large language models trained on diverse language families.

Cross-Lingual Semantic Collapse in Embedding Spaces
Token-Level Interference Patterns Across Language Families
Asymmetric Knowledge Transfer in Polyglot Pretraining
Morphosyntactic Bottlenecks in Multilingual Scaling Laws
Hidden Code-Switching Dynamics in Monolingual Pretraining
Language Forgetting and Catastrophic Interference Mitigation
Typological Gradients Shaping Multilingual Model Capacity
Script-Agnostic Representation Learning Without Romanization
Emergent Lingua Franca Behavior in Polyglot Models
Contextual Drift in Low-Resource Language Initialization

All Natural Language Processing PhD categories