VentureBeat

Fine-tuning vs. in-context learning: New research guides better LLM customization for real-world tasks

Two popular approaches for customizing large language models (LLMs) for downstream tasks are fine-tuning and in-context learning (ICL ...
Semiconductor Engineering

Largest High-Quality Verilog Dataset for LLM Fine-Tuning (Univ. of Florida)

A new technical paper titled “VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL ...
VentureBeat

This new framework lets LLM agents learn from experience, no fine-tuning required

A new learning paradigm developed by University College London (UCL) and Huawei Noah’s Ark Lab enables large language model ...