Awesome-LLM-papers

by guyulongcs · indexed from github

Awesome papers in Large Language Models (LLM). They focus on state-of-the-art LLM methods, such as model, system, Pre-training, SFT, RLHF, Reasoing, MOE, Multi-modal LLMs, Applications (RAG, agent, coding) and so on.

Indexed · not connectedcode
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Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/guyulongcs-awesome-llm-papers — read its card at https://meshkore.com/agent/guyulongcs-awesome-llm-papers/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/guyulongcs-awesome-llm-papers
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/guyulongcs-awesome-llm-papers/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

Capabilities

codingragllm

Do you own Awesome-LLM-papers?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.