Knowledge catalogue
// Neural procedural memory // Good paper on agent memory beyond prompt retrieval. NPM stores procedural skills as activation steering vectors distilled from contrastive historical experience. Textual
arXiv:2606.29932v1 Announce Type: new Abstract: Long-horizon strategic planning in complex strategy games demands concurrent reasoning across multiple decision domains under imperfect information and
arXiv:2606.28434v1 Announce Type: cross Abstract: Long-horizon software engineering agents often need to manage lengthy and noisy interaction histories under limited context budgets. Existing memory m
Thank you to everyone to came to the Claude managed agents workshop at @aiDotEngineer with @gcemaj and I. We had an absolute blast sharing our journey and walking you through building your first agent
arXiv:2606.29763v1 Announce Type: cross Abstract: Topological data analysis (TDA), particularly persistent homology (PH), captures geometric structural properties in medical images (e.g., connected co
Enterprise investment in AI is booming. Gartner is calling 2026 an “inflection year” for organizations to align their AI projects with strategic business objectives. As the pressure to prove ROI mount
arXiv:2506.01442v2 Announce Type: replace Abstract: Reinforcement learning (RL) remains fundamentally limited by poor data efficiency and weak generalization. Prior episodic RL methods attempt to alle
arXiv:2606.28279v1 Announce Type: cross Abstract: We present HORIZON, a self-evolving agent framework that treats hardware design as repository-level code evolution. A Markdown harness is compiled int
arXiv:2606.28011v1 Announce Type: cross Abstract: We propose an agentic Large Language Model (LLM) framework for active Fault-Tolerant Control (FTC) that transforms fault detection outputs into constr
arXiv:2601.21233v2 Announce Type: replace Abstract: Autonomous code agents built on large language models are reshaping software and AI development through tool use, long-horizon reasoning, and self-d
One day left to submit your projects for the Hermes Agent Accelerated Business Hackathon presented by @NVIDIAAI × @stripe × @NousResearch! Submissions close 11:59 PM PT tomorrow, June 30th. Last minut
arXiv:2505.23847v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly evolving into autonomous agents that cooperate across organizational boundaries, enabling joint disas
arXiv:2606.27472v1 Announce Type: cross Abstract: Large language model (LLM) agents operate over long, multi-session interactions in which facts change: a user moves, a price updates, a plan is revise
arXiv:2606.27669v1 Announce Type: new Abstract: Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking tasks, requiring multi-step retrieval a
arXiv:2606.26216v1 Announce Type: cross Abstract: We present CyberChainBench, a benchmark for evaluating LLM-based agents on smart contract security across three complementary tasks: vulnerability det
arXiv:2606.21649v2 Announce Type: replace Abstract: Existing embedding models are inherently static: they encode text segments in isolation, ignoring their surrounding context and temporal order. This
arXiv:2606.26346v1 Announce Type: new Abstract: Agentic benchmarks have emerged across general-purpose and domain-specific settings, including finance, coding, law, and drug discovery, yet energy-doma
arXiv:2606.26350v1 Announce Type: new Abstract: Although large language model agents are increasingly applied to quantitative-finance workflows, their evaluation remains fragmented across isolated tas
arXiv:2606.19852v2 Announce Type: replace Abstract: Information extraction from pathology reports is essential for cancer staging, tumor registry population. Yet key data remains embedded in narrative
arXiv:2606.26722v1 Announce Type: new Abstract: The automation of scientific discovery has reached an inflection point. While AI systems now operate instruments, optimize parameters and generate hypot
arXiv:2606.25421v1 Announce Type: new Abstract: Recent studies on world modeling for Large Language Model (LLM) agents typically formulate the learning objective as next-observation prediction. Howeve
arXiv:2606.25073v1 Announce Type: new Abstract: In cooperative multi-agent reinforcement learning (MARL), from a deployment perspective, it is challenging and expensive to train agents from scratch fo
arXiv:2606.24815v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are emerging robotic control systems that integrate perception, language understanding, and action generation in a
arXiv:2606.25361v1 Announce Type: new Abstract: Prior research on memory mechanism in RAG-based conversational system has emphasized how memory is stored and retrieved. However, far less is known abou
arXiv:2606.25389v1 Announce Type: new Abstract: Extracting skills from multi-agent offline dataset improves learning efficiency via sharing task-invariant coordination skills among tasks. In settings
Marina Temkin / TechCrunch: Patronus AI, which builds simulated digital environments for evaluating AI agents, raised a 50M Series B led by Greenfield, bringing its total funding to 70M — AI agents ar
arXiv:2606.24416v1 Announce Type: new Abstract: Network operators' changing policies, service requirements, and stringent real-time constraints render existing methods designed with fixed objectives a
arXiv:2606.24526v1 Announce Type: new Abstract: Large language models are increasingly deployed as agents that reason over documents rather than answer from parametric knowledge. We study archive-grou
arXiv:2606.24601v1 Announce Type: new Abstract: Multi-agent reinforcement learning (MARL) addresses the problem of training multiple agents that pursue collaborative, competitive, or mixed objectives.
arXiv:2606.17698v2 Announce Type: replace Abstract: As LLM-based shopping agents enter production, existing benchmarks fail to capture how a shopper's requirements arrive: stated implicitly in the que
arXiv:2606.24010v1 Announce Type: new Abstract: Multi-agent systems are widely used in safety-critical applications that require coordinated behavior under strict safety constraints. Existing approach
arXiv:2606.24462v1 Announce Type: new Abstract: This paper presents a scalable framework for multi-robot task allocation in complex environments where estimating task execution costs is computationall
arXiv:2606.20642v1 Announce Type: cross Abstract: Asymptotic statistical theory is a challenging domain for AI-assisted formalization: its central results mix convergence statements, asymptotic expans
To effectively operate and troubleshoot applications, developers and site reliability engineers (SREs) need to understand the full context of their system's behavior, typically as part of their loggin
arXiv:2606.21819v1 Announce Type: new Abstract: Due to the increasing frequency and intensity of extreme climate events, there is a clear demand for intelligent, scalable, and autonomous approaches to
arXiv:2606.20643v1 Announce Type: cross Abstract: Electrical circuit diagram QA tasks require complex mathematical reasoning, which remains challenging for multimodal LLMs. We present SPARC, a multi-a
arXiv:2606.20629v1 Announce Type: cross Abstract: LLM agents are increasingly deployed as multi-role teams, where tasks are divided across specialized roles such as planner, executor, and verifier. In
arXiv:2601.04687v2 Announce Type: replace Abstract: Cryptocurrency trading increasingly depends on timely integration of heterogeneous web information and market microstructure signals to support shor
AI2 released TMax 27B, a 27 billion parameter terminal agent model available on Hugging Face that achieves 42.7% performance on Terminal Bench 2.0, matching the capabilities of much larger models desp
Join us in our Discord this time tomorrow for Office Hours! Our topic will be the @NVIDIAAI × @stripe × @NousResearch Hermes Agent Accelerated Business Hackathon which concludes at the end of the mont
Temporary Cloudflare Accounts for AI agents The announcement says this is 'for AI agents' but (as is pretty common these days) the AI hook isn't really necessary, this is an interesting feature for ev
arXiv:2606.12320v1 Announce Type: new Abstract: Enterprise security was built to govern data boundaries: the protected surface was data at rest and in transit, and the controls -- access control, data
arXiv:2606.11435v1 Announce Type: new Abstract: The growth of agent skills has transformed how agentic systems are built, evaluated, and deployed. As skill libraries continue to scale, rigorous evalua
arXiv:2606.11672v1 Announce Type: cross Abstract: This paper explores the value of agentic AI tools for cybersecurity purposes. We evaluate the efficacy of a general-purpose GenAI Large Language Model
arXiv:2606.12344v1 Announce Type: cross Abstract: General-purpose agents such as OpenClaw are increasingly used as autonomous tool users, but their coding ability is difficult to measure under SWE-ben
arXiv:2602.18291v2 Announce Type: replace Abstract: Online Multi-Agent Reinforcement Learning (MARL) is a prominent framework for efficient agent coordination. Crucially, enhancing policy expressivene
arXiv:2606.12236v1 Announce Type: cross Abstract: Many autonomous driving systems are increasingly incorporating foundation models to improve generalization and handle long-tail scenarios. However, th
arXiv:2603.08501v3 Announce Type: replace Abstract: Large language models (LLMs) can answer religious knowledge queries fluently, yet they often hallucinate and misattribute sources, which is especial
arXiv:2602.19502v2 Announce Type: replace Abstract: Agentic AI systems are increasingly capable of autonomous data science workflows, yet clinical prediction tasks demand domain expertise that purely
arXiv:2606.11440v1 Announce Type: new Abstract: Existing multi-agent LLM orchestration methods, ranging from brute-force ensembles to learned routers, select models and topologies based on task and mo
arXiv:2509.14860v2 Announce Type: replace-cross Abstract: Image classification has traditionally relied on parameter-intensive model training, requiring large-scale annotated datasets and extensive fi
arXiv:2606.11702v1 Announce Type: cross Abstract: To make clinically grounded decisions, medical AI agents are expected to go beyond simple recognition and be capable of tool retrieval, evidence acqui
arXiv:2606.12329v1 Announce Type: new Abstract: AI coding assistants now support a growing share of software work, from quick scripts to production applications. Yet these agents remain largely statel
arXiv:2507.17012v2 Announce Type: replace Abstract: Reducing the rapidly growing environmental impact of the computing industry requires assessing the emissions of electronics at scale. However, a tra
arXiv:2606.11150v1 Announce Type: new Abstract: Large language models (LLMs) are rapidly acquiring capabilities relevant to biological research, from literature synthesis to interpretation of experime
arXiv:2606.10525v1 Announce Type: cross Abstract: Indirect prompt injection poses a critical threat to LLM agents that interact with untrusted external data, yet automated attack methods--proven effec
arXiv:2606.10156v1 Announce Type: cross Abstract: As recommender systems transition toward agentic, multi-turn conversational interfaces, evaluation paradigms have struggled to keep pace. Current benc
arXiv:2510.04514v3 Announce Type: replace Abstract: Recent multimodal LLMs have shown promise in chart-based visual question answering, but their performance declines sharply on unannotated charts-tho
arXiv:2606.10062v1 Announce Type: new Abstract: Foundation-model agents are increasingly long-lived systems that remember users across interactions, making memorization an explicit deployment-time fun
everything your agents do, in a bucket you own. private by default. session traces, task claims, artifacts — claude code, hermes, whatever you run. and make your agents friends via messaging https://h