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Rethinking the Privacy of Text Embeddings: A Reproducibility Study of “Text Embeddings Reveal (Almost) As Much As Text”
2025
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LLM Evaluators Recognize and Favor Their Own Generations
2024
[5]
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
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Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement
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Text Embeddings Reveal (Almost) As Much As Text
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Towards General Text Embeddings with Multi-stage Contrastive Learning
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Sentence Embedding Leaks More Information than You Expect: Generative Embedding Inversion Attack to Recover the Whole Sentence
2023
[11]
Vision-Language Models for Vision Tasks: A Survey
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Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing
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Information Leakage in Embedding Models
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[18]
Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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