Knowledge catalogue
@cognition funny you should say that https://x.com/manuelsampedrop/status/2063746243180773656?s=20 @swyx @cognition hope it scores scope discipline too, half my agent failures are perfectly fine code
I really do think we'll see a lot of value accrue in AI startups building 'model routing as a service' Not just OpenRouter - this includes a much broader set of verticalized agents and infrastructure.
arXiv:2604.05360v2 Announce Type: replace-cross Abstract: Gait analysis is essential in post-stroke rehabilitation but remains time-intensive and cognitively demanding, especially when clinicians must
arXiv:2502.00225v4 Announce Type: replace-cross Abstract: We evaluate the ability of the current generation of large language models (LLMs) to help a decision-making agent facing an exploration-exploi
OpenAI Group PBC is still focused on its plans to transform ChatGPT into some kind of “superapp,” and it will have a heavy focus on artificial intelligence agents and autonomous coding bots, according
arXiv:2606.05646v1 Announce Type: cross Abstract: Large language models (LLMs) have enabled powerful software engineering (SE) agents capable of navigating complex codebases and resolving real-world i
arXiv:2512.20111v2 Announce Type: replace Abstract: As the time horizons of sequential decision-making tasks grow, keeping full interaction histories in model context becomes increasingly costly. Rece
Meet the winners of the Milan AI Week Hackathon. Discover how Cascade AI, ContextGuard, and Deals Machine are using agentic AI, workflow automation, and real-time orchestration on Vultr infrastructure
Building AI that Builds AI: Introducing the Sakana AI RSI Lab 🚀 https://sakana.ai/rsi-lab Today, we are announcing the Sakana AI Recursive Self-Improvement (RSI) Lab: a dedicated research group in Tok
arXiv:2606.06380v1 Announce Type: new Abstract: The question of whether artificial systems can be conscious remains open, in part because existing approaches either evaluate systems against theory-der
arXiv:2606.04746v1 Announce Type: new Abstract: Multi-Agent Path Finding (MAPF) algorithms are increasingly used to plan motion for robot teams in industrial warehouses and robotic shared workspaces,
arXiv:2606.04399v1 Announce Type: new Abstract: In the paradigm of decentralized learning, a group of agents collaborate to train a global model using distributed datasets without a central server. Al
arXiv:2606.05112v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically del
arXiv:2606.04029v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has received increasing attention and adoption in real-world use cases. Most of these systems follow a train-then-fix para
arXiv:2606.04433v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in multi-image, multi-turn agentic settings where decisions depend on visual changes. However, in
arXiv:2509.08726v3 Announce Type: replace-cross Abstract: This paper focuses on the decentralized stochastic optimization problem f(mathbf{x})=frac{1}{m}sum_{i=1}^m f_i(mathbf{x}) over a connected net
arXiv:2604.17220v2 Announce Type: replace-cross Abstract: Modeling coordination among generative agents in complex multi-round decision-making presents a core challenge for AI and operations managemen
latest iteration of middleware is rad: there was a subagent that we had that was taking some pretty wild trajectories and was costing wayyyy too much We adapted a 60 line middleware from a different a
microsoft MAI tech report is a gold mine, one of the most transparent for a model at this scale. this model uses zero synthetic data or distillation from previous models. this means reasoning, agentic
arXiv:2603.03480v2 Announce Type: replace Abstract: We study reinforcement learning with delayed state observation, where the agent observes the current state after some random number of time steps. W
arXiv:2606.02754v1 Announce Type: new Abstract: Personalization is a crucial capability of modern language agents. However, current research primarily positions personalized agents as passive responde
arXiv:2606.03201v1 Announce Type: cross Abstract: Reinforcement learning from expert videos across visually distinct domains is challenging due to the absence of reward signals and the presence of dom
@swyx and I are curating the AI in GTM track at @aiDotEngineer on June 30. The thing every AI engineer must realize: GTM just became an engineering problem. Outbound = agent design. Enrichment = retri
You shipped your app. Now what? Your app may look great, but if no one can find it, it stays invisible Publishing is only the beginning Meet SEO Agent. It runs a scan for you and suggests fixes to hel
arXiv:2606.02528v1 Announce Type: cross Abstract: Large language models now power robo-advisors and trading agents, yet whether they carry built-in biases toward specific assets is largely untested. W
arXiv:2604.03789v2 Announce Type: replace-cross Abstract: Recent advances in large language models have significantly improved their ability to perform mathematical reasoning, extending from elementar
arXiv:2606.00827v1 Announce Type: cross Abstract: Strategic classification (SC) investigates scenarios where agents manipulate their features to obtain favorable decisions from predictive models. Exis
Everyone talks about 1M context. The harder part is making 1M context actually usable. Serving MiniMax M3 required optimizing for long-context, multimodal, and agentic workloads simultaneously. Excite
Professionals who carry personal liability for their decisions — lawyers, tax accountants, auditors — cannot afford AI that gets it wrong. As enterprises accelerate deployment of agentic systems, the
arXiv:2512.05277v3 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as the perception and reasoning backbone of autonomous agents acting in the wild, with
arXiv:2606.00860v1 Announce Type: cross Abstract: Self-report questionnaires remain the prevailing tool for probing the psychological states of persona-conditioned agents (PC-Agents). However, classic
micropython-wasm 0.1a1 is a Python library for running a MicroPython sandbox using WebAssembly . This alpha release includes fixes for limitations discovered while building datasette-agent-micropython
arXiv:2606.00288v1 Announce Type: new Abstract: Large language models are undergoing a transition from model technology to system technology. As developers use Codex, Claude Code, AutoGPT, and related
arXiv:2606.01364v1 Announce Type: cross Abstract: The attack surface of a modern operating system is a haystack: thousands of signed binaries and millions of functions, almost none relevant to any giv
arXiv:2606.01788v1 Announce Type: new Abstract: Embodied visual navigation, where an agent perceives a complex environment and acts to reach a goal from raw sensory input, underpins a wide range of ap
arXiv:2606.02219v1 Announce Type: new Abstract: Object pose estimation is a fundamental problem for an agent system to perceive or manipulate objects in images or videos. However, current instance-lev
arXiv:2606.00880v1 Announce Type: cross Abstract: Continual reinforcement learning aims to produce agents that learn not only to improve at their current tasks but also to adapt as task distributions
arXiv:2602.13602v2 Announce Type: replace Abstract: We present revise (nderline{Re}asoning with nderline{Vi}deo nderline{S}parsity), a multi-round agent for video question answering (VQA). Instead of
Cloud security startup Upwind Security Inc. today announced it has integrated its runtime security platform with Cisco Cloud Control, the unified platform for agentic information technology operations
We Parse PDFs We spent 7 figures to put this on billboards throughout SF. I thought long and hard about putting something more creative and whimsical. But then you wouldn’t know what we do. AI agents
arXiv:2605.31594v1 Announce Type: new Abstract: Communication costs are a major bottleneck in distributed learning and first-order optimization. A common approach to alleviate this issue is to compres
arXiv:2605.31444v1 Announce Type: new Abstract: Reinforcement Learning (RL) enables autonomous agents to learn policies from experience, but realistic problems often involve enormous state spaces, mak
great look into how Rippling built RipplingAI .@Rippling AI runs on Deep Agents and LangSmith. Here’s how they shipped to millions of users in 6 months. https://www.langchain.com/blog/how-rippling-wen
arXiv:2605.31514v1 Announce Type: cross Abstract: Much research has been carried out on large language models (LLMs) and LLM-powered agentic workflows. However, many works within the field state emerg
arXiv:2605.30656v1 Announce Type: new Abstract: In many practical reinforcement learning environments, observations are far higher-dimensional than the variables that matter for control. In this work,
MiniMax-M3 will by arrive on HuggingFace openweight at next week! Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities - Coding & Agentic Frontier: 59.0% SWE-Ben
Open models! Introducing MiniMax M3: The First Open-Weights Model to Combine Three Frontier Capabilities - Coding & Agentic Frontier: 59.0% SWE-Bench Pro, 66.0% Terminal Bench 2.1, 34.8% SWE-fficiency
arXiv:2605.31097v1 Announce Type: cross Abstract: Mainstream relational databases ship a uniform feature set across deployments, although individual workloads exercise only a fraction of the available
May ships trace-based evaluation for any agent on any cloud, Grok 4.3 and DeepSeek V4 in the model catalog, GPT-5 Reinforcement Fine-Tuning at gated GA, three Microsoft Research on-device agent models
1/10 - PDF parsing at browser speed Jerry Liu showed LiteParse v2 using Rust to WebAssembly for sub-second extraction of messy PDFs, without calling a model. It can sit as a default step in agent and
The secret to LiteParse lies in the grid projection algorithm. We project a complex page layout with text and tables into well-structured text, that humans can read and agents can understanding. This
arXiv:2605.29705v1 Announce Type: new Abstract: Trajectory prediction is a fundamental task for autonomous systems, requiring complex reasoning about multi-agent interactions and intents. Large langua
arXiv:2605.30322v1 Announce Type: cross Abstract: We introduce Gram, an automated alignment auditing framework to assess the propensity of AI agents to engage in sabotage. We evaluate Gemini models ac
arXiv:2605.29963v1 Announce Type: cross Abstract: Honeypots are decoy systems mimicking real system components designed to defend against cyber attacks. Recently, LLMs increasingly serve as simulation
Quality went up alongside output. Even with more PRs shipping, total incidents dropped 5%. They built security guardrails and quality standards into the agentic workflow itself. Productivity vs qualit
The hand-wringing over token usage is real, but I don’t see any organization that has adopted AI retreating from use in coding or even considering it. We are a few months into agentic coding, and comp
The teams seeing the biggest wins from AI are completely changing how they work, not speeding up what they already do. What steps can you delete, what handoffs go away, what can an agent just own end
arXiv:2605.27995v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong capabilities in using external tools to solve complex tasks. However, existing evaluations oft
arXiv:2605.28287v1 Announce Type: new Abstract: Discovering novel stable molecules without training data remains a grand scientific challenge. Current molecular generative models are trained on large,
arXiv:2605.28148v1 Announce Type: cross Abstract: The rapid development of LLMs coupled with the introduction of Model Context Protocol (MCP) has revolutionized how intelligent agents interact with AP