Knowledge catalogue
arXiv:2509.14143v2 Announce Type: replace Abstract: Vision-language-action (VLA) models have recently emerged as a promising paradigm for robotic control, enabling end-to-end policies that ground natu
arXiv:2606.01494v1 Announce Type: cross Abstract: Agent skills extend AI agents with reusable instructions, tools, scripts, references, and workflows, establishing a security boundary distinct from bo
Climbing with no distillation, like the Big Boys do, has been super fun! Read the tech report for a taste of our ̶s̶u̶f̶f̶e̶r̶i̶n̶g̶ journey Super excited to announce seven new world-class MAI models
arXiv:2606.02568v1 Announce Type: new Abstract: Clinical practice is not the selection of an answer from enumerated options: a physician gathers heterogeneous information incrementally and commits to
arXiv:2512.05671v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have achieved remarkable success in dyadic (one-on-one) instruction, they face significant challenges in One-to-M
arXiv:2506.22881v3 Announce Type: replace Abstract: Density ratio estimation is a core concept in statistical machine learning because it provides a unified mechanism for tasks such as importance weig
arXiv:2504.05033v3 Announce Type: replace-cross Abstract: Cloth manipulation is a difficult problem mainly because of the non-rigid nature of cloth, which makes a good representation of deformation es
arXiv:2606.01946v1 Announce Type: new Abstract: Embedded magnetic tracking holds highly attractive prospects for remote navigation of endoluminal medical devices. However, existing six-degree-of-freed
arXiv:2606.00269v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models can be steered at test time by intervening on semantically meaningful internal directions, but existing methods use
arXiv:2606.02172v1 Announce Type: cross Abstract: Learning discriminative visual representations from distributed, heterogeneous data is a fundamental challenge in Federated Learning (FL). Prototype-b
arXiv:2606.00074v1 Announce Type: cross Abstract: Reliable seizure prediction is a prerequisite for closed-loop neurostimulation therapy, yet existing methods rarely account for the variability in EEG
arXiv:2606.00327v1 Announce Type: cross Abstract: Clustering is widely used across the sciences as the foundation for downstream data-driven scientific discoveries. However, clustering results are hig
arXiv:2606.01951v1 Announce Type: new Abstract: Vision-language-action (VLA) models are promising for diverse robotic tasks, but their performance heavily depends on large-scale high-quality training
arXiv:2606.00837v1 Announce Type: cross Abstract: Diffusion models provide strong priors for generating structured data, but many tasks require outputs beyond the scale on which these models are typic
arXiv:2606.00101v1 Announce Type: cross Abstract: With the rapid advancement of artificial intelligence generated content (AIGC) technologies, video forgery has become increasingly prevalent, posing n
arXiv:2603.03202v3 Announce Type: replace Abstract: As large language models (LLMs) advance their mathematical capabilities toward the IMO and research level, the scarcity of challenging, high-quality
arXiv:2606.00472v1 Announce Type: cross Abstract: Conventional tissue image analysis software provides foundational capabilities for cellular analysis, including segmentation, basic morphological feat
Codex CLI now runs inside Devin Desktop. You can pair your Codex subscription with Devin Desktop to have native multi-agent orchestration. Learn more about using your favorite agents in Devin Desktop:
OpenAI's Codex is an AI system that translates natural language instructions into code, designed to assist users across different roles, tools, and workflows. It enables developers, non-technical user
OpenAI's Codex is evolving beyond code generation to become a general productivity tool accessible to non-programmers for knowledge work tasks. The tool leverages large language models to assist with
arXiv:2606.00026v1 Announce Type: new Abstract: This paper investigates whether combining cognitively grounded linguistic features with transformer-based embeddings improves automated detection of dep
arXiv:2606.02194v1 Announce Type: new Abstract: Distilling expert demonstration data into large generative models using behavioral cloning is a scalable approach to learning capable policies for robot
arXiv:2606.00890v1 Announce Type: new Abstract: Ultrasound is the most widely used real-time imaging modality in clinical practice, yet per-frame video annotation remains a major bottleneck: expert la
arXiv:2606.00100v1 Announce Type: cross Abstract: Self-supervised deep learning-based methods have shown great promise for accelerated magnetic resonance imaging (MRI) reconstruction, achieving high i
arXiv:2602.07218v2 Announce Type: replace-cross Abstract: Adaptability has been regarded as a central feature in the foundation models, enabling them to effectively acclimate to unseen downstream task
arXiv:2606.00658v1 Announce Type: cross Abstract: Large video diffusion models achieve strong visual quality but remain expensive to deploy because each sample requires many denoising steps and a larg
arXiv:2606.01895v1 Announce Type: cross Abstract: With the growing number of satellites in low Earth orbit (LEO) constellations, the near-Earth space environment has become increasingly congested, mak
arXiv:2606.00954v1 Announce Type: new Abstract: Achieving high-fidelity object-level control in Diffusion Transformers remains a significant challenge despite the introduction of structural priors lik
arXiv:2606.00950v1 Announce Type: new Abstract: Unsupervised skill discovery (USD) aims to learn diverse behaviors without reward functions, but often results in task-irrelevant or hazardous behaviors
arXiv:2606.02372v1 Announce Type: new Abstract: Equipping language agents with world models enables them to anticipate environment dynamics and evaluate candidate actions before execution. However, ex
Come check out our booth at Snowflake Summit 2026 ❄️ We Parse PDFs ❄️ Come meet the LlamaIndex Team at Snowflake Summit 2026. It might be chilly in Snow Park ☃️ but the AI infrastructure market is red
arXiv:2606.00756v1 Announce Type: new Abstract: Deploying lightweight Large Language Model (LLM) agents on edge servers can reduce latency and move agentic services closer to users, but resource-const
arXiv:2606.01897v1 Announce Type: new Abstract: Traditional Video Quality Assessment (VQA) focuses narrowly on aesthetic fidelity, overlooking the complex social dynamics that define quality in User-G
arXiv:2606.00145v1 Announce Type: cross Abstract: Vision-language-action (VLA) agents can execute natural-language instructions, yet deployed systems still lack an operational interface: deciding when
arXiv:2606.01513v1 Announce Type: cross Abstract: High-stakes enterprise document generation, including financial dispute narratives, compliance notices, and audit summaries, demands schema correctnes
arXiv:2606.00047v1 Announce Type: cross Abstract: Frontier AI governance often centres on the model-level governance paradigm, which assumes that a model's capability profile is primarily a function o
arXiv:2606.01468v1 Announce Type: cross Abstract: Due to their explicit priors and ability to model uncertainty, Bayesian methods have played a major role in dynamical latent variable modeling of sing
Computer-use agents are moving from the cloud to your local machine. Fast. When we launched Holo3 two months ago, the production feedback was clear: digital agents need to be blazing fast, cost-effect
Max Cherney / Reuters: Computex 2026: ARM CEO Rene Haas says Oracle and ByteDance are among the customers of the company's new AGI CPU data center chips — Chinese tech company ByteDance and U.S. data
arXiv:2603.02237v2 Announce Type: replace-cross Abstract: Representation steering offers a lightweight mechanism for controlling the behavior of large language models (LLMs) by intervening on internal
arXiv:2606.01643v1 Announce Type: new Abstract: Sign Language Production (SLP) is the task of generating avatar sign language motion from natural language text. The quality of the generated motion is
arXiv:2606.01329v1 Announce Type: new Abstract: We show that computing the log-partition function (free-energy) of conditioned inhomogeneous Curie--Weiss spin Hamiltonians reduces to an unbalanced 2 o
Conductor's parallel coding agents were local-only, but now they can run remotely on Vercel. 'Our customers can't tell the difference because Vercel's Sandboxes are so fast.' https://vercel.com/blog/h
arXiv:2606.00761v1 Announce Type: cross Abstract: SwiGLU has become a standard gated activation in modern Transformer MLPs, yet its gate sharpness -- the smoothness and selectivity of the gating funct
Congrats @cognition on Devin Desktop! We've been prototyping with the team to connect local agents and @harvey's Spectre cloud agents, so context can follow engineers across their stack. Excited about
🎉 Congratulations to @OdessiaTravel on their public launch! Odessia is an AI-powered travel agent that allows users to plan and book entire trips in one conversation. The team used LangSmith and LangG
Google Cloud Storage (GCS) is a foundational component of the modern agentic tech stack and the preferred home for unstructured data at scale. As enterprises deploy agents in production, the critical
arXiv:2606.01223v1 Announce Type: cross Abstract: Despite substantial progress in long-context modeling, existing benchmarks remain confined to factual memory for explicit recall, failing to measure t
arXiv:2602.03024v2 Announce Type: replace-cross Abstract: Deep Equilibrium Models (DEQs) have emerged as a powerful paradigm in deep learning, offering the ability to model infinite-depth networks wit
arXiv:2606.01789v1 Announce Type: new Abstract: In graphical causal model, causal discovery aims to construct a causal graph based on numerical data and domain knowledge in plain text. However, the ev
arXiv:2606.02211v1 Announce Type: cross Abstract: Large language models are often influenced by extraneous input features, such as cues revealing a user's preferred answer. Consistency training reduce
arXiv:2606.01400v1 Announce Type: cross Abstract: Evaluating large language models (LLMs) across comprehensive benchmarks is expensive and time-consuming. We propose a graph-based prompt selection fra
arXiv:2603.00829v2 Announce Type: replace-cross Abstract: Safe deployment of Large Language Model (LLM) agents in autonomous settings requires reliable oversight mechanisms. A central challenge is det
arXiv:2606.00374v1 Announce Type: new Abstract: Recent advances in reinforcement learning (RL) have demonstrated impressive whole-body agility for humanoid robots, yet ensuring safety and satisfying c
arXiv:2606.01747v1 Announce Type: cross Abstract: Through digital humanities research and scale-up historical data analysis, a significant amount of traditional historical text is converted into struc
arXiv:2606.01134v1 Announce Type: cross Abstract: Automatically distinguishing child-directed speech from adult-directed speech in long-form recordings is key to scalable analyses of children's langua
arXiv:2603.16572v2 Announce Type: replace-cross Abstract: Agent skills extend local AI agents, such as Claude Code and OpenClaw, with additional functionality. Their growing popularity has led to dedi
arXiv:2606.01863v1 Announce Type: new Abstract: Continual learning struggles to balance retaining past knowledge with absorbing new tasks. Stefan-CL elegantly resolves this stability-plasticity dilemm
Continual Learning involves engineering whole systems including Efficient Verifiers to make RL/fine-tuning and running evaluations much cheaper at scale! some initial work we’re releasing from LangCha
arXiv:2606.00229v1 Announce Type: cross Abstract: Natural language is a powerful reasoning medium for language and vision-language models, but it is mismatched to the granularity of continuous control