Knowledge catalogue
arXiv:2605.20023v1 Announce Type: new Abstract: Agent Skills, structured packages of procedural knowledge loaded into an LLM agent at inference time, are widely reported to improve task pass rates by
WisdomAI Inc., creator of an artificial intelligence-native business intelligence platform, is jumping on the agentic AI bandwagon with the latest update to its flagship Federated Agentic Intelligence
Multi-agent orchestration is the destination, but for most enterprises, the road is blocked long before the first agent gets deployed by the quality of the data feeding those systems. As organizations
arXiv:2603.23638v2 Announce Type: replace Abstract: Large language model (LLM) agents are increasingly tested on complex tasks, but their ability to allocate scarce resources over long horizons remain
arXiv:2605.16598v1 Announce Type: cross Abstract: Agentic retrieval improves multi-hop question answering by giving language models autonomy to iteratively gather evidence. Recent work augments these
arXiv:2602.16346v3 Announce Type: replace Abstract: LLM-based agents execute real-world workflows via tools and memory. These affordances enable ill-intended adversaries to also use these agents to ca
arXiv:2605.17292v1 Announce Type: new Abstract: Multi-agent large language model (LLM) systems have shown promise for solving complex tasks through agent collaboration. However, existing frameworks as
arXiv:2605.16757v1 Announce Type: new Abstract: Multi-agent language systems are often built as hand-designed workflows, where agents are assigned semantic roles and communication protocols are specif
Unity Catalog is a Databricks governance solution that helps secure AI agent actions by managing access controls and permissions across agent operations. It prevents unauthorized or 'rogue' AI behavio
arXiv:2605.16481v1 Announce Type: cross Abstract: Long video understanding requires more than large context windows. It also needs a memory mechanism that decides what visual evidence to retain, keeps
arXiv:2605.15706v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existi
Every time I ask my 10-year-old to use coding agents, he gets extremely disappointed. It turns out that all he wants is to build his own rocket simulator. No amount of context engineering helps. No mo
arXiv:2605.15701v1 Announce Type: cross Abstract: Memory data are ubiquitous in Large Language Model (LLM)-based agents (e.g., OpenClaw and Manus). A few recent works have attempted to exploit agents'
arXiv:2605.16143v1 Announce Type: new Abstract: Large language model based agents often fail in unfamiliar environments due to premature exploitation: a tendency to act on prior knowledge before acqui
The Open Agent Leaderboard is a benchmarking system hosted on Hugging Face that evaluates and ranks AI agents based on their performance across various tasks and capabilities. It provides a standardiz
when evaluating long running agents, all of your evals don't need to be end to end. i'm working on a proper blog about this, but in our evals for our agents that run for 30-60 minutes, we have two set
arXiv:2605.14786v1 Announce Type: cross Abstract: As LLM-based agents increasingly browse the web on users' behalf, a natural question arises: can websites passively identify which underlying model po
SuperGrok has been integrated into the Hermes Agent, representing an advancement in Nous Research's AI agent capabilities. This integration likely combines SuperGrok's reasoning or processing features
arXiv:2605.14290v1 Announce Type: cross Abstract: ReAct has become the default architecture across LLM agents, and many existing web agents follow this paradigm. We argue that it is the wrong default
Nous Research has integrated Grok, xAI's large language model, into the Hermes Agent framework, allowing users with active @grok subscriptions to leverage Grok's capabilities within the Hermes Agent e
arXiv:2604.03551v2 Announce Type: replace-cross Abstract: Software Engineering 3.0 marks a paradigm shift in software development, in which AI coding agents are no longer just assistive tools but acti
arXiv:2605.12718v1 Announce Type: new Abstract: Multi-agent debate has emerged as a promising approach for improving LLM reasoning on ground-truth tasks, yet current methodologies face certain structu
arXiv:2605.12920v1 Announce Type: cross Abstract: Effective collaboration between embodied agents requires more than acting in a shared environment; it demands communication grounded in each agent's e
SWE-ZERO and AgentTrove are trending datasets on Hugging Face related to software engineering and agentic AI systems. The post indicates growing interest in trace datasets that capture agent behaviors
Freshworks Inc. today unveiled an expanded set of agentic capabilities in its Freshservice information technology service management platform led by a new no-code Freddy AI Agent Studio that lets ente
Anyscale has introduced a new Agent Skill designed to enhance LLM post-training capabilities, likely enabling developers to build and train agentic systems more effectively using Ray's distributed com
arXiv:2605.13618v1 Announce Type: cross Abstract: The Materials Genome Initiative catalyzed the proliferation of centralized platforms--SaaS, PaaS, and IaaS--that aggregate computational and experimen
arXiv:2602.01453v3 Announce Type: replace Abstract: We study cooperative multi-agent reinforcement learning in the setting of reward-free exploration, where multiple agents jointly explore an unknown
arXiv:2506.19417v2 Announce Type: replace Abstract: Cooperative multi-agent reinforcement learning (MARL) under sparse rewards remains fundamentally challenging because agents often fail to concentrat
just tried this out and it one-shotted* this video: 'before the agent does anything' *i generated the narrative using chatgpt and used that as a prompt. featuring: @e2b @runanywhereai @composio @mem0a
arXiv:2605.08769v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems have shown strong potential on complex tasks through agent specialization, tool use, and collaborat
arXiv:2605.09027v1 Announce Type: new Abstract: In multi-agent systems (MAS), a single deceptive agent can nullify all gains of an agentic AI collective and evade deployed defenses. However, existing
arXiv:2605.08670v1 Announce Type: new Abstract: Large language model (LLM) powered AI agents have emerged as a promising paradigm for autonomous problem-solving, yet they continue to struggle with com
arXiv:2605.09076v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly collaborate over peer-to-peer networks to improve their reliability. However, these same interactions c
arXiv:2605.08310v1 Announce Type: cross Abstract: Browser agents are increasingly deployed in long-horizon tasks, which require executing extended action chains to accomplish user goals. However, this
arXiv:2603.23806v2 Announce Type: replace-cross Abstract: AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invoca
arXiv:2605.07301v1 Announce Type: new Abstract: Accurately predicting opponents' behavior from interactions is a fundamental capability for large language model (LLM)-based agents in multi-agent and g
arXiv:2602.12852v2 Announce Type: replace Abstract: Deep Research systems based on web agents have shown strong potential in solving complex information-seeking tasks, yet their search efficiency rema
With AI coding tools like Antigravity and Claude Code, I can build a working web app in record time. But deploying it? That's where I'd historically lose the rest of the afternoon to Dockerfiles, IAM
arXiv:2505.13246v2 Announce Type: replace Abstract: Purpose: This paper introduces the concept of 'Agentic Publication,' a novel LLM-driven framework designed to complement traditional scientific publ
arXiv:2605.05185v1 Announce Type: new Abstract: Deep search has become a crucial capability for frontier multimodal agents, enabling models to solve complex questions through active search, evidence v
arXiv:2605.01143v1 Announce Type: new Abstract: Large Language Model (LLM)-powered agents demonstrate strong capabilities in autonomous task execution, tool use, and multi-step reasoning. However, the
arXiv:2605.02584v1 Announce Type: cross Abstract: Agentic AI will be an essential enabling technology for designing future mobile communication systems, which could provide flexible and customized ser
arXiv:2605.01758v1 Announce Type: new Abstract: Large multimodal model-based Multi-Agent Systems (MASs) enable collaborative complex problem solving through specialized agents. However, MASs are vulne
arXiv:2605.01457v1 Announce Type: new Abstract: Generative models have emerged as a major paradigm for offline multi-agent reinforcement learning (MARL), but existing approaches require many iterative
arXiv:2605.02592v1 Announce Type: new Abstract: Foundation models, particularly large language models, are increasingly integrated into agent architectures for industrial tasks such as decision suppor
arXiv:2605.01102v1 Announce Type: new Abstract: Single-agent systems (SAS) have become the default pattern for LLM-driven scientific workflows, but routing planning, tool use, and synthesis through a
Run an entire company with agents 🔥 It's always awesome to see companies continuing to innovate on AI-native UI/UX, particularly around multi-agent coordination, to solve deeply complex tasks beyond w
arXiv:2605.00314v1 Announce Type: cross Abstract: An agent skill is a configuration package that equips an LLM-driven agent with a concrete capability, such as reading email, executing shell commands,
arXiv:2604.24920v2 Announce Type: replace-cross Abstract: Agentic systems increasingly act with user secrets for APIs, messaging platforms, and cloud services. Today's bearer-secret interfaces impleme
arXiv:2603.03565v2 Announce Type: replace-cross Abstract: Conversational shopping assistants (CSAs) represent a compelling application of agentic AI, but moving from prototype to production reveals tw
arXiv:2604.28138v1 Announce Type: cross Abstract: Autonomous agents act through sandboxed containers and microVMs whose state spans filesystems, processes, and runtime artifacts. Checkpoint and restor
NEW paper from Microsoft Research. If you care about training computer-use agents, this is one to keep. (bookmark it) The team builds 1,000 synthetic computers (each with realistic directory structure
shoutout to the man @kylejeong for cooking this up 🔥 every agent can now get a dedicated browser subagent in seconds to navigate sites, fill out forms, click through things, you get it Deep Agents x B
arXiv:2604.26522v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents exhibit systemic failures in compositional generalization, limiting their robustness in interactive environments
DeepAgents Deploy is great, you get - a fully open agent harness (no hidden stuff, inspect everything) - managed infra - can use any cocktail of models including Open Models - and everything is traced
arXiv:2601.22154v2 Announce Type: replace-cross Abstract: Agentic Reinforcement Learning (Agentic RL) has achieved notable success in enabling agents to perform complex reasoning and tool use. However
This is so good @hwchase17 walks through the complete setup of a Deep Agents deployment step-by-step It’s a great example of getting started fast with Deep Agents from the CLI! DeepAgents Deploy is th
arXiv:2604.23815v1 Announce Type: new Abstract: Scientific Deep Research (DR) agents answer user queries by synthesizing research papers into multi-section reports. User feedback can improve their uti
arXiv:2604.24686v1 Announce Type: new Abstract: Autonomous AI agents can remain fully authorized and still become unsafe as behavior drifts, adversaries adapt, and decision patterns shift without any