Knowledge catalogue
arXiv:2606.07462v1 Announce Type: new Abstract: As foundation models advance and agent scaffolding becomes increasingly sophisticated, agents have demonstrated remarkable proficiency in complex, long-
arXiv:2602.04234v6 Announce Type: cross Abstract: Multi-agent systems (MAS) have emerged as a prominent paradigm for leveraging large language models (LLMs) to tackle complex tasks. However, the mecha
Agentic artificial intelligence is being misread as a set of separate battles – for example, Snowflake Inc. versus Databricks Inc., copilots versus agents, model makers versus application vendors. We
Hermes Agent, developed by Nous Research, is an AI agent designed specifically for creative professionals and artists. The tool likely focuses on automating tasks, enhancing workflows, or providing sp
Hermes Agent v0.16.0, released by Nous Research and dubbed 'The Surface Release,' represents an update to their Hermes Agent framework. This version likely includes bug fixes, performance improvements
Gary Marcus discusses a paradox in the agentic AI market: while developers are creating numerous new applications powered by agentic AI systems, these applications are failing to achieve meaningful us
arXiv:2606.05749v1 Announce Type: new Abstract: Iterative retrieval-reasoning agents have recently shown promise for multimodal long-document question answering. However, most existing systems maintai
arXiv:2606.06079v1 Announce Type: new Abstract: Agent skills, which consist of reusable strategies that guide agent reasoning and action, have shown strong potential for improving model capability at
The rise of agentic commerce is forcing retailers to rethink their entire data strategy — not as a future concern, but as the immediate prerequisite for competing in a world where AI agents make purch
This post likely announces or describes how to invoke or utilize a Hermes Agent, possibly related to function calling, tool use, or agentic capabilities within the Hermes model framework developed by
arXiv:2606.04435v1 Announce Type: new Abstract: Multi-step agentic retrieval-augmented generation (RAG) pipelines have demonstrated significant capability for complex reasoning tasks, yet remain vulne
arXiv:2606.05021v1 Announce Type: new Abstract: We investigate multi-agent deep reinforcement learning and propose two enhancements to the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algor
arXiv:2602.14117v2 Announce Type: replace-cross Abstract: Open Radio Access Networks (O-RAN) promise flexible 6G network access through disaggregated, software-driven components and open interfaces, b
Agentic AI is making the semantic layer an essential enterprise priority because headless agents asking thousands of questions simultaneously have zero tolerance for inconsistent data definitions. Thi
arXiv:2606.02871v1 Announce Type: cross Abstract: Large reasoning models improve performance by generating extended chain-of-thought (CoT) reasoning, but this behavior becomes inefficient when applied
I'm finally launching this agent tomorrow! Will be free, open source, and powered exclusively by open models on @togethercompute. Will also drop a full guide on how it works! Building an agent that ca
New research from Google. Just shows the impressive results you can get from custom agent harnesses. LEAP wraps a general-purpose LLM in an agentic scaffold that grounds every step in the Lean compile
arXiv:2606.03161v1 Announce Type: cross Abstract: OpenAgenet, abbreviated as OAN, is an open infrastructure project for trusted Agent interconnection. It addresses a problem that becomes visible when
arXiv:2606.03163v1 Announce Type: cross Abstract: This paper describes the technical architecture of OpenAgenet / OAN. OAN is a protocol-neutral trust layer for open Agent interconnection. It specifie
arXiv:2606.03686v1 Announce Type: new Abstract: We present DeepSpeak-Agentic, a dataset of videos comprising over 37 hours of semi-structured conversations between a human and an embodied AI agent. We
arXiv:2606.02812v1 Announce Type: new Abstract: Modeling patient trajectories from longitudinal electronic health records (EHRs) requires reasoning over sparse, noisy, and long-context multimodal sequ
arXiv:2606.01279v1 Announce Type: new Abstract: AI agents are increasingly being tasked with automating AI research itself, particularly the critical post-training phase that transforms base LLMs into
arXiv:2606.01094v1 Announce Type: new Abstract: Clinical order generation serves as a critical bridge between clinical decision-making and real-world practice, translating medical decisions into concr
arXiv:2606.01828v1 Announce Type: cross Abstract: Large language model-driven multi-agent systems enhance the reliability of complex reasoning tasks through multi-round deliberation, role specializati
Fleet offers the most secure computer use experience, ensuing your can let your agent access private resources, without worrying about it mishandling or leaking secrets Giving agents access to sensiti
arXiv:2312.03644v3 Announce Type: replace Abstract: Offline Multi-agent Reinforcement Learning (MARL) is valuable in scenarios where online interaction is impractical or risky. While independent learn
This post outlines the agent development lifecycle, consisting of four key phases: Build, Test, Deploy, and Monitor. The content covers best practices and methodologies for developing AI agents using
arXiv:2511.03100v2 Announce Type: replace-cross Abstract: The agent-environment co-design paradigm jointly optimises agent policies and environment configurations in search of improved system performa
arXiv:2605.31509v1 Announce Type: cross Abstract: Large language model agents trained with reinforcement learning (RL) often learn brittle, task-specific shortcuts. We hypothesize that agents generali
arXiv:2605.30248v1 Announce Type: new Abstract: Image generation models have evolved from text-conditioned pixel synthesis toward multimodal agents endowed with visual comprehension and tool invocatio
Agents are easy to prototype and hard to improve. A repeatable loop of traces, evals, failed-span inspection, and targeted harness changes makes agent behavior easier to debug and improve. The post Ho
arXiv:2605.27489v1 Announce Type: cross Abstract: Multi-agent LLM systems decompose workflows across agents, tools, shared context, memory, and decision gates. This modularity improves interpretabilit
Hermes Agent v0.15.0, released by Nous Research as 'The Velocity Release,' represents an update to their Hermes Agent framework that likely focuses on performance improvements and speed optimizations.
Nous Research has announced support for Opus 4.8 in the Hermes Agent framework. This update enables the Hermes Agent to utilize Anthropic's Opus 4.8 model, expanding the available model options for us
arXiv:2605.28424v1 Announce Type: new Abstract: Equipping large language models with explicit skills has emerged as a promising paradigm for enabling autonomous agents to solve complex tasks. Agent sk
arXiv:2605.27850v1 Announce Type: new Abstract: Effective multi-agent systems cannot be designed by selecting prompts or communication graphs in isolation. Agent behavior depends on the information an
arXiv:2502.14321v3 Announce Type: replace-cross Abstract: Large language model-based multi-agent systems have recently gained significant attention due to their potential for complex, collaborative, a
cognition is now the largest independent agent lab in the world. take the 200% utilization that everyone is hitting from this chart and run out the sales growth from this, i encourage you to go thru t
As agent adoption scaled, we saw a common pattern emerge across enterprises, including our own sales organization: specialized agents deliver value, but without orchestration, users carry the cognitiv
Robinhood is opening its trading platform to AI agents. In an announcement on Wednesday, Robinhood says traders can now create a separate account for an AI agent and add a specific amount of money, al
“agent debt” is a new term, but it was inevitable, an instantiation of the AI-driven technical debt I keep warning about. what happens when you build it fast, but you don’t really know how to fix it.
arXiv:2605.25641v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) systems in complex B2B (business-to-business) settings may often receive free-form response feedback. Rathe
arXiv:2605.24468v1 Announce Type: new Abstract: Long-horizon agentic reasoning requires large language models to act over long interaction histories containing thoughts, tool calls, observations, and
New paper from Microsoft on Self-Evolving Agent Skills New research from Microsoft Research I see a lot of AI engineers handwriting agent skill docs and hope they generalize. Probably not optimal. Thi
Latent Space reports on a rebranding or reorganization where Model Labs have been renamed or converted into Agent Labs, reflecting a shift in focus toward AI agent development and capabilities. This c
arXiv:2605.22794v1 Announce Type: cross Abstract: Autonomous agentic systems are largely static after deployment: they do not learn from user interactions, and recurring failures persist until the nex
arXiv:2605.21850v1 Announce Type: new Abstract: Recent development of agents has renewed demand for long-context reasoning capacity of LLMs. However, training LLMs for this capacity requires costly lo
arXiv:2605.20425v1 Announce Type: new Abstract: Designing multi-agent workflows is especially difficult in open-ended scientific settings where tasks lack curated training sets, reliable scalar evalua
arXiv:2605.20704v1 Announce Type: cross Abstract: Autonomous AI agents that spawn sub-agent swarms create a safety gap: existing credential revocation mechanisms, OAuth~2.0 introspection, OCSP, and W3
Hermes Agent has been updated to support integration with Bitwarden Secrets Manager, enabling secure credential and secret management capabilities within the Hermes agent framework. This integration a
MagenticLite is an agentic system for small models that works across the browser and local file system in a single workflow. It combines specialized models and orchestration to support efficient agent
arXiv:2603.06007v2 Announce Type: replace Abstract: Large language model-based (LLM-based) multi-agent systems (MAS) are increasingly used to extend agentic problem solving via role specialization and
The innovation race has entered a new phase with enterprise agentic AI spreading across every part of the business. The potential of agents — once limited to technical teams — is quickly becoming acce
arXiv:2605.19330v1 Announce Type: new Abstract: LLM agents organize behavior through skills - structured natural-language specifications governing how an agent reasons, retrieves, and responds. Unlike
arXiv:2605.05974v2 Announce Type: replace-cross Abstract: LLM agents rely on prompts to implement task-specific capabilities based on foundation LLMs, making agent prompts valuable intellectual proper
Engine is a sophisticated production agent system developed by a team that Harrison Chase recommends for understanding advanced agent architecture and implementation. The post suggests it represents n
arXiv:2605.18024v1 Announce Type: cross Abstract: Cooperation is central to multi-agent reinforcement learning (MARL), yet learned coordination can be fragile when external perturbations disrupt inter
arXiv:2605.18597v1 Announce Type: new Abstract: Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inf
arXiv:2605.18077v1 Announce Type: new Abstract: Communication is a key component in multi-agent reinforcement learning (MARL) for mitigating partial observability, yet prior approaches often rely on i
arXiv:2601.00360v3 Announce Type: replace-cross Abstract: As multi-agent AI systems become increasingly autonomous, evidence shows they can develop collusive strategies similar to those long observed