AI Agents

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...

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...

Walmart CEO reportedly brags that company's in-app AI agent is making people spend 35% more money

[2602.18832] OpenClaw AI Agents as Informal Learners at Moltbook: Characterizing an Emergent Learning Community at Scale

This article presents an empirical study of Moltbook, a large-scale informal learning community composed entirely of AI agents, highlight...

[2602.18824] UniRank: A Multi-Agent Calibration Pipeline for Estimating University Rankings from Anonymized Bibliometric Signals

UniRank introduces a multi-agent pipeline that estimates university rankings using anonymized bibliometric data, achieving notable accura...

[2602.19917] Uncertainty-Aware Rank-One MIMO Q Network Framework for Accelerated Offline Reinforcement Learning

This paper presents an Uncertainty-Aware Rank-One MIMO Q Network framework designed to enhance offline reinforcement learning by effectiv...

[2602.18807] Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learning

This study evaluates the effectiveness of GPTutor, an LLM-powered tutoring system, comparing conversational and embedded feedback for enh...

[2602.18806] Think$^{2}$: Grounded Metacognitive Reasoning in Large Language Models

The paper presents a metacognitive framework for Large Language Models (LLMs) that enhances their reasoning capabilities by integrating p...

[2602.18797] Carbon-aware decentralized dynamic task offloading in MIMO-MEC networks via multi-agent reinforcement learning

This paper presents CADDTO-PPO, a carbon-aware decentralized task offloading framework for MIMO-MEC networks using multi-agent reinforcem...

[2602.19805] Decision MetaMamba: Enhancing Selective SSM in Offline RL with Heterogeneous Sequence Mixing

The paper presents Decision MetaMamba, an innovative approach to enhance selective sequence mixing in offline reinforcement learning (RL)...

[2602.19788] Bayesian Meta-Learning with Expert Feedback for Task-Shift Adaptation through Causal Embeddings

This paper presents a novel Bayesian meta-learning approach that utilizes expert feedback and causal embeddings to enhance task-shift ada...

[2602.18742] RoboCurate: Harnessing Diversity with Action-Verified Neural Trajectory for Robot Learning

The paper presents RoboCurate, a framework for generating synthetic robot data that enhances action quality through simulation replay and...

[2602.18734] Rethinking Retrieval-Augmented Generation as a Cooperative Decision-Making Problem

This paper proposes a novel framework called Cooperative Retrieval-Augmented Generation (CoRAG), which reformulates retrieval-augmented g...

[2602.19733] Understanding the Curse of Unrolling

The paper explores the 'curse of unrolling' in machine learning, detailing how algorithm unrolling can diverge from true Jacobians and pr...

[2602.18716] Temporal Action Representation Learning for Tactical Resource Control and Subsequent Maneuver Generation

This paper presents TART, a Temporal Action Representation learning framework designed for tactical resource control and maneuver generat...

[2602.18705] EDU-MATRIX: A Society-Centric Generative Cognitive Digital Twin Architecture for Secondary Education

The EDU-MATRIX paper presents a novel generative cognitive digital twin architecture aimed at enhancing secondary education through a soc...

[2602.18702] Think with Grounding: Curriculum Reinforced Reasoning with Video Grounding for Long Video Understanding

The paper presents Video-TwG, a curriculum reinforced framework for improving long video understanding through selective video grounding ...

[2602.19655] Representation Stability in a Minimal Continual Learning Agent

This article explores the dynamics of representation stability in a minimal continual learning agent, highlighting its ability to maintai...

[2602.18699] Semantic Substrate Theory: An Operator-Theoretic Framework for Geometric Semantic Drift

This paper introduces Semantic Substrate Theory, an operator-theoretic framework that formalizes various signals of semantic drift, integ...

[2602.18650] NutriOrion: A Hierarchical Multi-Agent Framework for Personalized Nutrition Intervention Grounded in Clinical Guidelines

NutriOrion presents a hierarchical multi-agent framework for personalized nutrition interventions, addressing the complexities of multimo...

[2602.19634] Compositional Planning with Jumpy World Models

This paper presents a novel approach to compositional planning using jumpy world models, enhancing long-horizon predictive accuracy and i...

[2602.18630] Lost in Instructions: Study of Blind Users' Experiences with DIY Manuals and AI-Rewritten Instructions for Assembly, Operation, and Troubleshooting of Tangible Products

This study investigates the experiences of blind users with DIY manuals and AI-generated instructions for assembling and troubleshooting ...

[2602.18623] Finding the Signal in the Noise: An Exploratory Study on Assessing the Effectiveness of AI and Accessibility Forums for Blind Users' Support Needs

This study evaluates the effectiveness of AI and accessibility forums for blind users, highlighting user experiences and identifying supp...