Papers by Zhongzhi Luan

2 papers
Scaling Sentence Embeddings with Large Language Models (2024.findings-emnlp)

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Challenge: Current methods based on contrastive learning have generated high-quality sentence embeddings.
Approach: They propose a method to enhance LLM performance on sentence embeddings with a one-word limitation.
Outcome: The proposed method outperforms contrastive learning methods on sentence embeddings without fine-tuning and with fine-untun.
On Domain-Adaptive Post-Training for Multimodal Large Language Models (2025.findings-emnlp)

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Challenge: Adapting general multimodal large language models to specific domains is important for practical applications.
Approach: They investigate domain adaptation of multimodal large language models via post-training . they develop a generate-then-filter pipeline that curates diverse visual instruction tasks .
Outcome: The proposed model outperforms existing models in domain adaptation by combining data from open-source models with training pipelines.

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