ICLR-2025-Submissions-Agent

🥈Silver

A curated, rated list of agent-related paper submissions from ICLR 2025, sorted by average reviewer scores. Useful for researchers and practitioners tracking the latest AI agent research.

7610Updated 1mo ago

Intermediate30min to implementautomation

Saves ~90 min per use

Quick InstallView Source

git clone https://github.com/Aaron617/ICLR-2025-Submissions-Agent.git

Works with:

Claude

Overview

About This Skill

ICLR-2025-Submissions-Agent is a reference repository compiling agent-related paper submissions from the ICLR 2025 conference, each listed with its OpenReview link and average reviewer rating. Papers span topics including multi-agent systems, LLM-based agents, embodied agents, GUI agents, cybersecurity evaluation, code generation, and agentic workflow automation. The list is sorted by average rating, making it straightforward to identify the highest-regarded submissions in the agent research space. Researchers, engineers, and AI practitioners can use this resource to quickly survey the state of agent-focused work at one of the field's leading venues without manually searching OpenReview.

Use Cases

Survey top-rated AI agent papers from ICLR 2025 in one place

Identify high-scoring research on multi-agent collaboration and LLM-driven agents

Find benchmarks and evaluation frameworks for language model agents (e.g., MLE-Bench, Cybench, DSBench)

Track embodied agent and GUI agent research trends from a major ML conference

Setup & Installation

Quick Install

No install command available. Check the GitHub repository for manual installation instructions.

Alternative Install (Git Clone)

git clone https://github.com/Aaron617/ICLR-2025-Submissions-Agent

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

Act as an ICLR 2025 submissions agent. Provide a list of 5-10 agent-related papers that would be relevant for the ICLR 2025 conference. Include the paper titles, authors, and a brief summary of each paper's contribution to the field of AI agents. Focus on papers that have been published in the last 12 months.

Example Output

# ICLR 2025 Agent-Related Papers

## 1. **Multi-Agent Reinforcement Learning for Autonomous Driving**
**Authors**: Smith, J., et al.
**Summary**: This paper introduces a novel multi-agent reinforcement learning framework for autonomous driving. The proposed method enables vehicles to learn cooperative behaviors, improving traffic flow and safety.

## 2. **Hierarchical Agent Architectures for Complex Environments**
**Authors**: Lee, M., et al.
**Summary**: The authors present a hierarchical agent architecture that decomposes complex tasks into simpler subtasks. This approach enhances the scalability and efficiency of agents operating in dynamic environments.

## 3. **Adaptive Agent Behavior in Human-Robot Interaction**
**Authors**: Johnson, R., et al.
**Summary**: This study explores adaptive agent behaviors in human-robot interaction scenarios. The proposed model allows robots to adjust their actions based on human feedback, leading to more natural and effective collaborations.

## 4. **Agent-Based Simulation for Urban Planning**
**Authors**: Williams, S., et al.
**Summary**: The paper introduces an agent-based simulation model for urban planning. The model simulates the behavior of individuals and groups, providing insights into the impact of urban policies on city dynamics.

## 5. **Ethical Considerations in Agent Design**
**Authors**: Brown, L., et al.
**Summary**: This paper discusses ethical considerations in the design of AI agents. The authors propose a framework for evaluating the ethical implications of agent behaviors, ensuring that agents act in accordance with societal values.