<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> This repository is a curated collection of research papers detailing adaptation strategies for agentic AI systems. It serves as a comprehensive resource for researchers and practitioners seeking to understand the evolving landscape of AI agent adaptation techniques, providing a structured overview of recent advancements and methodologies.

How It Works

This repository functions as a comprehensive, curated bibliography of research papers focused on adaptation strategies for agentic AI systems. It systematically categorizes advancements into Agent Adaptation (e.g., Tool Execution Signaled, Agent Output Signaled) and Tool Adaptation (Agent-Agnostic, Agent-Supervised). The data is presented through detailed timelines, mapping methods to their respective venues, tasks, tools, agent backbones, and tuning techniques, offering a structured overview of the field's evolution.

Quick Start & Requirements

This repository is a collection of research papers and does not provide runnable code or direct installation instructions.

Highlighted Details

• Task Breadth: Encompasses a wide array of applications, including formal theorem proving, coding, complex question answering (QA), web navigation, recommendation systems, and scientific research.
• Methodological Trends: Demonstrates a significant focus on Reinforcement Learning (RL) techniques like GRPO and PPO, alongside Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO), particularly evident in recent (2024-2025) research entries.
• Model Diversity: Showcases the integration and adaptation of numerous state-of-the-art Large Language Models (LLMs) as agent backbones, including various versions of Qwen, LLaMA, GPT, Mistral, and others.
• Tooling Ecosystem: Features extensive research into both agent-agnostic and agent-supervised tool adaptation, detailing the use of diverse tools such as code interpreters, search engines, SQL engines, and specialized APIs for enhanced agent capabilities.

Maintenance & Community

Contributions are welcomed via Pull Requests to add new papers or update entries. No specific community channels (Discord, Slack) or active maintainer information beyond the paper authors are listed.

Licensing & Compatibility

No license information is provided in the README.

Limitations & Caveats

This repository serves as a research collection and does not provide executable code or direct implementation guidance. The accompanying paper is noted as "Ongoing Work," indicating the research landscape is dynamic and subject to further development. Information is presented in tabular format, requiring manual extraction or custom parsing for detailed analysis or direct application.