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cs.CL2025
Fine-Tuning Large Multimodal Models for Automatic Pronunciation Assessment
Ke Wang, Wenning Wei, Yan Deng +2
Automatic Pronunciation Assessment (APA) is critical for Computer-Assisted Language Learning (CALL), requiring evaluation across multiple granularities and aspects. Large Multimoda…
cs.CL2025
Deep Contrastive Unlearning for Language Models
Estrid He, Tabinda Sarwar, Ibrahim Khalil +2
The past a few years have witnessed the great success of large language models, demonstrating powerful capabilities in comprehending textual data and generating human-like language…
cs.CL2024
A Survey on Data Synthesis and Augmentation for Large Language Models
Ke Wang, Jiahui Zhu, Minjie Ren +8
The success of Large Language Models (LLMs) is inherently linked to the availability of vast, diverse, and high-quality data for training and evaluation. However, the growth rate o…