Knowledge catalogue
arXiv:2605.09341v1 Announce Type: cross Abstract: Large language model (LLM) agent systems are increasingly expected to improve after deployment, but existing work often decouples two adaptation targe
arXiv:2605.08693v1 Announce Type: new Abstract: Skills provide an effective mechanism for improving LLM agents on complex tasks, yet in existing agent frameworks, their creation, refinement, and selec
arXiv:2605.10114v1 Announce Type: new Abstract: Large Language Model (LLM)-based agents (e.g., OpenClaw) increasingly rely on reusable skill libraries to solve artifact-rich tasks such as document-cen
arXiv:2605.08580v1 Announce Type: cross Abstract: To cope with the large contexts that long-horizon LLM agents produce, modern frameworks increasingly rely on compaction -- invoking an LLM to rewrite
arXiv:2605.10515v1 Announce Type: cross Abstract: The integration of Artificial Intelligence (AI) with Distributed Ledger Technology (DLT) has become a growing research area, yet contributions tend to
arXiv:2605.10052v1 Announce Type: cross Abstract: As artificial intelligence engineering paradigms shift from single-agent Prompt and Context Engineering toward multi-agent extbf{Coordination Engineer
arXiv:2507.11198v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) enable new possibilities for qualitative research at scale, including annotation and qualitative coding of educat
arXiv:2605.10388v1 Announce Type: new Abstract: End to end (E2E) autonomous driving trajectory prediction is often trained with camera frames sampled at the highest available temporal frequency, assum
Nous Research held a 'Hermes Agent Jam' event where developers showcased projects built using or related to their Hermes agent framework. The event appears to have been a community-driven showcase hig
The agent also reimplemented the “Blues Improvisation” experiment by @douglas_eck and @SchmidhuberAI in 2002 which show that LSTMs can learn temporal structure in music. Finding temporal structure in
arXiv:2605.10754v1 Announce Type: new Abstract: LLM-based foundation agents that perceive, reason, and act across thousands of reasoning steps are rapidly becoming the dominant paradigm for deploying
arXiv:2605.10828v1 Announce Type: new Abstract: As large language models are increasingly deployed in retrieval-augmented generation and agentic systems that accumulate extensive context, understandin
The Mini Shai-Hulud attack targets emerging AI-assisted development workflows by compromising multiple integration points including continuous integration systems, code editor hooks, and AI agent conf
arXiv:2605.08323v1 Announce Type: cross Abstract: Communication is fundamental to sustaining reciprocity and cooperation in strategic interactions. We identify and formulate the influence attribution
Hugging Face offers substantial infrastructure capabilities for hosting machine learning models, datasets, and agent memory systems. The statement suggests that organizations currently using alternati
arXiv:2605.10117v1 Announce Type: cross Abstract: Autonomous driving scenes range from empty highways to dense intersections with dozens of interacting road users, yet current 3D detection models appl
thoughts after doing a bunch of synthetic data gen for eval + environment building - LLMs are incredible projections of the world bundled into a set of weights - but doing targeted extraction of certa
arXiv:2605.09443v1 Announce Type: cross Abstract: The advancement of Multimodal Large Language Models (MLLMs) has expanded Role-Playing Agents (RPAs) into visually grounded environments. However, huma
arXiv:2605.10038v1 Announce Type: new Abstract: Time series analysis underpins forecasting, monitoring, and decision making in domains such as finance and weather, where solving a task often requires
arXiv:2507.09788v2 Announce Type: replace-cross Abstract: Recent advances in Large Language Models (LLM) have led to a new class of autonomous agents, renewing and expanding interest in the area. LLM-
arXiv:2605.10344v1 Announce Type: new Abstract: Test-time scaling has become an effective paradigm for improving the reasoning ability of large language models by allocating additional computation dur
🚨 Today: OpenMed Agent ships in preview. Built on @huggingface: → HF endpoints power clinical extraction + terminology → MCP for your own services → Every tool call, every plan, fully visible 1,000+ O
Today's Hermes Agent Jam starts in 90 minutes! Join the Nous team in our Discord to share what you're working on @ http://discord.gg/nousresearch Join the Nous Research team for another Hermes Agent J
arXiv:2605.09104v1 Announce Type: new Abstract: As LLM agents evolve, tokens have emerged as the core economic primitives of Agentic AI. However, their exponential consumption introduces severe comput
Tomorrow @JulienAIArt and I are going to dive into Hermes Agent with the ComfyUI Skill and see what it can do! Bring your questions and tips! Join us for a live build session exploring Hermes Agent in
arXiv:2510.20036v2 Announce Type: replace Abstract: Large language model (LLM) agents rely on external tools to solve complex tasks, but real-world toolsets often contain redundant tools with overlapp
arXiv:2605.09366v1 Announce Type: new Abstract: Transforming neuroimaging data into clinically actionable biomarkers is a knowledge-intensive and labor-intensive process. Standardized workflows such a
arXiv:2605.10257v1 Announce Type: new Abstract: Managing disruptions in railway traffic management is a major challenge. Rising traffic density and infrastructure limits increase complexity, making th
arXiv:2409.13107v3 Announce Type: replace Abstract: Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning compl
arXiv:2605.08830v1 Announce Type: cross Abstract: End-to-end autonomous driving requires models to understand traffic scenes, infer driving intent, and generate executable motion plans. Recent vision-
arXiv:2605.10106v1 Announce Type: cross Abstract: Recent advances in Multi-modal Large Language Models (MLLMs) target 3D spatial intelligence, yet the progress has been largely driven by post-training
Voice selection significantly impacts user perception and experience across various applications, including financial services support, healthcare intake processes, and entertainment platforms. Togeth
we just shipped delta channels in langgraph 1.2. as agents run longer and use more context, full-state checkpointing doesn't scale, but delta channel snapshots do. this new algorithm is now powering m
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:2605.08380v1 Announce Type: cross Abstract: AI agents are increasingly framed as software-engineering teammates, yet most research studies them inside human-centered workflows. Little is known a
What’s special about the @LangChain community is that it’s built by those who are willing to take the extra step to push the boundaries of what’s possible. It’s a community that builds technologies th
arXiv:2602.06286v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in high-stakes settings where good decisions require forming beliefs over the probability of
arXiv:2605.08460v1 Announce Type: cross Abstract: Since the official release of ChatGPT in 2022, large language models (LLMs) have rapidly evolved from chatbot-style interfaces into agentic systems th
arXiv:2605.08478v1 Announce Type: new Abstract: We study how to allocate inference-time compute for competitive programming under fixed budgets. Evaluating 216 Codeforces problems across Divisions 1-3
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:2605.09650v1 Announce Type: new Abstract: Modern agents built on frontier language models often cannot adapt their weights. What, then, remains trainable? We argue it is the agent's workspace, t
This post analyzes the strategic directions and priorities of OpenAI, Anthropic, and xAI by examining their publicly listed job openings, inferring each company's focus areas, capabilities development
arXiv:2508.11070v2 Announce Type: replace Abstract: Decision makers are increasingly relying on machine learning in sensitive situations. Algorithmic recourse aims to provide individuals with actionab
arXiv:2605.08450v1 Announce Type: cross Abstract: Imitation learning is effective for training agents when expert demonstrations are available, but collecting demonstrations for every complex task in
arXiv:2605.08084v1 Announce Type: cross Abstract: The pursuit of autonomous driving has produced one of the richest sensor data collections in all of robotics. However, its scale and diversity remain
arXiv:2605.06976v1 Announce Type: cross Abstract: Many ranking and agent trace datasets are recorded as linear orders even though their latent structure is only partially ordered. This is especially c
A lab with no humans🧪 Tokyo University of Science is operating a robotic medical research laboratory equipped with 10 robots, including the humanoid robot Maholo LabDroid, developed by the Tokyo Insti
arXiv:2508.15294v4 Announce Type: replace Abstract: In the current field of agent memory, extensive explorations have been conducted in the area of memory retrieval, yet few studies have focused on ex
arXiv:2605.06737v1 Announce Type: cross Abstract: Autonomous agents based on Large Language Models (LLMs) are increasingly being utilized in complex software systems. However, reliability remains a si
arXiv:2605.05703v2 Announce Type: replace-cross Abstract: Optimizing the communication structure of large language model based multi-agent systems (LLM-MAS) has been shown to improve downstream perfor
Agent engineering is hard Deep Agents hides a lot of the weird systems complexity, but still gives you more room to customize the harness than almost any agent SDK I've used This is harder to build th
arXiv:2605.06713v1 Announce Type: cross Abstract: Agentic AI systems can plan, call tools, inspect code, interact with web applications, and coordinate multi-step workflows. These same capabilities ch
Ben Thompson / Stratechery: Agentic inference is set to be different than today's inference, and will change compute infrastructure because speed won't matter when humans aren't involved — Subscribe t
arXiv:2512.10371v2 Announce Type: replace Abstract: The rapid development of mobile GUI agents has stimulated growing research interest in long-horizon task automation. However, building agents for th
# Agents as Products This post likely explores how AI agents can be effectively deployed as standalone products, discussing their practical applications and advantages over traditional software soluti
arXiv:2602.04672v3 Announce Type: replace Abstract: Reconstructing dynamic hand-object interactions from monocular videos is critical for dexterous manipulation data collection and creating realistic
arXiv:2605.06841v1 Announce Type: new Abstract: In model-based learning, the agent learns behaviors by simulating trajectories based on world model predictions. Standard world models typically learn a
arXiv:2605.07744v1 Announce Type: new Abstract: The concurrent target assignment and pathfinding (TAPF) problem extends multi-agent pathfinding (MAPF) by asking planners to allocate distinct targets a
Enterprise AI adoption has crossed a threshold: The question is no longer whether to invest, but how to do it wisely. As agentic workloads multiply and inference costs rise, AI choice — the ability to
An abbreviated history of Cognition... Scott Wu is the co-founder of Cognition AI, one of the fastest-growing companies in history. He’s also the greatest competitive programmer the US has ever produc