Thanks for sharing our survey! We are also maintaining an Awesome Code as Agent Harness Papers repo for recent work on code-centric agentic systems and harness engineering: github.com/YennNing/Aweso…
AK@_akhaliq
Code as Agent Harness
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Xuying Ning
8 posts
Xuying Ning
@krystal_ning
UIUC CS PhD, Prev@Columbia&XJTU
Urbana, IL Katılım Nisan 2019
27 Takip Edilen73 Takipçiler
Check out our latest survey on code as agent harnesses, spanning 102 pages and 400+ papers. We outline a roadmap toward executable, verifiable, and stateful AI systems.
Tianxin Wei@wei_tianxin
🚀Code as Agent Harness: A survey work from UIUC, Stanford, and Meta. 📄arxiv.org/abs/2605.18747 Code is no longer just the output of AI. It is becoming the executable, inspectable, and stateful substrate through which AI agents reason, act, verify, remember, and self-correct over long horizons. In our new survey, we examine this shift through the lens of Code as Agent Harness, focusing on how code serves as: • 🧠 Harness Interface: coding for reasoning, acting, and environment modeling • ⚙️ Harness Mechanisms: planning, memory, tool use, feedback, and optimization • 🤝 Multi-Agent Harnesses: collaboration through shared code, tests, and execution traces We review applications spanning: 💻 Coding Agents 🖥️ GUI/OS Agents 🤖 Embodied Agents 🔬 Scientific Discovery 🏢 Enterprise Workflows If you find this survey helpful, feel free to explore our resource collection below. 🤗 Hugging Face Daily: huggingface.co/papers/2605.18… 💻 GitHub: github.com/YennNing/Aweso… 🌍 Website: code-as-harness.github.io/code-as-harnes… Feedback, suggestions, and community contributions are warmly welcome! #AI #Agents #LLM #Coding #AgenticAI #SoftwareEngineering
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Check out our latest survey: huggingface.co/papers/2605.18…
elvis@omarsar0
// Code as Agent Harness // 100+ page report on all things related to agent harnesses. (bookmark it) In particular, the survey summarizes methods and applications of code as agent harness. This paper makes a strong case that code-as-harness might be the key to moving us towards a broader science harness engineering. Is code all you need? Maybe. Regardless, the paper argues that future systems must have the following four properties: executable, inspectable, stateful, and governed. Paper: arxiv.org/abs/2605.18747 Learn to build effective AI agents in our academy: academy.dair.ai
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Xuying Ning retweetledi
Great new paper to read: Code as Agent Harness
(bookmark it)
elvis@omarsar0
// Code as Agent Harness // 100+ page report on all things related to agent harnesses. (bookmark it) In particular, the survey summarizes methods and applications of code as agent harness. This paper makes a strong case that code-as-harness might be the key to moving us towards a broader science harness engineering. Is code all you need? Maybe. Regardless, the paper argues that future systems must have the following four properties: executable, inspectable, stateful, and governed. Paper: arxiv.org/abs/2605.18747 Learn to build effective AI agents in our academy: academy.dair.ai
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Xuying Ning retweetledi
Big PlugMem update 🧠
A plug-and-play memory module for LLM agents — turns raw trajectories into a knowledge graph your agent actually reasons over.
🎉 Accepted to ICML 2026
🔌 Drop it into OpenClaw 🦞, Claude Code, and other agent runtimes
🔍 Visualize memory · test retrieval · replay sessions
🥇 SOTA backbone on LongMemEval & HotpotQA — general enough to build on
Paper: arxiv.org/abs/2603.03296
Code: github.com/TIMAN-group/Pl…
#ICML2026 #LLM #Agents
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Xuying Ning retweetledi
PlugMem transforms AI agents’ interaction histories into structured, reusable knowledge. It integrates with any agent, supports diverse tasks and memory types, and maximizes decision quality while significantly reducing memory token use: msft.it/6017Qc9vv
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Xuying Ning retweetledi
📰New preprint: How can we build a task-agnostic plug-and-play memory module for LLM agents that supports multiple memory types?
We present PlugMem🔌🧠, a plugin memory module that works across tasks by turning heterogeneous experience into knowledge.
Evaluated unchanged on long-term dialogue🗣️, multi-hop QA🕵️, and web agents🕸️🤖, PlugMem improves performance while using far fewer memory tokens.
📜Paper: empathyang.github.io/files/PlugMem.…
🔨Code: github.com/TIMAN-group/Pl…
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Xuying Ning retweetledi
🚀 Just released: Agentic Reasoning for Large Language Models. A comprehensive survey charting the frontier of agentic AI.
📄 arxiv.org/pdf/2601.12538
with UIUC, Google DeepMind, Amazon, Meta, UCSD, and Yale.
✨ This survey examines how reasoning is instantiated, extended, and leveraged within agents, unifying agent architectures with reasoning mechanisms across diverse settings. It covers 800+ papers across the fast-growing agentic ecosystem.
🧠 What’s inside?
• A unified roadmap of agentic reasoning across capabilities and environmental dynamics. This includes foundational abilities such as planning, search, and tool use, self-evolving adaptation via feedback and memory, and multi-agent collaboration.
• Coverage of both in-context reasoning and post-training reasoning optimization.
• Applications and benchmarks spanning math discovery, vibe coding, science, robotics, healthcare, autonomous research, and web exploration.
• Open challenges ahead: governance, personalization, long-horizon interaction, world modeling, latent reasoning, and scalable multi-agent training.
📌 Explore the curated resource collection Awesome-Agentic-Reasoning for papers and tools in this rapidly evolving field:
📚 github.com/weitianxin/Awe…
#AgenticAI #LLMs #AIAgents #Reasoning #Survey #MLResearch
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