Knowledge catalogue
arXiv:2610.03221v1 Announce Type: new Abstract: Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they re
arXiv:2610.02801v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) achieves strong sample efficiency by planning within learned latent dynamics, yet its performance degrades sub
arXiv:2610.03510v1 Announce Type: cross Abstract: Recent advances in autoregressive video generation have improved temporal consistency over extended durations, yet interactive storytelling requires m
We're expanding our approach to content provenance to include text in response to EU regulatory requirements, while recognizing the significant limitations of current text watermarking technology. Our
arXiv:2610.02894v1 Announce Type: cross Abstract: Match only geometry you can identify; otherwise spread the penalty. We quantify that decision by the trust ratio tau = epsilon / gamma (estimation unc
arXiv:2610.03607v1 Announce Type: new Abstract: Learning general-purpose robot policies requires large-scale real-world interaction data, yet collecting robot demonstrations remains expensive and diff
arXiv:2610.02323v1 Announce Type: cross Abstract: Flow-based Vision-Language-Action (VLA) policies generate action chunks by transporting samples from a task-agnostic isotropic Gaussian source. As thi
arXiv:2610.02263v1 Announce Type: cross Abstract: Patient-level lung ultrasound (LUS) diagnosis requires integrating findings acquired across multiple anatomical zones, yet clinical examinations frequ
arXiv:2610.03546v1 Announce Type: new Abstract: EEG foundation models (EFMs) capture reusable knowledge from large-scale EEG data, while many EEG recordings also include companion physiological signal
Elon was thinking about superintelligence long before anyone in the mainstream even understood where superintelligence was heading He was deeply involved in the conversation around Nick Bostrom’s Supe
I've been looking at the <32B model space and keep coming back to an interesting question. A few years ago, projects like Hummingbird+ suggested that cheap custom accelerators (FPGA-based) might becom
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Hi folks, it's Lewis here from the post-training team at Hugging Face. We've been exploring how to train open models in different coding harnesses and wrote up a looong guide on how we solved this usi
arXiv:2610.00125v1 Announce Type: cross Abstract: One-Pixel Attacks (OPAs) represent one of the most extreme demonstrations of adversarial fragility in deep learning, where modifying a single pixel ca
arXiv:2610.00111v1 Announce Type: new Abstract: Model judges now supervise multimodal systems at scale, filtering training data, selecting outputs, and supplying the reward that shapes multimodal reas
arXiv:2610.01893v1 Announce Type: cross Abstract: By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, he
arXiv:2610.00926v1 Announce Type: cross Abstract: Autonomous driving is a cornerstone technology for the future of intelligent transportation, where end-to-end learning has emerged as a transformative
arXiv:2610.00126v1 Announce Type: cross Abstract: Agent developers increasingly compare prompts, tools, policies, and diagnosis algorithms through simulator-grounded verifiers. A verifier can neverthe
arXiv:2610.00535v1 Announce Type: cross Abstract: Uncertainty quantification is critical in scientific machine learning, where black-box, image-based models are increasingly deployed in high-stakes se
arXiv:2610.01185v1 Announce Type: new Abstract: Multiple UAVs can cooperatively transport heavy payloads while controlling their position and orientation. Trajectory-based methods offer high agility w
arXiv:2610.01389v1 Announce Type: new Abstract: Modern retrieval systems must both be automated and interactive, allowing users to search and refine results in real time. We present AiSearch, a flexib
arXiv:2610.01716v1 Announce Type: cross Abstract: Artificial intelligence presents an unusually difficult problem for global governance. The technology develops rapidly, crosses borders easily, and is
arXiv:2610.02122v1 Announce Type: cross Abstract: Real-world enterprise data science and analytics workflows require reasoning across dozens of tables, performing statistical analyses, and acting on t
arXiv:2610.01741v1 Announce Type: new Abstract: Predictive Vision-Language-Action (VLA) models aim to improve robotic manipulation via future observation or world dynamics forecasting. However, existi
arXiv:2610.00257v1 Announce Type: new Abstract: In standard transformer attention, a source token sends the same value vector to every receiver. The query determines how much to attend but not what to
arXiv:2610.00347v1 Announce Type: cross Abstract: Self-modifying AI agents can replace, fork, and roll back identity-bearing software while descendants remain executable. Per-successor authorization d
arXiv:2610.01215v1 Announce Type: new Abstract: GUI agents require high-quality interaction trajectories to learn how software environments respond to actions, maintain state, and support multi-step w
arXiv:2610.01415v1 Announce Type: new Abstract: Large language model (LLM) agents can now undertake increasingly complex tasks, but the way they organize interaction history into memory does not ensur
arXiv:2610.00315v1 Announce Type: cross Abstract: Historical Manchu documents preserve invaluable linguistic and cultural heritage, yet their digitization is hindered by severe degradations and the sc
arXiv:2610.01116v1 Announce Type: new Abstract: As the capabilities and ubiquity of Large Language Models (LLMs) grow, so does their environmental footprint. Despite calls for responsible AI, the mach
arXiv:2610.00619v1 Announce Type: cross Abstract: In this paper, we extend earlier findings of supra-competitive outcomes in optimal-execution games by identifying a learned punitive mechanism that de
arXiv:2610.01972v1 Announce Type: new Abstract: We present Informed Belief Localization Trees* (Informed BLT*), a sampling-based belief space planning (BSP) algorithm that scales to large outdoor digi
arXiv:2610.01039v1 Announce Type: new Abstract: While recent video generative models can synthesize high-fidelity videos, they struggle to portray plausible physical interactions and the resulting sta
arXiv:2610.02013v1 Announce Type: new Abstract: Equivariant machine learning interatomic potentials (MLIPs) have revolutionized atomistic modeling, but accurate treatment of complex materials and mole
arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook
arXiv:2610.02070v1 Announce Type: new Abstract: Memory-augmented large language models must decide which memories to retain, and recent systems do so by estimating each memory's effect on task perform
arXiv:2610.00431v1 Announce Type: cross Abstract: Continual parameter-efficient fine-tuning for large language models (LLMs) must balance retention of previously acquired knowledge, adaptation to new
arXiv:2610.01856v1 Announce Type: new Abstract: Vision-language-action (VLA) models unify visual perception, language understanding, and action generation, offering new opportunities for automation in
arXiv:2610.01331v1 Announce Type: new Abstract: Continual personalization of text-to-image diffusion models requires sequentially acquiring new concepts while retaining previously learned ones. Howeve
arXiv:2610.00174v1 Announce Type: new Abstract: Breast cancer is a significant contributor to female mortality across the world, displaying one of the highest oc currence rates among the various cance
arXiv:2610.00894v1 Announce Type: new Abstract: Recent works on continuous diffusion for discrete data have demonstrated performance on par with comparable discrete diffusion models. However, these co
arXiv:2610.00992v1 Announce Type: cross Abstract: Learning-based driving planners are usually trained and evaluated in open loop against logged trajectories. In closed loop, a trajectory with small di
arXiv:2610.00425v1 Announce Type: cross Abstract: Code generation has emerged as a central capability of large language models, with coding agents now able to produce functionally correct software pro
arXiv:2610.01773v1 Announce Type: cross Abstract: The central challenge in de novo protein design is generating plausible, mutually compatible structures and sequences, such that each designed sequenc
arXiv:2610.01710v1 Announce Type: new Abstract: Visual grounding localizes an object described by language with a bounding box. Most multimodal grounding models compress target identification, spatial
arXiv:2610.00418v1 Announce Type: new Abstract: Scaling Transformers to long contexts is constrained by the quadratic cost of self-attention and the linear growth of key-value cache memory transfer. S
arXiv:2610.00973v1 Announce Type: new Abstract: Science teachers frequently search for documentary excerpts not by describing what appears on screen, but by querying the abstract concepts they intend
arXiv:2512.00939v3 Announce Type: replace-cross Abstract: Recent progress in contact-rich robotic manipulation has been striking, yet most deployed systems remain confined to simple, scripted routines
arXiv:2606.15420v2 Announce Type: replace-cross Abstract: Safety evaluations test a policy on prompts that omit the incentive information deployment supplies: a commission, a performance score, a dash
arXiv:2610.00840v1 Announce Type: cross Abstract: Transformer-based large language models (LLMs) such as RoBERTa represent text using contextual word embeddings (CWEs), which alter the embeddings asso
arXiv:2610.01301v1 Announce Type: cross Abstract: Most current grasp synthesis systems are trained offline and remain fixed during deployment. While this works well when deployment conditions resemble
arXiv:2610.01397v1 Announce Type: new Abstract: Dynamic humanoid motions such as flips risk hardware damage due to suboptimal policies, disturbances or sim-to-real gaps. A motion tracking policy offer
arXiv:2610.01963v1 Announce Type: new Abstract: Emergency department (ED) triage is a high-stakes prioritization task in which demographic, socioeconomic, and system-context information may improperly
arXiv:2610.00759v1 Announce Type: cross Abstract: Cyber attack agents are typically trained and evaluated within a single simulator, making it unclear whether learned policies transfer beyond the envi
arXiv:2610.00680v1 Announce Type: cross Abstract: Curvature is often treated as an intrinsic property of a representation, although its empirical effect also depends on coordinate scale, learned logit
arXiv:2610.00961v1 Announce Type: new Abstract: As code generation is increasingly delegated to AI systems, the bottleneck is shifting from writing code to supervising the systems that write it --- a
arXiv:2610.02185v1 Announce Type: new Abstract: Looped Transformers achieve parameter efficiency by repeatedly executing a shared block across recurrent loops. Each loop yields an intermediate represe
arXiv:2610.01914v1 Announce Type: new Abstract: Decompositional scene reconstruction aims to reconstruct high-quality objects and background, yet existing methods still struggle with the level of qual