Autonomous agents, tool use, and agentic systems
Anthropic launches Claude Managed Agents in public beta — composable APIs for shipping production AI agents 10x faster Handles sandboxing...
Every agent I build forgets everything between sessions. I got tired of it and built brainctl. pip install brainctl, then: from agentmemo...
Hey everyone, I’m building a project for my university Machine Learning course called "Social network analysis using iterated game theory...
![[2510.10854] Discrete State Diffusion Models: A Sample Complexity Perspective](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This article presents a theoretical framework for discrete-state diffusion models, offering the first sample complexity bounds and insigh...
The paper introduces dual goal representations for goal-conditioned reinforcement learning (GCRL), enhancing state characterization and i...
This article introduces the Token Hidden Reward (THR) metric, which enhances exploration-exploitation strategies in Group Relative Deep R...
The paper presents TKN, a transformer-based neural network designed for real-time video prediction, achieving a remarkable prediction rat...
OpenTSLM introduces a new family of Time Series Language Models designed to enhance reasoning over multivariate medical data, outperformi...
AIRS-Bench introduces a suite of 20 tasks designed to evaluate AI agents' capabilities in scientific research, highlighting areas of stre...
The paper introduces OmniVideo-R1, a novel framework designed to enhance audio-visual reasoning through query intention and modality atte...
The paper presents the 8-bit Muon optimizer, which enhances computational efficiency and reduces memory usage in large-scale machine lear...
The paper introduces PATHWAYS, a benchmark assessing AI web agents' ability to discover and utilize hidden contextual information in mult...
The paper introduces ROMA, a Recursive Open Meta-Agent Framework designed to enhance performance in long-horizon multi-agent systems by a...
The paper presents DiffusionNFT, a novel online reinforcement learning paradigm that optimizes diffusion models directly on the forward p...
The paper explores how user persuasion affects the behavior of large language model (LLM) agents during long-horizon tasks, revealing tha...
The paper presents Multi-Agent Actor-Critic (MAAC) methods for optimizing decentralized collaboration among large language models (LLMs),...
The paper introduces ScholarGym, an evaluation environment designed to benchmark large language models in the information-gathering phase...
The paper presents Aeon, a Neuro-Symbolic Cognitive Operating System designed to enhance memory management in Long-Horizon LLM agents, ad...
The paper introduces MAVIS, a framework for aligning large language models (LLMs) to multiple objectives at inference time, enhancing fle...
This article examines the regulatory gaps in AI deployment within organizations, highlighting issues that allow internal systems to evade...
This article discusses the importance of explainable AI (XAI) in enhancing trust and accountability in AI applications, particularly in s...
This paper evaluates a novel behaviour planning approach, demonstrating its effectiveness across diverse domains such as storytelling, ur...
This article explores the use of digital twin technology in agriculture, focusing on its ability to enhance decision-making under imperfe...
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