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cs.LG2025
Enabling Fine-Grained Operating Points for Black-Box LLMs
Ege Beyazit, KL Navaneet, Prashant Mathur +3
Black-box Large Language Models (LLMs) provide practical and accessible alternatives to other machine learning methods, as they require minimal labeled data and machine learning ex…
cs.LG2024★ 1 cited
Can Contrastive Learning Refine Embeddings
Lihui Liu, Jinha Kim, Vidit Bansal
Recent advancements in contrastive learning have revolutionized self-supervised representation learning and achieved state-of-the-art performance on benchmark tasks. While most exi…