AI Agents

Autonomous agents, tool use, and agentic systems

This Week's Best | Monthly Best | Guide | Trending

Top This Week

Ai Agents

AI agents have been blindly guessing your UI this whole time. Here's the file that fixes it.

Every time you ask an AI coding agent to build UI, it invents everything from scratch. Colors. Fonts. Spacing. Button styles. All of it -...

Reddit - Artificial Intelligence · 1 min ·
Llms

OpenClaw security checklist: practical safeguards for AI agents

Here is one of the better quality guides on the ensuring safety when deploying OpenClaw: https://chatgptguide.ai/openclaw-security-checkl...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

Auto agent - Self improving domain expertise agent

someone opensource an ai agent that autonomously upgraded itself to #1 across multiple domains in < 24 hours…. then open sourced the e...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2602.19837] Meta-Learning and Meta-Reinforcement Learning - Tracing the Path towards DeepMind's Adaptive Agent
Machine Learning

[2602.19837] Meta-Learning and Meta-Reinforcement Learning - Tracing the Path towards DeepMind's Adaptive Agent

This article surveys meta-learning and meta-reinforcement learning, highlighting their significance in developing DeepMind's Adaptive Age...

arXiv - AI · 3 min ·
[2602.19672] SkillOrchestra: Learning to Route Agents via Skill Transfer
Machine Learning

[2602.19672] SkillOrchestra: Learning to Route Agents via Skill Transfer

The paper presents SkillOrchestra, a framework for skill-aware orchestration in AI systems, improving agent routing through skill transfe...

arXiv - Machine Learning · 3 min ·
[2602.19810] OpenClaw, Moltbook, and ClawdLab: From Agent-Only Social Networks to Autonomous Scientific Research
Robotics

[2602.19810] OpenClaw, Moltbook, and ClawdLab: From Agent-Only Social Networks to Autonomous Scientific Research

The paper discusses OpenClaw, Moltbook, and ClawdLab, highlighting their role in creating a dataset for AI interactions and proposing Cla...

arXiv - AI · 4 min ·
[2602.19633] TAPE: Tool-Guided Adaptive Planning and Constrained Execution in Language Model Agents
Llms

[2602.19633] TAPE: Tool-Guided Adaptive Planning and Constrained Execution in Language Model Agents

The paper presents TAPE, a novel framework for enhancing language model agents' planning and execution capabilities, addressing vulnerabi...

arXiv - AI · 3 min ·
[2602.18897] HEHRGNN: A Unified Embedding Model for Knowledge Graphs with Hyperedges and Hyper-Relational Edges
Machine Learning

[2602.18897] HEHRGNN: A Unified Embedding Model for Knowledge Graphs with Hyperedges and Hyper-Relational Edges

The paper presents HEHRGNN, a unified embedding model for knowledge graphs that incorporates hyperedges and hyper-relational edges, enhan...

arXiv - AI · 4 min ·
[2602.18858] Hyperbolic Busemann Neural Networks
Machine Learning

[2602.18858] Hyperbolic Busemann Neural Networks

The paper introduces Hyperbolic Busemann Neural Networks, which enhance neural network components by adapting them to hyperbolic space, i...

arXiv - Machine Learning · 3 min ·
[2602.19519] Ada-RS: Adaptive Rejection Sampling for Selective Thinking
Llms

[2602.19519] Ada-RS: Adaptive Rejection Sampling for Selective Thinking

The paper introduces Ada-RS, an adaptive rejection sampling framework aimed at enhancing selective thinking in large language models (LLM...

arXiv - Machine Learning · 3 min ·
[2602.19562] A Multimodal Framework for Aligning Human Linguistic Descriptions with Visual Perceptual Data
Machine Learning

[2602.19562] A Multimodal Framework for Aligning Human Linguistic Descriptions with Visual Perceptual Data

This paper presents a computational framework that aligns human linguistic descriptions with visual perceptual data, enhancing understand...

arXiv - AI · 4 min ·
[2602.18857] VariBASed: Variational Bayes-Adaptive Sequential Monte-Carlo Planning for Deep Reinforcement Learning
Machine Learning

[2602.18857] VariBASed: Variational Bayes-Adaptive Sequential Monte-Carlo Planning for Deep Reinforcement Learning

The paper presents VariBASed, a novel approach that integrates variational belief learning and sequential Monte-Carlo planning to enhance...

arXiv - Machine Learning · 3 min ·
[2602.18856] Issues with Measuring Task Complexity via Random Policies in Robotic Tasks
Nlp

[2602.18856] Issues with Measuring Task Complexity via Random Policies in Robotic Tasks

This paper evaluates the effectiveness of measuring task complexity in robotic tasks using random policies, revealing contradictions in e...

arXiv - Machine Learning · 4 min ·
[2602.19517] Classroom Final Exam: An Instructor-Tested Reasoning Benchmark
Llms

[2602.19517] Classroom Final Exam: An Instructor-Tested Reasoning Benchmark

The paper presents CFE, a multimodal benchmark for evaluating large language models' reasoning capabilities in STEM domains, highlightin...

arXiv - AI · 4 min ·
[2602.19502] Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark
Robotics

[2602.19502] Human-Guided Agentic AI for Multimodal Clinical Prediction: Lessons from the AgentDS Healthcare Benchmark

This article explores how human-guided agentic AI can enhance multimodal clinical prediction, detailing its performance in the AgentDS He...

arXiv - Machine Learning · 4 min ·
[2602.19458] ComplLLM: Fine-tuning LLMs to Discover Complementary Signals for Decision-making
Llms

[2602.19458] ComplLLM: Fine-tuning LLMs to Discover Complementary Signals for Decision-making

The paper presents ComplLLM, a framework for fine-tuning large language models (LLMs) to enhance decision-making by utilizing complementa...

arXiv - AI · 3 min ·
[2602.19439] OptiRepair: Closed-Loop Diagnosis and Repair of Supply Chain Optimization Models with LLM Agents
Llms

[2602.19439] OptiRepair: Closed-Loop Diagnosis and Repair of Supply Chain Optimization Models with LLM Agents

The paper presents OptiRepair, a novel approach using LLM agents for diagnosing and repairing infeasible supply chain optimization models...

arXiv - Machine Learning · 4 min ·
[2602.19416] IR$^3$: Contrastive Inverse Reinforcement Learning for Interpretable Detection and Mitigation of Reward Hacking
Llms

[2602.19416] IR$^3$: Contrastive Inverse Reinforcement Learning for Interpretable Detection and Mitigation of Reward Hacking

The paper presents IR$^3$, a novel framework for detecting and mitigating reward hacking in Reinforcement Learning from Human Feedback (R...

arXiv - Machine Learning · 4 min ·
[2602.18801] SGNO: Spectral Generator Neural Operators for Stable Long Horizon PDE Rollouts
Machine Learning

[2602.18801] SGNO: Spectral Generator Neural Operators for Stable Long Horizon PDE Rollouts

The paper introduces the Spectral Generator Neural Operator (SGNO), a novel approach to enhance the stability of long horizon rollouts in...

arXiv - Machine Learning · 4 min ·
[2602.19298] ALPACA: A Reinforcement Learning Environment for Medication Repurposing and Treatment Optimization in Alzheimer's Disease
Machine Learning

[2602.19298] ALPACA: A Reinforcement Learning Environment for Medication Repurposing and Treatment Optimization in Alzheimer's Disease

The paper presents ALPACA, a reinforcement learning environment designed for optimizing medication repurposing and treatment strategies i...

arXiv - AI · 3 min ·
[2602.18740] HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learning
Ai Agents

[2602.18740] HONEST-CAV: Hierarchical Optimization of Network Signals and Trajectories for Connected and Automated Vehicles with Multi-Agent Reinforcement Learning

The paper presents HONEST-CAV, a hierarchical framework for optimizing traffic flow in mixed environments of human-driven and automated v...

arXiv - AI · 4 min ·
[2602.18739] When World Models Dream Wrong: Physical-Conditioned Adversarial Attacks against World Models
Machine Learning

[2602.18739] When World Models Dream Wrong: Physical-Conditioned Adversarial Attacks against World Models

This paper introduces the Physical-Conditioned World Model Attack (PhysCond-WMA), a novel method to exploit vulnerabilities in generative...

arXiv - Machine Learning · 4 min ·
[2602.19244] Robust Exploration in Directed Controller Synthesis via Reinforcement Learning with Soft Mixture-of-Experts
Machine Learning

[2602.19244] Robust Exploration in Directed Controller Synthesis via Reinforcement Learning with Soft Mixture-of-Experts

This paper presents a Soft Mixture-of-Experts framework for Directed Controller Synthesis, enhancing exploration policies in reinforcemen...

arXiv - Machine Learning · 3 min ·
Previous Page 81 Next

Related Topics

Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

Stay updated with AI News

Get the latest news, tools, and insights delivered to your inbox.

Subscribe to Newsletter

Daily or weekly digest • Unsubscribe anytime