Knowledge catalogue
arXiv:2610.18186v1 Announce Type: new Abstract: Large-scale applications of lifelong multi-agent path finding (LMAPF) call for computationally inexpensive movement decisions under changing traffic con
arXiv:2610.15628v1 Announce Type: new Abstract: Deep learning is now central to radiology, helping detect changes on X-rays, CTs, and MRIs. However, these systems are highly vulnerable to adversarial
arXiv:2610.15157v1 Announce Type: cross Abstract: Efficient perception is a prerequisite for the small, low-power devices targeted by robotics, mixed reality, autonomous driving, and drone application
arXiv:2604.01581v4 Announce Type: replace Abstract: Drone-view geo-localization (DVGL) typically assumes access to satellite imagery during task-specific development. We study a late-arriving-gallery
arXiv:2610.14094v1 Announce Type: new Abstract: Existing jailbreak attacks have exposed serious safety weaknesses in multimodal large language models (MLLMs). Most prior attacks rely on specially cons
arXiv:2610.17939v1 Announce Type: cross Abstract: Traditional time-series classification methods often operate as black boxes, providing a class prediction without indicating which time point or time
arXiv:2610.16457v1 Announce Type: new Abstract: Humans expand their locomotion capability by wearing appropriate footwear, such as hiking boots for mountains or skates for ice. Footwear changes the gr
arXiv:2510.18996v2 Announce Type: replace Abstract: Autonomous navigation in 3D is a fundamental problem for autonomy. Despite major advancements in terrestrial and aerial settings due to improved ran
arXiv:2610.14196v1 Announce Type: cross Abstract: Late-interaction (multi-vector) models represent documents using a set of token-level vectors, providing a middle ground between cross-encoders and de
arXiv:2610.18472v1 Announce Type: new Abstract: Few-step distillation reduces the sampling cost of diffusion and flow models, but existing approaches often require auxiliary score models or specialize
arXiv:2610.18135v1 Announce Type: new Abstract: World-model-based visual navigation enables action planning by predicting future states under candidate trajectories. However, long-horizon rollout rema
arXiv:2610.15585v1 Announce Type: new Abstract: World Action Models (WAMs), often built upon pretrained video-generation world models, have emerged as a promising framework for general-purpose and ope
arXiv:2610.17448v1 Announce Type: new Abstract: Gaps, skips, and mistakes are the normal state of a historical register: rows go missing, tables cross page breaks, columns slip under wrong names, and
arXiv:2610.14663v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) has emerged as a powerful dynamic scene representation, supporting real-time high quality rendering but suffers from prohib
arXiv:2610.16165v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated remarkable capabilities in solving complex tasks in coding, mathematical logic, and iterative reasoning
arXiv:2610.16448v1 Announce Type: new Abstract: Diffusion models, particularly Diffusion Transformers, achieve strong image and video generation quality but remain expensive at inference time due to r
Today I'm excited to share that New Material is joining @MistralAI to design sovereign frontier AI. We're establishing a new team, 'Solutions Design' within Mistral: working across product, engineerin
arXiv:2610.14683v1 Announce Type: new Abstract: Large language model (LLM)-based AI Scientists advance scientific discovery, yet they suffer from inefficiencies due to noisy observations. Existing pri
arXiv:2610.15570v1 Announce Type: cross Abstract: Settling one comparison between two truncation samplers has cost six thousand A100-hours, and nothing says in advance how far apart two samplers can b
arXiv:2610.16517v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are often pretrained via imitation learning, making reinforcement learning (RL) post-training important when deplo
arXiv:2603.18572v2 Announce Type: replace-cross Abstract: Deep unrolled models (DUM) have become the state-of-the-art for accelerated MRI reconstruction, yet their robustness under domain shift remain
arXiv:2610.14394v1 Announce Type: cross Abstract: Training large-scale recommender systems on dynamic industrial platforms, such as Short-Form Video (SFV) services with billions of daily interactions,
arXiv:2610.16969v1 Announce Type: cross Abstract: Latent Action Models (LAMs) can capture manipulation priors from action-free videos, but discrete latents usually impose a granularity bottleneck, lim
arXiv:2610.18697v1 Announce Type: cross Abstract: World models (WMs) and world-action models (WAMs) focus on future world prediction and executable action generation, respectively. Although these mode
arXiv:2610.17383v1 Announce Type: new Abstract: Large-scale repositories of wearable sensor data have enabled the development of foundation models for human activities and behavior. However, existing
arXiv:2610.14007v1 Announce Type: new Abstract: A familiar line of reasoning runs as follows: language models are flexible approximators trained under a strictly proper loss, so scale brings them clos
arXiv:2610.14530v1 Announce Type: new Abstract: Multi-robot systems (MRS) offer significant advantages over single-robot platforms by enabling information sharing and coordination for different tasks
David Silver is one of the all-time greats. He was the creator of AlphaGo, which changed the course of history by showing that neural nets could achieve superhuman performance for the first time. He a
Robots That Predict the Future: Dyna-2, Million-Hour World Models, & the Bitter Lesson of Robotics @DynaRobotics’s @JasonMa2020 explains how world-action models predict the future to guide physical ro
Physical AI needs context about its surroundings to adapt beyond a fixed set of instructions. Munich-based Spranic is building a spatial memory layer that records physical spaces and how they change.
Today, we’re open sourcing the full NVIDIA Run:ai platform as part of the NVIDIA DSX AI Factory Platform. Developers, platform teams, and partners can build on production-grade AI workloads and GPU or
Hi r/MachineLearning, Stjepan from Manning here. The mods approved this post, and I appreciate being welcomed back to share another book with you. We’ve just launched AI Recommender Systems: Transform
arXiv:2610.13572v1 Announce Type: new Abstract: Humanoid tennis requires reactive whole-body coordination under rapidly changing ball dynamics, yet collecting task-specific motion-capture demonstratio
arXiv:2610.13007v1 Announce Type: new Abstract: Learning-based methods have demonstrated strong performance in mapless robot navigation. However, a learned policy remains restricted to the embodiment
arXiv:2610.13929v1 Announce Type: new Abstract: Robot policies often convert sensing and control into fixed-rate observation-action sequences, leaving physical time implicit in sequence position. This
arXiv:2610.13276v1 Announce Type: new Abstract: Set-based language model routing aims to increase the coverage of the event where at least one model answers a query correctly while controlling the num
arXiv:2412.13844v2 Announce Type: replace-cross Abstract: Retrieval models for recommendation need to account for outcomes such as watch time while searching large item corpora efficiently. We present
Enterprise AI scalability is running into a hard budget wall for some customers. As agentic workloads multiply, cloud token bills are consuming allocations faster than planned, prompting companies to
arXiv:2507.19608v2 Announce Type: replace Abstract: On-device LLM inference is increasingly important for edge platforms but remains challenging due to high computational and memory demands and tight
arXiv:2610.12758v1 Announce Type: new Abstract: Language models have been adopted faster than evaluation practices that reliably assess their risks, and a growing share of use is affective rather than
arXiv:2610.13328v1 Announce Type: new Abstract: Serving a Mixture-of-Experts (MoE) model pays for expert precision twice: the resident footprint pays for every expert the router can reach, while each
arXiv:2610.12789v1 Announce Type: new Abstract: Self-evolving LLM agents typically improve how they act through accumulated experience, reflection, or skills. Yet even procedurally capable agents can
arXiv:2610.12793v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) policies fail on memory tasks, behaviour that depends on events observed long before the current frame, because
arXiv:2610.12528v1 Announce Type: new Abstract: Continuous glucose monitoring (CGM) foundation models encode each day as one vector that mixes who the person is, what happened that day and how the sen
arXiv:2610.13208v1 Announce Type: new Abstract: Time-series foundation models use the same network depth for every input, although forecasting windows differ in structure and difficulty. We test wheth
arXiv:2610.13764v1 Announce Type: cross Abstract: Prior-data fitted networks (PFNs) are trained to approximate the Bayesian posterior predictive distribution (PPD) of a synthetic prior, yet results ab
Coding agents have changed how fast teams ship, and more of the software they ship now includes agents. A production agent spans model calls, routing decisions, tools, and the infrastructure underneat
arXiv:2610.12886v1 Announce Type: new Abstract: Action-chunking policies predict future controls but execute only a prefix before replanning. How should a fixed action-token budget be organized to sup
arXiv:2610.13040v1 Announce Type: cross Abstract: Consumer rotating devices, including washing machines, air conditioners, electric fans, robotic vacuum cleaners, and home fitness equipment, increasin
arXiv:2610.13158v1 Announce Type: new Abstract: Reactive collision avoidance in unknown, cluttered environments must perceive obstacles and correct motion within milliseconds. Existing methods rely on
arXiv:2610.13534v1 Announce Type: new Abstract: Long-horizon embodied agents must maintain task-relevant information, coordinate heterogeneous robots, and adapt their decisions as execution unfolds. E
arXiv:2610.13838v1 Announce Type: new Abstract: Nearly every autonomous or semi-autonomous flipper controller assumes access to an elevation map of the terrain under and in front of the robot. The ter
Ambient intelligence startup Mistlabs Ltd. today brought its Ambi artificial intelligence system out of beta test on Apple Inc. devices, backed by 26 million in new funding. Ambi is designed to act wi
arXiv:2610.13943v1 Announce Type: new Abstract: Pretrained vision-language-action (VLA) models encode broad manipulation priors, yet adapting them to specific tasks requires balancing limited robot in
arXiv:2610.12684v1 Announce Type: new Abstract: Non-prehensile manipulation with mobile robots has primarily targeted placement in coarse goal regions. Precision placement has been studied with manipu
Over the last few months at @river_ai_inc we’ve developed what we believe is the best system in the world for building your own internal custom models, driven by 10 years of experience training top mo
arXiv:2610.12558v1 Announce Type: new Abstract: Humanoid robots have many degrees of freedom and contact surfaces, yet most loco-manipulation research restricts manipulation to the hands and avoids ot
arXiv:2610.13871v1 Announce Type: new Abstract: Many optimization problems provide direct access to only part of the gradient, while the remaining component must be inferred from function evaluations.
arXiv:2610.13296v1 Announce Type: cross Abstract: High-precision retrieval over external knowledge bases is essential for LLM agents to operate effectively. However, existing Information Retrieval (IR
arXiv:2610.13588v1 Announce Type: cross Abstract: Uncertainty quantification for electric vehicle (EV) charging demand is essential to turn the increasing pressure of EV adoption on power systems into