2 papers
cs.CL2026
Fine-tuning vs. In-context Learning in Large Language Models: A Formal Language Learning Perspective
Bishwamittra Ghosh, Soumi Das, Till Speicher +5
Large language models (LLMs) operate in two fundamental learning modes - fine-tuning (FT) and in-context learning (ICL) - raising key questions about which mode yields greater lang…
cs.LG2025
Rethinking Memorization Measures and their Implications in Large Language Models
Bishwamittra Ghosh, Soumi Das, Qinyuan Wu +4
Concerned with privacy threats, memorization in LLMs is often seen as undesirable, specifically for learning. In this paper, we study whether memorization can be avoided when optim…