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cs.AI2026

Apodex 1.1: Scaling Agentic Intelligence for Complex Work

Apodex Team, B. An, B. Li +73

General-purpose language models can reason and synthesize knowledge, but complex work also requires sustained interaction with files, information sources, and executable code, toge…

cs.AI2026

Apodex Discovery: Reality Benchmarks and Environments for Evaluating and Building Discoverative Artificial Intelligence

Brian Wang, Bin Feng, Xiaoman Pan +26

Apollo did not reach the Moon merely because its engineers could solve difficult equations. It succeeded by turning a distant ambition into a mission architecture of explicit objec…

cs.AI2026

MiroEval: Benchmarking Multimodal Deep Research Agents in Process and Outcome

Fangda Ye, Yuxin Hu, Pengxiang Zhu +19

Recent progress in deep research systems has been impressive, but evaluation still lags behind real user needs. Existing benchmarks predominantly assess final reports using fixed r…

cs.AI2026

MiroFlow: Towards High-Performance and Robust Open-Source Agent Framework for General Deep Research Tasks

Shiqian Su, Sen Xing, Xuan Dong +13

Despite the remarkable progress of large language models (LLMs), the capabilities of standalone LLMs have begun to plateau when tackling real-world, complex tasks that require inte…

cs.AI2025

Evolving Prompts In-Context: An Open-ended, Self-replicating Perspective

Jianyu Wang, Zhiqiang Hu, Lidong Bing

We propose a novel prompt design paradigm that challenges conventional wisdom in large language model (LLM) prompting. While conventional wisdom prioritizes well-crafted instructio…