10 AI Agent Papers

Hey clever folks,

This week, we thought, why not share with you the 10 cutting-edge AI agent research papers curated by Athina AI (shoutout to Paras Madan for this excellent roundup). 

Let’s get into it 👇

1. AI Agents Can Coordinate Beyond The Human Scale

LLMs can self-organize in agent societies, but only up to a point. This study identifies coordination limits and how advanced models can push beyond them. (AI is breaking a new scale every day)

2. Cocoa: Co-Planning & Co-Execution With AI Agents

A collaborative interface for shared planning between humans and agents. (Imagine: computational notebooks meet task planning)

3. BrowseComp: A Benchmark for Browsing Agents

A test set of 1,266 search tasks to check how well agents can persistently browse and retrieve hard-to-find info.  (AI with common sense) 

4. Progent: Secure Privilege Control for Agents

In this study, we found that fine-grained permissions help prevent LLM agents from using tools or data inappropriately while maintaining performance.

5. Better Collaborative Reasoning at Test Time

This paper presents an adaptive multi-agent system that boosts the performance of systems across math, coding, and logic tasks.

Check out more details here:  Top AI Agent Papers - Athina AI

6. AgentA/B: Simulated A/B Testing With Agents

LLM-powered agents simulate users in A/B tests, offering faster UI/UX testing without waiting for traffic. (No more spending hours on A/B tests, let AI agents do it for you)

7. A-MEM: Dynamic, Context-Aware Agent Memory

Inspired by Zettelkasten, A-MEM helps agents store, evolve, and link information like a living notebook. (AI can memorise, why I am still stuck at remembering names)

8. Responsible AI for Agentic Systems

Organizational case studies reveal gaps in responsible AI practices when applied to highly autonomous agents.

9. DocAgent: Better Code Documentation With Multi-Agent Flow

Agents collaborate to generate reliable, structured code documentation, even for complex systems. (Now, the only complex thing that needs coding is my life)

10. FOA: Scalable Multi-Agent Reasoning With Tree Search

Fleet of Agents (FOA) uses dynamic search plus filtering to get high reasoning quality with fewer compute resources. 

Insider’s Tip: Use ChatGPT to Break Down These Papers

Want to actually understand these papers (not just skim them)?

Try this setup:
Split-screen mode → Paper on the left, ChatGPT on the right

Then paste this prompt:

You're an AI research explainer.  

Break this paper down for me in plain English.  

Explain key concepts, real-world use cases, and why it matters for AI agents.

Catch the full breakdown of all 10 papers here → Athina AI Hub

More AI news is coming soon,

 — Written by Aaron & The Clever Nest Team

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