Knowledge catalogue
arXiv:2504.08192v2 Announce Type: replace Abstract: Machine unlearning is a promising approach to improve LLM safety by removing unwanted knowledge from the model. However, prevailing gradient-based u
arXiv:2609.09113v1 Announce Type: cross Abstract: While research on recursive self-improvement (RSI) has predominantly automated model training pipelines, reliable autonomous development demands a mis
arXiv:2603.06356v2 Announce Type: replace Abstract: Cooperative transport and manipulation of heavy or bulky payloads by multiple manipulators requires coordinated formation tracking, while simultaneo
arXiv:2609.08444v1 Announce Type: new Abstract: Large language models (LLMs) and vision-language models (VLMs) have significantly advanced zero-shot task planning for embodied agents. However, most LL
arXiv:2609.05850v1 Announce Type: new Abstract: Despite the significant efforts devoted to aligning large language models (LLMs) with human values and ensuring safe deployment, recent work has reveale
arXiv:2609.08038v1 Announce Type: new Abstract: Smart healthcare monitoring systems require precise action recognition to ensure well-being and timely intervention in critical situations such as falls
arXiv:2609.07823v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) show strong progress on vision-language tasks, yet their reliability in safety-critical settings remains undere
Sam said that at the Senate in 2023, too; i was there, right next to him. and then he quietly lobbied against the EU AI Act. can anybody ever take him at his word? NEWS: OpenAI told congressional offi
arXiv:2609.08281v1 Announce Type: new Abstract: Object detectors have shown remarkable performance in various fields, among these medical imaging, surveillance, and autonomous driving. However, they a
@sama Maybe. Or maybe this isn’t even an isolated incident, just like the Hugging Face incident wasn’t quite a one-off: BREAKING: OpenAI might have stolen another major proof. In a detailed Mastodon p
arXiv:2609.07740v1 Announce Type: cross Abstract: Kolmogorov-Arnold Networks (KANs) replace the fixed activation functions and linear weights of Multi-Layer Perceptrons (MLPs) with learnable univariat
arXiv:2609.06385v1 Announce Type: new Abstract: Pretrained 3D generative models produce detailed geometry and appearance but are primarily designed for object-centric generation within a limited spati
arXiv:2609.05826v1 Announce Type: new Abstract: Dynamic programming for optimal classification trees becomes computationally expensive as the numbers of features and training samples increase. We deve
arXiv:2609.07857v1 Announce Type: cross Abstract: Robotic ophthalmic surgery offers high precision but introduces a 'sensory gap' by decoupling the surgeon from their instrument, resulting in a loss o
arXiv:2609.05594v1 Announce Type: new Abstract: Diverse and simulation-ready indoor scenes are essential for interactive entertainment and embodied AI, yet their scalable generation remains challengin
Scientists at frontier AI labs have unique insight into the most advanced models, often seeing the associated risks months before models are released to the public. Their perspective is vital for keep
arXiv:2609.08155v1 Announce Type: new Abstract: Scientific figures are the interface through which research claims are inspected and reused, but final published panels rarely expose the data or plotti
arXiv:2609.06061v1 Announce Type: new Abstract: Termination-based constrained reinforcement learning is attractive for safety-critical robotic deployments: it avoids online optimization at inference,
arXiv:2609.06257v1 Announce Type: new Abstract: Reliable marine-engine fault diagnosis in maritime IoT is challenged by distributed data ownership, heterogeneous fault distributions, and continuously
arXiv:2609.07605v1 Announce Type: new Abstract: Agentic systems can interpret user requests, search the live web, and use external tools, but their ability to transform retrieved web content into a us
arXiv:2609.06484v1 Announce Type: new Abstract: Planning with a generative model aims to estimate the value of a state using as few simulator calls as possible. SmoothCruiser achieves problem-independ
arXiv:2609.06468v1 Announce Type: new Abstract: K-Means is one of the most widely used clustering algorithms, but its susceptibility to initial centroid selection remains a primary bottleneck for its
arXiv:2609.08280v1 Announce Type: new Abstract: In multi-robot collaboration, task handovers rely on downstream verifiers performing remote attestation, which inspects sensor telemetry to ensure a rob
arXiv:2504.14373v4 Announce Type: replace-cross Abstract: Creating photorealistic 3D head avatars from limited input has become increasingly important for applications in virtual reality, telepresence
arXiv:2609.08867v1 Announce Type: new Abstract: Reasoning segmentation converts an implicit linguistic conclusion into a precise mask, requiring both semantic identification and spatial grounding. Exi
arXiv:2609.08346v1 Announce Type: new Abstract: Moving-object perception must decide which image regions correspond to real motion and keep every instance identified over time. Methods that read motio
arXiv:2609.07558v1 Announce Type: cross Abstract: Fibre optic sensing, such as distributed acoustic sensing (DAS), has become a widespread technology for geophysical studies. To process the large-scal
arXiv:2609.08461v1 Announce Type: cross Abstract: Parametric PDEs can admit different boundary conditions with different accuracy and computational cost. We introduce a framework for learning when one
arXiv:2609.06530v1 Announce Type: new Abstract: Continual learning is a crucial capability for Graphical User Interface (GUI) agents to adapt to evolving applications while retaining knowledge acquire
arXiv:2609.05859v1 Announce Type: cross Abstract: Learning with class-conditional label noise often relies on a transition model from latent clean classes to observed annotations. Forward correction e
arXiv:2609.07415v1 Announce Type: new Abstract: We present a self-supervised approach, Self-MVGTE, for estimating 3D gaze targets from multiple camera views. Unlike existing methods that independently
arXiv:2609.07982v1 Announce Type: new Abstract: Standard semi-supervised learning (SSL) typically relies on labelled and unlabelled data sharing a common marginal distribution. This assumption is ofte
arXiv:2609.06419v1 Announce Type: new Abstract: Medical vision-language models (VLMs) require confidence that reflects both answer correctness and patient-specific visual evidence. Recent GRPO-based m
arXiv:2609.05742v1 Announce Type: new Abstract: American Sign Language (ASL) generation remains challenging due to limited paired text-ASL motion data and the difficulty of learning motion representat
arXiv:2601.17090v3 Announce Type: replace Abstract: Partial differential equations (PDEs) govern complex systems, yet neural operators often struggle to efficiently capture the long-range, nonlocal in
arXiv:2609.07868v1 Announce Type: cross Abstract: We study the training dynamics of multiclass logistic regression on high-dimensional Gaussian mixture models with a large number of classes and establ
arXiv:2609.07997v1 Announce Type: new Abstract: We characterize the sharp structure-agnostic minimax risk for coefficient estimation in the partial linear model when the outcome and treatment nuisance
arXiv:2609.06547v1 Announce Type: new Abstract: Real-time 3D mapping is fundamental for autonomous robotic navigation, with Euclidean Signed Distance Fields (ESDFs) serving as the standard representat
arXiv:2609.06296v1 Announce Type: new Abstract: Self-supervised sign language representation learning must model two properties not central to natural-image SSL: signs are produced by a small set of a
arXiv:2609.08496v1 Announce Type: new Abstract: Sign language video generation demands precise hand and facial articulation, yet modern video diffusion models, trained predominantly on spoken-language
arXiv:2609.09152v1 Announce Type: cross Abstract: We study how far gradient descent (GD) can be accelerated by predetermined nonnegative stepsizes in smooth convex optimization. Writing p_{sil}=log_2(
arXiv:2609.08200v1 Announce Type: new Abstract: Token-level text anomaly detection, as an emerging trend of text anomaly detection, moves beyond coarse-grained document-level detection by localizing a
arXiv:2609.05533v1 Announce Type: new Abstract: Long-horizon manipulation is partially observable: the information needed to choose the next action may appear only in observations from minutes earlier
TorchServe is no longer maintained, leaving teams to own the entire GPU inference stack. The AWS Ray Serve Deep Learning Container is a supported, pre-tested container with the framework, GPU drivers,
arXiv:2609.07085v1 Announce Type: new Abstract: Single-view 3D reconstruction, also known as image-to-3D, is a persistently challenging task due to the extreme lack of information. Recently, diffusion
arXiv:2609.07269v1 Announce Type: new Abstract: This paper develops a singularity-free guiding vector field (SF-GVF) for path following on the special orthogonal group SO(3). First, we lift the Euclid
arXiv:2609.05521v1 Announce Type: cross Abstract: The limitations of on-board sensors and blind spots caused by occlusion cause the reduction of perception quality in autonomous vehicles. In such case
arXiv:2401.09895v3 Announce Type: replace Abstract: One of the fundamental challenges in cell microscopy (MS) image analysis is instance segmentation (IS), particularly when segmenting cluster regions
arXiv:2609.06718v1 Announce Type: new Abstract: Humanoid soccer is a challenging testbed for dynamic whole-body control, requiring robots to coordinate balance, locomotion, object interaction, and ski
arXiv:2609.05861v1 Announce Type: cross Abstract: One important AI-for-RAN use case is energy saving, in which radio resources and cell energy modes must be dynamically controlled without violating us
Small business owners deserve every advantage. Meet the 16 plugins that help take work off your plate so you can focus on what matters most—running your business. Explore the small business collection
arXiv:2609.07445v1 Announce Type: new Abstract: Autonomous tugboating is central for automating maritime operations such as port logistics and vessel maneuvering, where multiple tugboats must cooperat
arXiv:2609.06906v1 Announce Type: cross Abstract: We develop a new low-accuracy sampler, called smoothed Picard Hamiltonian Monte Carlo, which combines Gaussian smoothing, Picard iteration, and higher
arXiv:2609.07394v1 Announce Type: new Abstract: Anticipating whether a person will interact from one's own perspective is a highly intuitive task for humans, that relies on a combination of cues. We i
arXiv:2609.08221v1 Announce Type: new Abstract: Micro-actions are subtle, low-intensity non-verbal behaviors that provide cues to fine-grained human states, including emotions and intentions. Recogniz
arXiv:2609.06187v1 Announce Type: new Abstract: As the share of solar power grows, nowcasting weather-driven solar variability becomes critical for reliable energy system operation. State-of-the-art a
arXiv:2609.07590v1 Announce Type: new Abstract: We present our solution to the LUMPI track of the UCF UrbanTwin Sim2Real LiDAR Challenge at the 6th DriveX Workshop, ECCV 2026. The detector must be tra
arXiv:2609.07608v1 Announce Type: new Abstract: Bridging the simulation-to-reality gap in roadside LiDAR requires addressing several coupled discrepancies, including scene geometry, sampling density,
The fix: run the server detached/headless instead of keeping it attached to a console window. RTX 5090, ~27B NVFP4 model via ninfer: Terminal focused: 130–200 tok/s Terminal unfocused: 50–60 tok/s Cli
arXiv:2609.07983v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) have recently emerged as a promising approach for solving Partial Differential Equations (PDEs), offering a mes