REPOGEO REPORT · LITE
xhyumiracle/Awesome-AgenticLLM-RL-Papers
Default branch main · commit 30061293 · scanned 5/15/2026, 12:44:09 PM
GitHub: 1,766 stars · 78 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface xhyumiracle/Awesome-AgenticLLM-RL-Papers, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highabout#1Add a concise description to the repository's About section
Why:
COPY-PASTE FIXA comprehensive, curated collection of research papers and resources on Agentic Reinforcement Learning for Large Language Models (LLMs), serving as the official repository for 'The Landscape of Agentic Reinforcement Learning for LLMs: A Survey'.
- highreadme#2Refine the README's opening sentence to emphasize its role as a collection
Why:
CURRENTThis is the Official repo for the survey paper: The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
COPY-PASTE FIXThis repository serves as the official, curated collection of research papers and resources for the survey: 'The Landscape of Agentic Reinforcement Learning for LLMs'.
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- Generative Agents: Interactive Simulacra of Human Behavior · recommended 2×
- Voyager: An Open-Ended Embodied Agent with Large Language Models · recommended 1×
- Reflexion: Language Agents with Reinforcement Learning Fine-Tuning · recommended 1×
- RLHF-V: Towards Reliable Large Language Models via RLHF with Value Alignment · recommended 1×
- Language Models as Zero-Shot Reinforcement Learners · recommended 1×
- CATEGORY QUERYWhat are the latest research papers on combining large language models with reinforcement learning agents?you: not recommendedAI recommended (in order):
- Voyager: An Open-Ended Embodied Agent with Large Language Models
- Reflexion: Language Agents with Reinforcement Learning Fine-Tuning
- Generative Agents: Interactive Simulacra of Human Behavior
- RLHF-V: Towards Reliable Large Language Models via RLHF with Value Alignment
- Language Models as Zero-Shot Reinforcement Learners
- Large Language Models as General Pattern Machines
- Guiding Large Language Models with RL: A Survey
AI recommended 7 alternatives but never named xhyumiracle/Awesome-AgenticLLM-RL-Papers. This is the gap to close.
Show full AI answer
- CATEGORY QUERYWhere can I find a comprehensive survey on agentic reinforcement learning algorithms for LLMs?you: not recommendedAI recommended (in order):
- A Survey of Large Language Models in Reinforcement Learning
- Generative Agents: Interactive Simulacra of Human Behavior
- Foundation Models for Decision Making: Problems, Methods, and Opportunities
- Prompting Large Language Models for Autonomous Agent Systems: A Survey
- Reinforcement Learning from Human Feedback (RLHF): A Survey
- LLM-as-a-Judge: A Comprehensive Survey
AI recommended 6 alternatives but never named xhyumiracle/Awesome-AgenticLLM-RL-Papers. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenessfail
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of xhyumiracle/Awesome-AgenticLLM-RL-Papers?passAI did not name xhyumiracle/Awesome-AgenticLLM-RL-Papers — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts xhyumiracle/Awesome-AgenticLLM-RL-Papers in production, what risks or prerequisites should they evaluate first?passAI named xhyumiracle/Awesome-AgenticLLM-RL-Papers explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo xhyumiracle/Awesome-AgenticLLM-RL-Papers solve, and who is the primary audience?passAI did not name xhyumiracle/Awesome-AgenticLLM-RL-Papers — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
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xhyumiracle/Awesome-AgenticLLM-RL-Papers — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite