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cs.CL2025
Refract ICL: Rethinking Example Selection in the Era of Million-Token Models
Arjun R. Akula, Kazuma Hashimoto, Krishna Srinivasan +3
The emergence of long-context large language models (LLMs) has enabled the use of hundreds, or even thousands, of demonstrations for in-context learning (ICL) - a previously imprac…
cs.CL2024
Comparative Analysis of Different Efficient Fine Tuning Methods of Large Language Models (LLMs) in Low-Resource Setting
Krishna Prasad Varadarajan Srinivasan, Prasanth Gumpena, Madhusudhana Yattapu +1
In the domain of large language models (LLMs), arXiv:2305.16938 showed that few-shot full-model fine-tuning -- namely Vanilla Fine Tuning (FT) and Pattern-Based Fine Tuning (PBFT)…