AI Agents

persistent memory system for AI agents — single SQLite file, no external server, no API keys. free and opensource - BrainCTL

Every agent I build forgets everything between sessions. I got tired of it and built brainctl. pip install brainctl, then: from agentmemo...

Why does Multi-Agent RL fail to act like a real society in Spatial Game Theory? [P] [R]

Hey everyone, I’m building a project for my university Machine Learning course called "Social network analysis using iterated game theory...

AWS turns its S3 storage service into a file system for AI agents

[2505.21723] Are Statistical Methods Obsolete in the Era of Deep Learning? A Study of ODE Inverse Problems

This article examines the relevance of statistical methods in the age of deep learning, using ordinary differential equation (ODE) invers...

[2509.25275] VoiceBridge: General Speech Restoration with One-step Latent Bridge Models

VoiceBridge introduces a novel one-step latent bridge model for general speech restoration, enhancing audio quality from various distorti...

[2509.18008] Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration

This article presents a configurable research platform aimed at enhancing human-agent collaboration, exploring the dynamics of human-huma...

[2509.13550] Complexity Bounds for Smooth Multiobjective Optimization

This paper investigates the oracle complexity of finding ε-Pareto stationary points in smooth multiobjective optimization, presenting new...

[2509.12456] Reinforcement Learning-Based Market Making as a Stochastic Control on Non-Stationary Limit Order Book Dynamics

This paper explores the use of reinforcement learning for market making in non-stationary limit order book dynamics, presenting a practic...

[2509.05311] Large Language Model Integration with Reinforcement Learning to Augment Decision-Making in Autonomous Cyber Operations

This article explores the integration of Large Language Models (LLMs) with Reinforcement Learning (RL) to enhance decision-making in auto...

[2410.22009] On uniqueness in structured model learning

This paper explores the uniqueness in structured model learning for systems of partial differential equations (PDEs), proposing a framewo...

[2508.19278] Towards Production-Worthy Simulation for Autonomous Cyber Operations

This article presents a framework for enhancing simulation environments in Autonomous Cyber Operations (ACO) by implementing new actions ...

[2508.18210] Why Synthetic Isn't Real Yet: A Diagnostic Framework for Contact Center Dialogue Generation

This article presents a diagnostic framework for evaluating synthetic dialogue generation in contact centers, highlighting the limitation...

[2508.07514] Robust MultiSpecies Agricultural Segmentation Across Devices, Seasons, and Sensors Using Hierarchical DINOv2 Models

This article presents a robust segmentation framework using Hierarchical DINOv2 models for reliable plant species and damage identificati...

[2507.19457] GEPA: Reflective Prompt Evolution Can Outperform Reinforcement Learning

The paper introduces GEPA, a novel prompt optimizer that leverages natural language reflection to enhance learning efficiency in large la...

[2507.16713] A Pragmatist Robot: Learning to Plan Tasks by Experiencing the Real World

The paper presents PragmaBot, a framework for robotic task planning that utilizes real-world experiences and self-reflection to enhance l...

[2506.20430] An Agentic System for Rare Disease Diagnosis with Traceable Reasoning

The paper presents DeepRare, a multi-agent system utilizing large language models for the differential diagnosis of rare diseases, demons...

[2506.08672] RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic Sampling

RuleReasoner introduces a novel approach to rule-based reasoning using domain-aware dynamic sampling, enhancing reinforcement learning fo...

[2602.06130] Self-Improving World Modelling with Latent Actions

The paper presents SWIRL, a framework for self-improving world modeling in machine learning, focusing on latent actions to enhance predic...

[2602.05319] Accelerated Sequential Flow Matching: A Bayesian Filtering Perspective

This paper introduces Accelerated Sequential Flow Matching, a Bayesian filtering framework that enhances real-time inference in stochasti...

[2602.04942] Privileged Information Distillation for Language Models

This paper presents methods for distilling privileged information in language models, focusing on improving performance in multi-turn env...

[2602.03901] NeuroPareto: Calibrated Acquisition for Costly Many-Goal Search in Vast Parameter Spaces

NeuroPareto introduces a novel architecture for optimizing multi-objective problems in high-dimensional spaces, leveraging Bayesian class...

[2506.00494] Multi-Objective Neural Network-Assisted Design Optimization of Soft Fin-Ray Fingers for Enhanced Grasping Performance

This article presents a multi-objective optimization approach using neural networks to enhance the design of soft Fin-Ray fingers for imp...

[2602.03195] Reinforcement Learning with Promising Tokens for Large Language Models

This article presents a novel framework called Reinforcement Learning with Promising Tokens (RLPT) designed to optimize large language mo...