✳flâneur — a map of the web's best reading
Direct Nash Optimization: Teaching Language Models to Self-Improve with General Preferences
arxiv.org · saved by 1 readers
N/A
Explore this link on the map →related reading
- GitHub - brexhq/prompt-engineering: Tips and tricks for working with Large Language Models like OpenAI's GPT-4. · GitHubgithub.com
- GitHub - jacobhilton/deep_learning_curriculum: Language model alignment-focused deep learning curriculum · GitHubgithub.com
- GitHub - guidance-ai/guidance: A guidance language for controlling large language models. · GitHubgithub.com
- Parsed | Custom, interpretable AI systems that continuously learnparsed.com
- GitHub - karpathy/nanochat: The best ChatGPT that $100 can buy. · GitHubgithub.com
- GitHub - google-research/tuning_playbook: A playbook for systematically maximizing the performance of deep learning models. · GitHubgithub.com
- GitHub - affaan-m/ECC: The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond. · GitHubgithub.com
- GitHub - karpathy/autoresearch: AI agents running research on single-GPU nanochat training automatically · GitHubgithub.com
- GitHub - x1xhlol/system-prompts-and-models-of-ai-tools: FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Tragithub.com
- Meta-Prompt: A Simple Self-Improving Language Agentnoahgoodman.substack.com
- GitHub - openai/parameter-golf: Train the smallest LM you can that fits in 16MB. Best model wins! · GitHubgithub.com
- GitHub - f/prompts.chat: f.k.a. Awesome ChatGPT Prompts. Share, discover, and collect prompts from the community. Free and open source — self-host for your organization with complete privacy. · GitHubgithub.com