mlsanityData to 14 Oct 2026

MIMIR: A Streamlined Platform for Personalized Agent Tuning in Domain Expertise

arXiv 2404.04285 ↗First posted 3 Apr 2024cs.CL cs.AIcited by 2

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

Abstract (arXiv)

Recently, large language models (LLMs) have evolved into interactive agents, proficient in planning, tool use, and task execution across a wide variety of tasks. However, without specific agent tuning, open-source models like LLaMA currently struggle to match the efficiency of GPT- 4, particularly given the scarcity of agent-tuning datasets for fine-tuning. In response, we introduce textscMimir: a streamlined platform offering a customizable pipeline that enables users to leverage both private knowledge and publicly available, legally compliant datasets at scale for personalized agent tuning. Additionally, textscMimir supports the generation of general instruction-tuning datasets from the same input. This dual capability ensures that language agents developed through the platform possess both specific agent abilities and general competencies. textscMimir integrates these features into a cohesive end-to-end platform, facilitating everything from the uploading of personalized files to one-click agent fine-tuning.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 25 of its 42 references that are in the map. First posted on arXiv 3 Apr 2024.

Builds on

25 of 42 references.

Closest ancestors · 3

Same direction, newest first

  1. 2023AgentTuning: Enabling Generalized Agent Abilities for LLMs19 Oct
  2. 2023FireAct: Toward Language Agent Fine-tuning9 Oct
  3. 2023Agents: An Open-source Framework for Autonomous Language Agents14 Sep

Other references · 22

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,380
  2. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  3. 2020Measuring Massive Multitask Language Understandingcited by 7,963
  4. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  5. 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,182
  6. 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,568
  7. 2022Self-Instruct: Aligning Language Models with Self-Generated Instructionscited by 2,724
  8. 2023ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIscited by 1,947
  9. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
  10. 2020What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Examscited by 1,356
  11. 2019PubMedQA: A Dataset for Biomedical Research Question Answeringcited by 1,288
  12. 2022Measuring and Narrowing the Compositionality Gap in Language Modelscited by 1,075
10 more
  1. 2023Enhancing Chat Language Models by Scaling High-quality Instructional Conversationscited by 839
  2. 2023Can Large Language Models Be an Alternative to Human Evaluations?cited by 734
  3. 2023Towards Expert-Level Medical Question Answering with Large Language Modelscited by 384
  4. 2023Principle-Driven Self-Alignment of Language Models from Scratch with Minimal Human Supervisioncited by 318
  5. 2023MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoningcited by 316
  6. 2024CodeAgent: Enhancing Code Generation with Tool-Integrated Agent Systems for Real-World Repo-level Coding Challengescited by 282
  7. 2023Camels in a Changing Climate: Enhancing LM Adaptation with Tulu 2cited by 229
  8. 2023HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledgecited by 162
  9. 2023Human-like Summarization Evaluation with ChatGPTcited by 126
  10. 2023Evil Geniuses: Delving into the Safety of LLM-based Agentscited by 106

Built on by

Cited by year

Citing papers per year: 2024: 1; 2025: 1.

2 papers.

  1. 2024Direct Multi-Turn Preference Optimization for Language Agentscited by 64
  2. 2025Iterative Tool Usage Exploration for Multimodal Agents via Step-wise Preference Tuningcited by 19

Similar, not cited

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  1. 2025AgentRefine: Enhancing Agent Generalization through Refinement Tuning
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  3. 2025Agent Fine-tuning through Distillation for Domain-specific LLMs in Microdomains
  4. 2026SkillAdaptor: Self-Adapting Skills for LLM Agents from Trajectories
  5. 2025PersonaAgent: Bridging Memory and Action for Personalized LLM Agents
  6. 2026Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
  7. 2026FT-Dojo: Towards Autonomous LLM Fine-Tuning with Language Agents
  8. 2025MinionsLLM: a Task-adaptive Framework For The Training and Control of Multi-Agent Systems Through Natural Language