Awesome Adaptation Agentic AI

Awesome Adaptation of Agentic AI

Skill by ara.so — AI Agent Skills collection.

Overview

This repository is a curated research collection accompanying the paper "Adaptation of Agentic AI" (arXiv:2512.16301). It systematically organizes papers on how AI agents adapt their behavior, particularly focusing on:

• Agent Adaptation: Methods to improve agent decision-making through tool execution signals (A1) or output signals (A2)
• Tool Adaptation: Approaches to optimize tools either independently (T1) or with agent supervision (T2)

The collection categorizes 40+ research papers by adaptation strategy, training method (RL, SFT, DPO), task domain, and implementation details.

Repository Structure

awesome-adaptation-of-agentic-ai/
├── README.md                 # Main paper collection with categorized tables
├── images/
│   ├── intro.png            # Overview diagram
│   ├── a1_illustrate.png    # Tool execution signaled adaptation
│   ├── a1_timeline.png      # Development timeline
│   ├── paper_icon.png       # Paper link icons
│   └── code_icon.png        # Code link icons
└── LICENSE

Installation & Usage

Cloning the Repository

# Clone the repository
git clone https://github.com/pat-jj/Awesome-Adaptation-of-Agentic-AI.git
cd Awesome-Adaptation-of-Agentic-AI

# View the main README
cat README.md

Browsing Papers

The repository organizes papers into four main categories:

1. A1: Tool Execution Signaled Agent Adaptation

   • RL-based methods (GRPO, PPO, AlphaZero-like)
   • SFT & DPO methods

2. A2: Agent Output Signaled Adaptation

   • Coming in future updates

3. T1: Agent-Agnostic Tool Adaptation

   • Coming in future updates

4. T2: Agent-Supervised Tool Adaptation

   • Coming in future updates

Key Research Categories

A1: Tool Execution Signaled (RL-Based)

Papers where agents learn from tool execution feedback using reinforcement learning:

Notable Methods:

• Orion (2025.11): IR agents with GRPO on LFM2
• DeepSeek-R1-Zero (2025.01): Coding agents with code executor feedback
• DeepSeek-Prover-V2 (2025.04): Formal theorem proving with Lean compiler
• FTRL (2025.08): Multi-step tool-use with GRPO

Common Pattern:

Agent → Tool Call → Execution Feedback → RL Update (GRPO/PPO)

A1: Tool Execution Signaled (SFT & DPO)

Papers using supervised fine-tuning and direct preference optimization:

Notable Methods:

• ToolLLM (2023.07): API planning with real-world APIs
• RetPO (2024.02): Information retrieval with DPO
• AWL (2024.12): Scientific reasoning with adaptive learning

Common Pattern:

Agent → Tool Call → Execution Trace → Supervised Learning

Common Use Cases

Finding Papers by Task

Example: Formal Theorem Proving

# Search README for theorem proving papers
grep -i "theorem proving" README.md

Papers include: AlphaProof, BFS-Prover-V2, Goedel-Prover-V2, Leanabell-Prover-V2, DeepSeek-Prover-V1.5/V2

Example: Coding & Code Execution

# Find coding-related papers
grep -i "coding\|code executor" README.md

Papers include: olmOCR2, R1-Code-Interpreter, Code-R1, DeepSeek-R1-Zero, RLEF, LeDex, CYCLE, CodeAct

Finding Papers by Method

Example: GRPO (Group Relative Policy Optimization)

# List all GRPO papers
grep "GRPO" README.md

Commonly used in: Tool-N1, DeepSeek-Prover-V2, SQL-R1, Rec-R1, DeepRetrieval, etc.

Example: DPO (Direct Preference Optimization)

# List all DPO papers
grep "DPO" README.md

Used in: AWL, LeReT, TP-LLaMA, RetPO

Finding Papers by Model Backbone

Example: Qwen2.5-based agents

# Find Qwen2.5 implementations
grep "Qwen2.5" README.md

Models include: olmOCR2, ToolExpander, BFS-Prover-V2, WebGen-Agent, Tool-R1, etc.

Accessing Paper Resources

Paper Links

All papers include arXiv or conference links:

[Paper](https://arxiv.org/abs/2512.16301)

Code Repositories

Many papers provide implementation code:

[Code](https://github.com/example/repo)

Reading Strategy

# Pseudo-code for systematic review
def research_adaptation_strategy(task_domain, method_type):
    """
    Navigate to specific adaptation category
    
    Args:
        task_domain: e.g., "coding", "theorem proving", "IR"
        method_type: "RL", "SFT", "DPO"
    
    Returns:
        List of relevant papers with links
    """
    # 1. Go to appropriate section (A1, A2, T1, T2)
    # 2. Filter by method_type (RL-based vs SFT/DPO)
    # 3. Search table for task_domain
    # 4. Check paper links, code availability, model backbones
    pass

Citation Format

When using this repository for research:

@article{jiang2025adaptation,
  title={Adaptation of Agentic AI},
  author={Jiang, Pengcheng and Lin, Jiacheng and Shi, Zhiyi and Wang, Zifeng and He, Luxi and Wu, Yichen and Zhong, Ming and Song, Peiyang and Zhang, Qizheng and Wang, Heng and others},
  journal={arXiv preprint arXiv:2512.16301},
  year={2025}
}

Contributing

The repository welcomes pull requests for:

• New papers on agentic AI adaptation
• Updates to existing paper information
• Corrections to categorizations
• Additional metadata (benchmarks, datasets)

Contribution Pattern:

# 1. Fork the repository
# 2. Add paper to appropriate category in README.md
# 3. Follow existing table format:
# | Time | Method | Venue | Task(s) | Tool(s) | Agent Backbone | Tuning |

# Example entry:
# | 2025.XX | YourMethod | Venue<br>🔗 [Paper](link)<br>💻 [Code](link) | Task | Tools | Model | Method |

# 4. Submit pull request

Key Insights from the Collection

Adaptation Taxonomy

1. Signal Type:

   • Tool execution feedback (A1)
   • Agent output quality (A2)

2. Training Methods:

   • GRPO: Group Relative Policy Optimization (most common in 2025)
   • PPO: Proximal Policy Optimization
   • AlphaZero-like: Self-play with value/policy networks
   • SFT: Supervised fine-tuning on execution traces
   • DPO: Direct preference optimization

3. Trend: Growing use of GRPO for tool-augmented agents (2025), especially with Qwen2.5 and DeepSeek models

Domain Coverage

• Coding: Code execution sandboxes (DeepSeek-R1-Zero, R1-Code-Interpreter)
• Formal Math: Lean compilers (AlphaProof, DeepSeek-Prover)
• Information Retrieval: Search engines, retrievers (DeepRetrieval, ReZero)
• Tool-Calling: API execution (ToolLLM, Tool-N1, ToolExpander)
• Web Agents: GUI interaction (WebGen-Agent)

Troubleshooting

Finding Specific Research

Q: How do I find papers using a specific model like LLaMA3?

grep -i "llama3" README.md

Q: Which papers have open-source code?

# Look for code icon in tables
grep "code_icon.png" README.md

Q: What are the most recent papers?

# Check Time column (sorted by date within categories)
# Most recent: 2025.11 (Orion), 2025.10 (olmOCR2, AlphaProof)

Understanding Abbreviations

• IR: Information Retrieval
• GRPO: Group Relative Policy Optimization
• PPO: Proximal Policy Optimization
• SFT: Supervised Fine-Tuning
• DPO: Direct Preference Optimization
• TTRL: Test-Time Reinforcement Learning
• EI: Expert Iteration

Repository Maintenance

The repository is actively maintained with:

• Last Update: 2026-05-15 (per metadata)
• Stars: 650+ (growing at ~3 stars/day)
• Open Issues: 2

For questions or issues, check: https://github.com/pat-jj/Awesome-Adaptation-of-Agentic-AI/issues

Related Resources

• Homepage: https://arxiv.org/abs/2512.16301
• License: CC BY-NC-ND 4.0 (content), NOASSERTION (code)
• Topics: adaptation, agentic-ai, large-language-models