mlsanityData to 7 Oct 2026

Towards AGI A Pragmatic Approach Towards Self Evolving Agent

arXiv 2601.11658 ↗First posted 15 Jan 2026cs.CL cs.AIcited by 2

On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks

Abstract (arXiv)

Large Language Model (LLM) based agents are powerful yet fundamentally static after deployment, lacking the ability to autonomously expand capabilities, generate new tools, or evolve their reasoning. This work introduces a hierarchical self-evolving multi-agent framework that integrates a Base LLM, an operational SLM agent, a Code-Generation LLM, and a Teacher-LLM to enable continuous adaptation. The workflow begins with the agent attempting a task using reasoning and existing tools; if unsuccessful, it escalates to tool synthesis through the Code-Gen LLM, and when failures persist, it triggers an evolution phase using Curriculum Learning (CL), Reward-Based Learning (RL), or Genetic Algorithm (GA) evolution. Using the TaskCraft dataset rich in hierarchical tasks, tool-use traces, and difficulty scaling we evaluate these paradigms. CL delivers fast recovery and strong generalization, RL excels on high-difficulty tasks, and GA offers high behavioral diversity. Across all settings, evolved agents outperform their originals, demonstrating robust, autonomous, self-improving agentic evolution.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 29 of its 35 references that are in the map. First posted on arXiv 15 Jan 2026.

Builds on

29 of 35 references.

Closest ancestors · 6

Same direction, newest first

  1. 2025A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems10 Aug
  2. 2025SEAgent: Self-Evolving Computer Use Agent with Autonomous Learning from Experience6 Aug
  3. 2025MAS-GPT: Training LLMs to Build LLM-based Multi-Agent Systems5 Mar
  4. 2024Agent Q: Advanced Reasoning and Learning for Autonomous AI Agents13 Aug
  5. 2024Symbolic Learning Enables Self-Evolving Agents26 Jun
  6. 2024EvoAgent: Towards Automatic Multi-Agent Generation via Evolutionary Algorithms20 Jun

Other references · 23

  1. 2020ALFWorld: Aligning Text and Embodied Environments for Interactive Learningcited by 1,143
  2. 2024Tulu 3: Pushing Frontiers in Open Language Model Post-Trainingcited by 988
  3. 2018MultiWOZ -- A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modellingcited by 760
  4. 2024Self-Rewarding Language Modelscited by 654
  5. 2025Absolute Zero: Reinforced Self-play Reasoning with Zero Datacited by 323
  6. 2018TextWorld: A Learning Environment for Text-based Gamescited by 304
  7. 2022ScienceWorld: Is your Agent Smarter than a 5th Grader?cited by 298
  8. 2023ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solvingcited by 276
  9. 2024WebRL: Training LLM Web Agents via Self-Evolving Online Curriculum Reinforcement Learningcited by 243
  10. 2018BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learningcited by 238
  11. 2024DeepSeek-Prover: Advancing Theorem Proving in LLMs through Large-Scale Synthetic Datacited by 225
  12. 2025R-Zero: Self-Evolving Reasoning LLM from Zero Datacited by 210
11 more
  1. 2025Self-Evolving Curriculum for LLM Reasoningcited by 107
  2. 2024NExT: Teaching Large Language Models to Reason about Code Executioncited by 60
  3. 2025Multi-Agent Evolve: LLM Self-Improve through Co-evolutioncited by 58
  4. 2024Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizingcited by 49
  5. 2024Diving into Self-Evolving Training for Multimodal Reasoningcited by 31
  6. 2025Agents of Change: Self-Evolving LLM Agents for Strategic Planningcited by 20
  7. 2024Self-Evolved Reward Learning for LLMscited by 16
  8. 2025Towards Agentic Self-Learning LLMs in Search Environmentcited by 8
  9. 2025ALAS: Autonomous Learning Agent for Self-Updating Language Modelscited by 6
  10. 2025The Path of Self-Evolving Large Language Models: Achieving Data-Efficient Learning via Intrinsic Feedbackcited by 6
  11. 2024Auto-Evolve: Enhancing Large Language Model's Performance via Self-Reasoning Frameworkcited by 4

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systemscited by 5
  2. 2026Agentic AI, Retrieval-Augmented Generation, and the Institutional Turn: Legal Architectures and Financial Governance in the Age of Distributional AGIcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Agent0: Unleashing Self-Evolving Agents from Zero Data via Tool-Integrated Reasoning
  2. 2025A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence
  3. 2024A Survey on Self-Evolution of Large Language Models
  4. 2026Tool-R0: Self-Evolving LLM Agents for Tool-Learning from Zero Data
  5. 2025Evolving in Tasks: Empowering the Multi-modality Large Language Model as the Computer Use Agent
  6. 2026Learning What to Remember and What to Internalize in LLM Self-Evolution via Adaptive Memory-Parameter Coordination
  7. 2024AgentGym: Evolving Large Language Model-based Agents across Diverse Environments
  8. 2025SE-Agent: Self-Evolution Trajectory Optimization in Multi-Step Reasoning with LLM-Based Agents