deer-flow vs ICLR2025-Papers-with-Code
deer-flow: DeerFlow is a community-driven framework designed for deep research, integrating language models with specialized tools for tasks like web search, crawling, and Python code execution. It offers a modular multi-agent system architecture for automated research, supporting various search engines, crawling tools, and private knowledge bases.; ICLR2025-Papers-with-Code: This repository curates a collection of ICLR 2025 papers and open-source projects, with a strong focus on Large Language Models and Natural Language Processing. It continuously updates to provide the latest research advancements, also linking to prior ICLR editions and an AI knowledge community.
TL;DR
- You want a batteries-included LangGraph agent runtime with a file system, isolated bash/Docker sandbox, persistent memory, and sub-agent delegation.
- You want to trigger long-running tasks from Feishu, WeCom, DingTalk, WeChat, Slack, or Telegram without exposing a public IP.
- Your machine or VPS has only 2 vCPU / 4 GB RAM; DeerFlow recommends 8 vCPU / 16 GB RAM for shared servers.
- You only want a lightweight script that writes cited web research reports without running local sandboxes; GPT Researcher is much lighter.
Researchers and practitioners staying updated on the latest ICLR findings in LLM and NLP.
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