Knowledge catalogue
arXiv:2601.21468v5 Announce Type: replace Abstract: Long-horizon agentic reasoning necessitates effectively compressing growing interaction histories into a limited context window. Most existing memor
arXiv:2602.05287v2 Announce Type: replace Abstract: This position paper argues that the pursuit of 'Universal Foundation Models for Time Series' rests on a fundamental category error, mistaking a stru
arXiv:2605.17946v1 Announce Type: new Abstract: Multimodal large language models are increasingly used as agent backbones that understand multimodal inputs, plan retrieval actions, invoke external too
I put together these annotated slides from my five minute lightning talk at PyCon US 2026, using the latest iteration of my annotated presentation tool. # I presented this lightning talk at PyCon US 2
arXiv:2605.16312v1 Announce Type: cross Abstract: We study adversarial action masking in self-play reinforcement learning: an attacker selectively removes legal actions from a victim's action set. Unl
arXiv:2605.17823v1 Announce Type: cross Abstract: When humans view scenes without a specific task (free-viewing), they initially direct their eye movements toward the scene center and then fixate on p
arXiv:2605.15850v1 Announce Type: cross Abstract: In recent years, generative AI (GenAI) in educational settings has become ubiquitous in students' daily lives, despite its potential to induce over-re
arXiv:2605.15769v1 Announce Type: cross Abstract: The co-optimization of a robot's body and brain presents a coupled challenge: the morphology constrains which control strategies are effective, while
Agentic AI inference at one-tenth the cost per token with NVIDIA Vera Rubin NVL72. Agent sandboxes run 50% faster on NVIDIA Vera than traditional CPUs — while enterprise data queries are up to 3x fast
arXiv:2509.21465v3 Announce Type: replace Abstract: Tabular foundation models are becoming increasingly popular for low-resource tabular problems. These models make up for small training datasets by p
Are your benchmarks actually measuring the capability you think they measure? New paper says they probably not. Coined the 'The Evaluation Trap', it provides a vocabulary for auditing whether your eva
arXiv:2605.15034v1 Announce Type: cross Abstract: Large language models (LLMs) have been extensively studied from computational and cognitive perspectives, yet their behavior as communicative actors i
arXiv:2605.14054v1 Announce Type: new Abstract: Achieving robust perception-reasoning synergy is a central goal for advanced Vision-Language Models (VLMs). Recent advancements have pursued this goal v
arXiv:2605.15016v1 Announce Type: cross Abstract: As large language models empower healthcare, intelligent clinical decision support has developed rapidly. Longitudinal electronic health records (EHR)
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: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
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:2602.22847v2 Announce Type: replace-cross Abstract: The concept of ranking aggregation plays a central role in preference analysis, and numerous algorithms for calculating median rankings, often
arXiv:2605.12542v1 Announce Type: cross Abstract: Large foundation models (FMs) are transforming Earth science by integrating heterogeneous multimodal data, such as multi-platform imagery, gridded rea
arXiv:2605.13335v1 Announce Type: new Abstract: Embodied agents in household environments must plan under partial observation: they need to remember objects, track state changes, and recover when acti
arXiv:2510.15297v4 Announce Type: replace-cross Abstract: We introduce VERA-MH (Validation of Ethical and Responsible AI in Mental Health), an automated evaluation of the safety of AI chatbots used in
arXiv:2605.12224v1 Announce Type: new Abstract: Advancements in reinforcement learning have produced a variety of complex and useful intrinsic driving forces; crucially, these drivers operate under a
The most expensive mistake in enterprise AI right now: treating FDEs as your whole transformation plan. Forward deployed engineers (FDEs) are important for custom deployments, but they won’t fix the c
arXiv:2605.09801v1 Announce Type: new Abstract: Solving multi-robot motion planning (MRMP) requires generating collision-free kinodynamically feasible trajectories for multiple interacting robots. We
Found my limit: ~8 simultaneous code generation/review tasks. Beyond that, context-switching turns from leverage into chaos. AI coding doesn’t remove the need for WIP limits. It might even make them m
arXiv:2605.08330v1 Announce Type: new Abstract: We present a hierarchical language-driven framework for robotic task and motion planning to improve natural, intuitive human-robot interaction in servic
arXiv:2605.09494v1 Announce Type: cross Abstract: Unmanned underwater vehicles (UUVs) operate persistently in communication-constrained environments, thus requiring high-level autonomous fault-toleran
arXiv:2605.10820v1 Announce Type: new Abstract: Scientific discovery is fundamentally a resource-constrained process that requires navigating complex trade-offs between the quality and quantity of mea
arXiv:2605.08518v1 Announce Type: new Abstract: Competition retrospectives are useful when they explain what a leaderboard measured, how hidden evaluation changed conclusions, and which design pattern
April brings Foundry Local GA for local AI development, GPT-5.5 model support with Tier 5 and Tier 6 default quota in Microsoft Foundry, new tracing paths for Microsoft Agent Framework and hosted agen
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:2412.11194v2 Announce Type: replace-cross Abstract: Security vulnerabilities in software can have severe consequences; however, manual vulnerability detection is costly and does not scale, espec
arXiv:2512.09682v2 Announce Type: replace-cross Abstract: This work studies the application of Multi-Agent Reinforcement Learning (MARL) to decentralized control of unmanned aerial vehicles to relay a
arXiv:2605.07692v1 Announce Type: new Abstract: Large-scale social simulators are essential for studying complex social patterns. Prior work explores hybrid methods to scale up simulations, combining
arXiv:2605.06223v2 Announce Type: replace Abstract: Natural-language instance navigation becomes challenging when the initial user request does not uniquely specify the target instance. A practical ag
arXiv:2502.13498v2 Announce Type: replace-cross Abstract: Object-goal visual navigation aims to reach a specific target object using egocentric visual observations. Recent deep reinforcement learning
arXiv:2511.03475v4 Announce Type: replace Abstract: AI applications increasingly depend on long-context inference, where LLMs consume substantial context to support stronger reasoning. Common examples
arXiv:2605.04345v1 Announce Type: new Abstract: We formally establish the equivalence between Observation Delay (OD) and Action Delay (AD) in cooperative partially observable multi-agent systems using
who’s adding this to reachy mini? Introducing GPT-Realtime-2 in the API: our most intelligent voice model yet, bringing GPT-5-class reasoning to voice agents. Voice agents are now real-time collaborat
arXiv:2603.20151v2 Announce Type: replace-cross Abstract: Engineering system design -- whether mechatronic, control, or embedded -- often proceeds in an ad hoc manner, with requirements left implicit
arXiv:2605.02913v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a central post-training tool for improving the reasoning abilities of large language models (LLMs). In these syst
Last week I gave a talk at AI Dev ’26 by @DeepLearningAI on “AI can’t read PDFs, how do we fix it” . I’m sharing the slides publicly if others are interested in doing a deep dive into document underst
small workflow note that adds up. /staged-pr is a skill (via slash command) i run when wrapping up a PR. it takes my staged code changes and drafts a concise PR title & description, based on my prefer
arXiv:2604.04328v3 Announce Type: replace-cross Abstract: The evaluation of general-purpose artificial agents, particularly those based on LLMs, presents a significant challenge due to the non-transit
arXiv:2605.02681v1 Announce Type: cross Abstract: We present two new classes of causal models of decision-making agents. Our approach is motivated by the needs of modeling the economics of computing s
arXiv:2511.14887v2 Announce Type: replace Abstract: The rapid advancement of electric vertical takeoff and landing (eVTOL) aircraft offers a promising opportunity to alleviate urban traffic congestion
arXiv:2605.02192v1 Announce Type: new Abstract: Should a single collision necessarily terminate an entire navigation episode? In most deep reinforcement learning (DRL) frameworks for robot navigation,
Join @YuvalinTheDeep, Senior Developer Advocate at @AI21Labs, for a live webinar in partnership with @DataCamp: The Four Gaps Between Demo Agents and Production Systems. If you're shipping agents to p
On episode 9 of High Leverage, Joe Ruscio (@josephruscio) sits down with Simon Willison (@simonw) to unpack the rapid evolution of AI coding tools and what they mean for software development. They exp
There’s a bunch of conflicting stances I don’t fully understand in the debate of Proprietary RL’d vs Open Harness, Model intelligence, and Agent Labs building harnesses for bespoke tasks Not all of th
A $1 Billion one person company may look like a video game. That’s the view Andrew Pignanelli and the team at Intelligence Co are taking. We sat down with him on @11AMdotclub ahead of today’s launch.
arXiv:2605.00334v1 Announce Type: cross Abstract: Production agentic systems make many model calls per user request, and most of those calls are short, structured, and routine. This raises a practical
arXiv:2605.00529v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enhances large language models with external knowledge, and tree-based RAG organizes documents into hierarchical in
arXiv:2605.00440v1 Announce Type: cross Abstract: The evolution of artificial intelligence (AI) has rendered the boundary between humanity and computational machinery increasingly ambiguous. In the pr
arXiv:2605.00798v1 Announce Type: cross Abstract: Humans solve problems by executing targeted plans, yet large language models (LLMs) remain unreliable for structured workflow execution. We propose Ru
arXiv:2604.27660v1 Announce Type: new Abstract: Many real-world tasks require language models (LMs) to reason over complex contexts that exceed their parametric knowledge. This calls for context learn
arXiv:2501.19143v2 Announce Type: replace Abstract: As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial a
arXiv:2604.27297v1 Announce Type: new Abstract: Deriving governing equations from empirical observations is a longstanding challenge in science. Although artificial intelligence (AI) has demonstrated
arXiv:2601.20969v3 Announce Type: replace Abstract: Epistemic planning extends (multi-agent) automated planning by making agents' knowledge and beliefs first-class aspects of the planning formalism. O
arXiv:2509.25236v3 Announce Type: replace Abstract: A core challenge in causal artificial intelligence is the principled coordination of multiple, imperfect, and subjective causal perspectives arising