Author

J. Hsiao

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Jul 2026

Fine-grained CLIP fine-tuning with self-annotated region alignment

SFF-CLIP (Self-annotated Fine-grained Fine-tuning for CLIP), which only uses image-text pairs as input to boost the fine-grained representation ability in the CLIP fine-tuning, while maintaining the global visual-semantic consistency.

Chen-Yang Zhao, Wei Lin, Antoni B. Chan et al. · arXiv.org · 0 citations

Preprint Jul 2026

Explaining and Tuning Transformer-based LLMs in Arithmetic Tasks with Human Strategies

The findings reveal that transformer-based large language models exhibit learning patterns similar to those of human learners, with a faster learning speed for simpler subtasks compared to more complex ones, which suggests that transformer-based LLMs may share cognitive processes with human learners in arithmetic.

Luyu Qiu, Jianing Li, Hwanhee Kim et al. · 0 citations