Papersby GlyphMiniCorp: The Last Mile of the AI Agent Firm research paper by Microsoft, 2026
Microsoft · Applied AI · Oct 5, 2026 · 0 citations · 39 upvotes · unverified
What it shows
MiniCorp is an office simulator that allows researchers to study how agents run companies and generate enterprise data for training.
By Jingying Zeng, Zhenwei Dai, Jinning Li and 6 more · arXiv 2610.05912 · PDF
UnverifiedSummarised by a model from the abstract; not yet checked by hand.
More from Microsoft
All 57WebHarbor: Docking Real Websites for Evolving GUI Agent EnvironmentsWebHarbor provides realistic, containerized website environments for training and testing computer-using web agents across complex online tasks.
Microsoft28 upvotesRead →Agent World Model in the Wild: Computer-Use Agent Environment SynthesisThis pipeline creates controllable, open-source environments to safely train and test AI agents on complex, long-horizon computer-use tasks.Microsoft69 upvotesRead →Self-Evolving Coding Agents via Harness-Policy OptimizationThis framework improves coding agents by recursively alternating between optimizing the agent's policy and the environment harness it uses to interact with code.Microsoft48 upvotesRead →AesCode: Aesthetic Code Generation with Decoupled Cross-Modal RewardsThis paper introduces a method to improve code-based visual generation by using image-based aesthetic guidance and decoupled rewards to ensure quality and correctness.Microsoft137 upvotesRead →APT: Feedback-Driven Agentic Post-Training for Text-to-Image GenerationThis paper introduces an automated post-training framework that uses a feedback loop of evaluation and diagnosis to improve text-to-image models.Microsoft23 upvotesRead →LensErase: A Foundation Model for Erase AnythingThis paper introduces a foundation model designed for versatile image editing and object removal using mask-based inputs and efficient positional encoding.Microsoft52 upvotesRead →Simplifying and Improving On-Policy Distillation for Few-Step DiffusionThis paper introduces a simplified regression-based method for distilling diffusion models that improves generation speed without requiring complex training techniques.Microsoft27 upvotesRead →ActiveSaddler: Automated Curriculum Learning for Agent Harness OptimizationActiveSaddler optimizes agent training by dynamically adapting the curriculum of scenarios based on discovered failure patterns.Microsoft86 upvotesRead →
Other applied ai papers
TopicAIRS-Bench: a Suite of Tasks for Frontier AI Research Science AgentsAIRS-Bench presents a comprehensive benchmark suite for evaluating LLM agents across diverse scientific domains, demonstrating current limitations while providing open-source resources for advancement.
Meta30 citations83 upvotesRead →SciPredict: Can LLMs Predict the Outcomes of Scientific Experiments in Natural Sciences?SciPredict benchmark reveals that large language models struggle to accurately predict scientific experiment outcomes and cannot reliably assess prediction confidence, unlike human experts who show better calibration and performance when experiments are deemed predictable.
Scale AI4 citations4 upvotesRead →AIM: Agentic Idea Management for Automated ResearchAIM is an autonomous framework that manages and explores research directions by using surrogate models to guide experimental budget allocation.
Google2 citations53 upvotesRead →Designer-RSI: Evolving Procedural Memory from User Traffic for Agentic Graphic DesignDesigner-RSI improves agentic graphic design by continually refining a procedural memory of skills based on user traffic and execution feedback.
Adobe1 citations34 upvotesRead →Automating ML for Science: Can Frontier Agents Climb Scientific Hills in the Wild?This testbed evaluates how well AI agents can improve scientific machine learning models and identifies their reliance on engineering tricks over research insight.
Anthropic18 upvotesRead →CommerceGen-Studio: An End-to-End Framework for Commercial-Grade Main-Image GenerationThis paper presents an end-to-end framework for generating commercial-grade e-commerce product images by combining metadata extraction, layout planning, and multi-condition generation.
Alibaba (Qwen)25 upvotesRead →
About this paper
- Citations
- 0, 0 influential · Semantic Scholar
- Upvotes
- 39 · Hugging Face
- Lab
- Microsoft · on Companies · on Acquisitions · on Quarterly · on Paydays · on Releases · on TechConf
Changes
A first count of 0 influential citations.
A first count of 0 citations.
MiniCorp is an office simulator that allows researchers to study how agents run companies and generate enterprise data for training.
Moved from Agents and evaluation to Applied AI.
Found by the weekly Hugging Face scan; not yet checked by hand.