Knowledge catalogue
arXiv:2606.00933v1 Announce Type: new Abstract: Coordinating multiple robots in shared environments requires generating feasible trajectories for each agent while accounting for interactions among age
arXiv:2606.00189v1 Announce Type: cross Abstract: Automated design and optimization of agentic LLM-based systems leads to sophisticated systems that substantially improve result quality over off-the-s
arXiv:2605.30653v1 Announce Type: new Abstract: Multi-agent LLM systems often treat agreement as evidence: when many agents in a panel give the same answer, that answer is assumed to be more reliable.
arXiv:2605.29560v1 Announce Type: new Abstract: Parameterizing high-fidelity 'digital twins' of batteries is a critical yet challenging inverse problem that hinders the pace of battery innovation. Pre
arXiv:2605.29612v1 Announce Type: cross Abstract: Although large language model (LLM) based multi-agent systems (MAS) show their capability to solve complex tasks and achieve higher performance over s
arXiv:2605.29146v1 Announce Type: cross Abstract: Medication recommendation predicts medications for patient visits, but existing methods still face two key challenges. At the model level, traditional
arXiv:2602.15198v2 Announce Type: replace-cross Abstract: Multi-agent systems, where LLM agents communicate through free-form language, enable sophisticated coordination for solving complex cooperativ
arXiv:2605.26252v1 Announce Type: new Abstract: Long-running AI agents need persistent memory. Memory supports learning across sessions, reduces repeated context injection, and enables auditing of pas
arXiv:2605.24197v1 Announce Type: new Abstract: We study a class of emergent misalignment in multi-agent systems (MAS), with a focus on automated workflows, which we refer to agentic misalignment. Alt
arXiv:2605.20876v1 Announce Type: new Abstract: Terminal agents extend Large Language Models with the ability to execute tasks directly in command-line environments, but their progress is bottlenecked
arXiv:2605.17467v1 Announce Type: new Abstract: Large language model-driven multi-agent systems (LLM-MAS) excel at complex tasks, yet unreliable agents remain a key bottleneck to system-level reliabil
arXiv:2605.15218v1 Announce Type: new Abstract: Large language models deployed for MAPDL finite-element simulation face practical reliability challenges: without structured execution control, tool enc
As artificial intelligence agents become more powerful, agentic AI governance becomes increasingly important – and yet, today’s governance solutions struggle to keep AI agents from going off the rails
arXiv:2605.12863v1 Announce Type: cross Abstract: This paper introduces language-based agent control (LBAC), a new programming model for agentic applications that brings techniques from programming la
arXiv:2605.08756v1 Announce Type: new Abstract: Automatic heuristic design (AHD) has emerged as a promising paradigm for solving NP-hard combinatorial optimization problems (COPs). Recent works show t
arXiv:2602.22953v2 Announce Type: replace Abstract: General-purpose agents perform tasks in unfamiliar environments without domain-specific manual customization. Yet no study has systematically measur
Across the public sector, the conversation has shifted; we are no longer just talking about the potential of AI, we are already seeing the impact. While visionary leadership and cultural buy-in are cr
arXiv:2605.07306v1 Announce Type: cross Abstract: Biological laboratory automation can reduce repetitive manual work and improve reproducibility, but reliable embodied execution in wet-lab environment
arXiv:2506.00886v3 Announce Type: replace Abstract: As large language models evolve into tool-augmented agents, a central question remains unresolved: when is external tool use actually justified? Exi
arXiv:2602.20078v3 Announce Type: replace-cross Abstract: Scaling cooperative multi-agent reinforcement learning (MARL) is fundamentally limited by cross-agent noise. When agents share a common reward
arXiv:2505.16120v2 Announce Type: replace Abstract: The emergence of Large Language Models (LLMs) has reshaped agent systems. Unlike traditional rule-based agents with limited task scope, LLM-powered
arXiv:2605.01865v1 Announce Type: cross Abstract: Cooperative multi-agent reinforcement learning (MARL) requires agents to discover joint strategies in a combinatorially large state-action space, yet
Strong Opinions, Loosely Held on Agent + Harness Engineering: 1. You can outperform any default harness+model (including codex & claude code) on pretty much any Task by engineering the harness around
arXiv:2601.21714v2 Announce Type: replace Abstract: The evolution of Large Language Model (LLM) agents towards System~2 reasoning, characterized by deliberative, high-precision problem-solving, requir
arXiv:2605.02489v1 Announce Type: cross Abstract: As the ecosystem of Large Language Model (LLM)-based agents expands rapidly, efficient and accurate Agent Discovery becomes a critical bottleneck for
arXiv:2602.20426v2 Announce Type: replace Abstract: While most efforts to improve LLM-based tool-using agents focus on the agent itself - through larger models, better prompting, or fine-tuning - agen
arXiv:2604.23581v1 Announce Type: cross Abstract: Agentic systems that chain reasoning, tool use, and synthesis into multi-step workflows are entering production, yet prevailing evaluation practices l
arXiv:2603.09002v2 Announce Type: replace-cross Abstract: Multi-agent artificial intelligence systems or MAS are systems of autonomous agents that exercise delegated tool authority, share persistent m
// Skill Retrieval Augmentation for Agentic AI // Great read for AI devs. (bookmark it) It's on finding efficient ways to incorporate skills for agents. The work introduces Skill Retrieval Augmentatio
The Hermes Agent Creative Hackathon ends on Sunday - plenty of time to build something cool on top of this skill or any of the others in our creative suite for a chance to win from the ͏26k prize pool
arXiv:2511.14135v2 Announce Type: replace-cross Abstract: Fair workload enforcement in heterogeneous multi-agent systems that pursue shared objectives remains challenging. Fixed fairness penalties oft
arXiv:2502.00955v2 Announce Type: replace Abstract: Monte Carlo Tree Search (MCTS) based methods provide promising approaches for generating synthetic data to enhance the self-training of Large Langua
OpenRouter released a guide focusing on optimizing the use of Hermes Agent through the OpenRouter platform. The guide likely covers best practices, configuration options, and techniques for maximizing
Intercom Inc. is expanding the role of its Fin artificial intelligence customer agent beyond customer support for the first time, positioning it as a sales assistant that operates across all stages of
Cursor has introduced multi-root workspaces that enable a single agent session to work across multiple repositories simultaneously, facilitating cross-repository code changes. This feature allows deve
Nous Research announced that details about their Hermes agent update were leaked publicly. The post, made by a Nous Research team member, acknowledges the unauthorized disclosure of information regard
arXiv:2604.20087v1 Announce Type: new Abstract: Skills have become the de facto way to enable LLM agents to perform complex real-world tasks with customized instructions, workflows, and tools, but how
arXiv:2506.09373v3 Announce Type: replace-cross Abstract: The advent of autonomous agents is transforming interactions with Graphical User Interfaces (GUIs) by employing natural language as a powerful
arXiv:2604.16333v1 Announce Type: new Abstract: Knee osteoarthritis frequently exhibits discordance between structural damage observed in imaging and patient-reported symptoms such as pain. This misma
arXiv:2604.18005v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used for open-ended idea generation, driven by the expectation that collective interaction will broaden the
arXiv:2604.16987v1 Announce Type: new Abstract: The rapid evolution of video generation technologies poses a significant challenge to media forensics, as conventional detection methods often fail to g
arXiv:2604.16778v1 Announce Type: new Abstract: LLM-powered agents often reason from scratch when presented with a new problem instance and lack automatic mechanisms to transfer learned skills to othe
This article explains how to ground Korean AI agents in realistic demographic data by utilizing synthetic personas, likely leveraging NVIDIA's Nemotron models available on Hugging Face. The approach e
arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens
arXiv:2604.00131v2 Announce Type: replace Abstract: Human memory adapts through selective forgetting: experiences become less accessible over time but can be reactivated by reinforcement or contextual
arXiv:2601.05808v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are expected to be trained to act as agents in various real-world environments, but this process relies on rich a
arXiv:2510.13220v2 Announce Type: replace Abstract: A fundamental limitation of current AI agents is their inability to learn complex skills on the fly at test time, often behaving like 'clever but cl
arXiv:2512.02543v2 Announce Type: replace Abstract: Deploying LLM agents at scale typically requires choosing between quality and cost. Existing cost-reduction approaches fail to preserve agility: the
Kimi K2.6 is now available in Hermes Agent. Simply run `hermes update` and use `hermes model` to select a compatible provider hosting the model! Meet Kimi K2.6: Advancing Open-Source Coding 🔹Open-sour
Meet Kimi K2.6 agent - Video hero section, WebGL shaders, real backends. From one prompt. 🔹 Video hero sections - cinematic aesthetic, auto-composited 🔹 WebGL shader animations - native GLSL / WGSL, l
arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre
In this post, we share how AWS Marketing’s Technology, AI, and Analytics (TAA) team worked with Gradial to build an agentic AI solution on Amazon Bedrock for accelerating content publishing workflows.
arXiv:2602.13156v2 Announce Type: replace-cross Abstract: Rapidly evolving cyberattacks demand incident response systems that can autonomously learn and adapt to changing threats. Prior work has exten
Renuka Kumar and Prashanth Ramagopal from the @Cisco team built a LangSmith + LangGraph powered framework for multi-agent coordination that behaves like a real-world software team. An inside look → ht
arXiv:2604.14399v1 Announce Type: new Abstract: Autonomous on-orbit servicing demands embodied agents that perceive through visual sensors, reason about 3D spatial situations, and execute multi-phase
arXiv:2512.10696v2 Announce Type: replace-cross Abstract: Procedural memory enables large language model (LLM) agents to internalize 'how-to' knowledge, theoretically reducing redundant trial-and-erro
arXiv:2604.12258v1 Announce Type: cross Abstract: Clinical research involves labor-intensive processes such as study design, cohort construction, model development, and documentation, requiring domain
Windsurf has released a new version of its AI-powered coding environment featuring the Agent Command Center, Spaces, and Devin integration. The update is available for download at windsurf.com/downloa
LAST CALL to win 5k The Agent 4 Content Challenge ends TODAY at midnight. Build app. Make a video. Post it. Clock is ticking https://x.com/Replit/status/2034372199319011645 20,000 up for grabs. 4 week
arXiv:2604.09747v1 Announce Type: cross Abstract: Large Language Model (LLM) agents have achieved rapid adoption and demonstrated remarkable capabilities across a wide range of applications. To improv