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Boosting Data Utilization for Multilingual Dense Retrieval Sep 28, 2025

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FLAME: Frozen Large Language Models Enable Data-Efficient Language-Image Pre-training
Randomly Removing 50% of Dimensions in Text Embeddings has Minimal Impact on Retrieval and Classification Tasks
LoSiA: Efficient High-Rank Fine-Tuning via Subnet Localization and Optimization
Analyzing the Effects of Supervised Fine-Tuning on Model Knowledge from Token and Parameter Levels
Training LLMs to be Better Text Embedders through Bidirectional Reconstruction

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LLM DataAug Hard Negative Sampling dense retrieval haullcination LLM Agent text-image retrieval contrastive learning dual encoder embedding model

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LLM DataAug Hard Negative Sampling dense retrieval haullcination LLM Agent text-image retrieval contrastive learning dual encoder embedding model

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