GenAI Learner

Discover how researchers from Google Cloud AI Research are pioneering new methods. SEARCH-R1 trains LLMs with reinforcement learning to autonomously generate multi-turn search queries. Get the non-technical breakdown on GenAI Learner. Arxiv: https://arxiv.org/abs/2503.09516

Arxiv: https://arxiv.org/abs/2510.04618 This recent paper from Stanford University and UC Berkeley introduces Agentic Context Engineering (ACE), a novel framework designed to enhance the performance of large language models (LLMs) in complex applications like agents and domain-specific reasoning by evolving their context, such as prompts and memory. ACE addresses key limitations of prior context a...

This recent MIT paper details a novel framework called Self-Adapting Language Models (SEAL), which allows large language models (LLMs) to modify their own weights through self-generated training data and update instructions, termed self-edits. The core mechanism involves an outer reinforcement learning (RL) loop that trains the model to create effective self-edits, rewarding generations that impro...

SOSP 2025 Paper READING ---- METIS: Fast Quality-Aware RAG Systems with Configuration Adaptation https://arxiv.org/pdf/2412.10543