elvis (@omarsar0)

Universal CLAUDE.md Claims to cut Claude output tokens by 63%! Drop-in. No code changes. CLAUDE.md is one of the best ways to steer Claude Code. Not surprised to see the efficiency reported here. <a target="_blank" href="https://github.com/drona23/claude-token-efficient" color="blue">github.com/...

Another impressive paper by Google DeepMind. It takes a closer look at the limits of embedding-based retrieval. If you work with vector embeddings, bookmark this one. Let's break down the technical details: ...

Overview of Self-Evolving Agents There is a huge interest in moving from hand-crafted agentic systems to lifelong, adaptive agentic ecosystems. What's the progress, and where are things headed? Let's find out: ...

Fine-tuning LLM Agents without Fine-tuning LLMs Catchy title and very cool memory technique to improve deep research agents. Great for continuous, real-time learning without gradient updates. Here are my notes: ...

Has GPT-5 Achieved Spatial Intelligence? GPT-5 sets SoTA but not human‑level spatial intelligence. My notes below: ...

Hierarchical Reasoning Model This is one of the most interesting ideas on reasoning I've read in the past couple of months. It uses a recurrent architecture for impressive hierarchical reasoning. Here are my notes: ...

Graph-R1 New RAG framework just dropped! Combines agents, GraphRAG, and RL. Here are my notes: ...

How much do LLMs memorize? Meta and collaborators suggest that they can estimate model capacity by measuring memorization. "Models in the GPT family have an approximate capacity of 3.6 bits-per-parameter." Once capacity fills, generalization begins! More in my notes below: ...

LLMs Get Lost in Multi-turn Conversation The cat is out of the bag. Pay attention, devs. This is one of the most common issues when building with LLMs today. Glad there is now paper to share insights. Here are my notes: ...