Knowledge catalogue
This post shares feature requests and ideas inspired by experimentation with micro (likely a small language model or tool), credited to another developer. It appears to be a wishlist of desired capabi
“Dependably for LLM agent failures” @hwchase17 Started on this and finding it awesome; also LangSmith engine sparked an idea. The 'Dependabot like for LLM agent failures'. LangSmith Engine gives you t
arXiv:2605.14403v1 Announce Type: new Abstract: Dermatological diagnosis requires integrating fine-grained visual perception with expert clinical knowledge. Although Multimodal Large Language Models (
arXiv:2605.14262v1 Announce Type: new Abstract: As robots become increasingly integrated into everyday environments, intuitive communication paradigms such as natural language and end-user programming
arXiv:2605.14350v1 Announce Type: new Abstract: Multi-task reinforcement learning (MTRL) aims to train a single agent to efficiently optimize performance across multiple tasks simultaneously. However,
arXiv:2605.15116v1 Announce Type: new Abstract: Large-scale labelled driving video data is essential for training autonomous driving systems. Although simulation offers scalable and fully annotated da
Excited to see SmithDB announcement at Interrupt, our purpose-built distributed database for agent observability! SmithDB is built on top object storage, written in Rust and leverages Apache DataFusio
Fine, you all want to code like this I guess. (Runway's new Agent mode is quite impressive, doing fairly complex story building from just a short text description of what you want. Not error free obvi
arXiv:2605.15181v1 Announce Type: new Abstract: Modern image editing models produce realistic results but struggle with abstract, multi step instructions (e.g., ``make this advertisement more vegetari
arXiv:2605.14501v1 Announce Type: cross Abstract: This paper proposes a fully dynamic Deep Reinforcement Learning (DRL) method for rebalancing dockless bike-sharing systems, overcoming the limitations
arXiv:2605.13874v1 Announce Type: cross Abstract: Autonomous research agents can already run machine learning experiments without human supervision, but many rely on a narrow search strategy: they rep
Go in with expectations that Grok Build is still beta, but improving almost every day Grok Build is amazing. The early beta just dropped for SuperGrok Heavy users and the first real feedback from deve
arXiv:2603.07833v2 Announce Type: replace-cross Abstract: Temporal-difference (TD) learning is highly effective at controlling and evaluating an agent's long-term outcomes. Most approaches in this par
arXiv:2603.21250v2 Announce Type: replace Abstract: Logical reasoning encompasses deduction, induction, and abduction. However, while Large Language Models (LLMs) have effectively mastered the former
Great paper discussing agentic search vs. vector search. // Is Grep All You Need? // Pay attention to this on, AI devs. (bookmark it) They find that grep-style text search, when wrapped in the right a
arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises the conversation has already abandoned. Context-m
Had the honor of sharing the stage with the one and only @sydneyrunkle at Interrupt 2026 to talk about Deep Agents. Sign-up for the Managed Deep Agents waitlist today to get early access! https://www.
arXiv:2605.14261v1 Announce Type: new Abstract: How should an agent's performance in a multiagent environment be evaluated when there is a limited sample size or a high cost of running a trial? The AI
@hwchase17 Started on this and finding it awesome; also LangSmith engine sparked an idea. The 'Dependabot like for LLM agent failures'. LangSmith Engine gives you the smoke detector. The natural next
arXiv:2605.14259v1 Announce Type: new Abstract: Applying Large Language Models (LLMs) to heterogeneous enterprise systems is hindered by hallucinations and failures in multi-hop, n-ary reasoning. Exis
ICYMI: 1️⃣ LangSmith Engine 2️⃣ SmithDB 3️⃣ Managed Deep Agents 4️⃣ LangSmith Sandboxes: Now Generally Available 5️⃣ Context Hub 6️⃣ LangSmith LLM Gateway 7️⃣ Sandboxes, Prebuilt agents, + free model
arXiv:2605.14851v1 Announce Type: cross Abstract: Operational plan generation and verification are critical for modern complex and rapidly changing battlefield environments, yet traditional generation
arXiv:2605.14612v1 Announce Type: cross Abstract: AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers
arXiv:2605.14455v1 Announce Type: new Abstract: The Intelligence Impact Quotient (IIQ) is a composite metric intended to quantify the depth to which AI systems are integrated into organizational work
it almost never makes sense to use real api's for your evals. with how good coding agents have become, i will pretty much always opt to create a fake mock server for my agent to hit. the workflow is u
it’s kind of awesome that continual learning has now come to the agent & harness level. i remember when online learning was the big craze in traditional ml a couple of years ago, that transitioned int
Key ideas I picked up at the @LangChain conference this week: 'AI engineering is data science. Look at your data.' — @sh_reya & @HamelHusain 'Data strategy *before* agents.' — @AndrewYNg 'Coding agent
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
arXiv:2605.14527v1 Announce Type: new Abstract: Developing machine learning interatomic potentials (MLIPs) for complex materials systems remains challenging because it requires expertise in atomistic
@LangChain’s Interrupt 2026 conference was a blast!! such a pleasure to with @VictorMoreira16 about deep agents! ICYMI: we just dropped v0.6, which is focused on performance at the model, harness, and
arXiv:2605.14832v1 Announce Type: cross Abstract: We present a flow-matching planner for autonomous driving that directly outputs actionable control trajectories defined by acceleration and curvature
arXiv:2605.14552v1 Announce Type: new Abstract: Recent advances in generative models have empowered impressive layered image generation, yet their success is largely confined to graphic design domains
arXiv:2602.16898v5 Announce Type: replace-cross Abstract: Task planning for robotic manipulation with large language models (LLMs) is an emerging area. Prior approaches rely on specialized models, fin
arXiv:2605.14771v1 Announce Type: new Abstract: MediaClaw is a multimodal agent platform built on the OpenClaw ecosystem. Its core design follows a three-layer architecture of unified abstraction, plu
arXiv:2605.14421v1 Announce Type: cross Abstract: We introduce MemLineage, a defense for LLM agent memory that attaches both cryptographic provenance and LLM-mediated derivation lineage to every entry
arXiv:2605.14212v1 Announce Type: new Abstract: Automatic multi-agent systems aim to instantiate agent workflows without relying on manually designed or fixed orchestration. However, existing automati
arXiv:2509.14159v3 Announce Type: replace Abstract: As robots become more integrated in society, their ability to coordinate with other robots and humans on multi-modal tasks (those with multiple vali
arXiv:2605.14038v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke external tools. Prior wor
arXiv:2605.14111v1 Announce Type: new Abstract: Hospital pharmacists make high-stakes decisions to mitigate drug shortages under uncertainty, time pressure, and patient risk. Interviews revealed that
money doesn't make you happy, but it sure buys tokens People freaking out over my AI spend. What nobody sees: Part of what excites me so much about working on OpenClaw is that I'm trying to answer the
arXiv:2511.17299v2 Announce Type: replace Abstract: Autonomous exploration of unknown environments is a key capability for mobile robots, but it is largely unsolved for robots equipped with only a sin
arXiv:2605.14199v1 Announce Type: new Abstract: Motion planning for autonomous vehicles requires generating collision-free and dynamically feasible trajectories in complex environments under real-time
arXiv:2605.14389v1 Announce Type: new Abstract: Time series forecasting is not just numerical extrapolation, but often requires reasoning with unstructured contextual data such as news or events. Whil
arXiv:2605.14940v1 Announce Type: cross Abstract: Semantic communication systems for goal-oriented transmission must protect task-relevant information not only through source compression but also via
Grok, through a standard subscription, now offers multiple AI capabilities beyond text chat, including image generation, web search via X, and image-to-video conversion. This represents an expansion o
This post likely demonstrates a humanoid robot using a trackpad interface to control a computer mouse and complete a practical task—booking a flight through a web application. The demo showcases the r
okay this email based mission control i prototypes last night is pretty cool: > starts with email > grab and summarize content about participants from crm/notes > auto bucket emails into workstreams u
OpenAI announced yet another reorganization Friday, consolidating certain areas and making company president Greg Brockman the official lead of all things product. In a memo viewed by The Verge, Brock
arXiv:2605.15040v1 Announce Type: new Abstract: Agentic modeling aims to transform LLMs into autonomous agents capable of solving complex tasks through planning, reasoning, tool use, and multi-turn in
arXiv:2605.13880v1 Announce Type: new Abstract: Agent memory is typically constructed either offline from curated demonstrations or online from post-deployment interactions. However, regardless of how
arXiv:2605.14113v1 Announce Type: cross Abstract: While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic
arXiv:2605.14235v1 Announce Type: new Abstract: We present an empirical evaluation of quantum entanglement in agent coordination within quantum multi agent reinforcement learning (QMARL). While QMARL
arXiv:2605.13900v1 Announce Type: cross Abstract: In large-scale multi-agent systems with shared resource constraints, an upstream planner must iteratively evaluate candidate resource plans -- assessi
arXiv:2605.14563v1 Announce Type: cross Abstract: Automated code documentation is essential for modern software development, providing the contextual grounding that both human developers and coding ag
Zac Hall / 9to5Mac: Replit says it has “worked things out with Apple”, which has approved a Replit update after four months, following a reported dispute over vibe coding apps — All's well that ends w
arXiv:2605.13872v1 Announce Type: cross Abstract: This article introduces S-AI-Recursive, a bio-inspired Sparse Artificial Intelligence architecture in which reasoning is operationalized as a hormonal
arXiv:2408.11186v4 Announce Type: replace-cross Abstract: We study sequential multi-issue trading between two greedily rational agents who exchange resources from a finite set of categories. Each agen
arXiv:2510.18766v2 Announce Type: replace Abstract: A future lunar habitat, as part of the Artemis program, will require a significant amount of logistics infrastructure. Cargo that is transported to
arXiv:2605.14588v1 Announce Type: new Abstract: Recursive learning -- where models are trained on data generated by previous versions of themselves -- is increasingly common in large language models,
SmithDB lets you see traces in seconds instead of minutes. This quote from our friends at @cogent_security says a lot: “At Cogent, our background agents can produce a huge volume of traces all at once