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cs.LG2025
Contextually Guided Transformers via Low-Rank Adaptation
Andrey Zhmoginov, Jihwan Lee, Max Vladymyrov +1
Large Language Models (LLMs) based on Transformers excel at text processing, but their reliance on prompts for specialized behavior introduces computational overhead. We propose a…
cs.LG2025
Projectable Models: One-Shot Generation of Small Specialized Transformers from Large Ones
Andrey Zhmoginov, Jihwan Lee, Mark Sandler
Modern Foundation Models (FMs) are typically trained on corpora spanning a wide range of different data modalities, topics and downstream tasks. Utilizing these models can be very…