Knowledge catalogue
arXiv:2607.25270v1 Announce Type: cross Abstract: Activation steering controls language models by adding vectors or features to hidden states at inference time, but the upstream source of these steeri
Who on earth came up with 5 hour limits? The day is 24 hours long. While do our limit times shift by an hour each day. Pls if you are going to have limits 4 or 6 hours. Hello people of Sol! I've reset
arXiv:2607.25234v1 Announce Type: new Abstract: Stereo depth estimation for driving, robotics and augmented reality must run at high resolution under tight latency budgets, yet in transformer-based ma
arXiv:2607.25648v1 Announce Type: cross Abstract: Public services face growing pressure to adopt artificial intelligence (AI) to close the gap between rising demand and falling resources. That pressur
arXiv:2607.26037v1 Announce Type: new Abstract: We present Wonder, a general-purpose video world model for real-time, camera-controllable world exploration. Given an image or a conditional video, Wond
arXiv:2607.25765v1 Announce Type: new Abstract: Enterprise agents often need to integrate heterogeneous knowledge sources: documents for narrative facts, tables for computation, and dependency graphs
arXiv:2607.25298v1 Announce Type: new Abstract: The high proportion of wind power connected to the grid places higher demands on fine-grained knowledge of regional wind fields. Since the wind informat
arXiv:2607.24113v1 Announce Type: cross Abstract: Previous research has shown that a human-like robot's acceptance heavily depends on the setting in which it operates and its ability to perform releva
arXiv:2607.23439v1 Announce Type: cross Abstract: Graphical models are ubiquitous in social and empirical science as they are intuitive and easy to use. These models belong to the broader class of Mar
arXiv:2607.23770v1 Announce Type: new Abstract: In this work we study Automatic Target Recognition (ATR) for Synthetic Aperture Sonar (SAS) data with a focus on deep neural networks (DNNs). The main c
arXiv:2607.24275v1 Announce Type: cross Abstract: Ethical governance of AI-driven systems is often expressed through high-level principles and static documentation, creating a gap between regulatory r
arXiv:2607.23633v1 Announce Type: cross Abstract: Sky-image irradiance studies often compare forecasting systems in which the image encoder, temporal model, fusion block, target definition, and traini
arXiv:2607.24663v1 Announce Type: cross Abstract: Scientific user facilities accumulate decades of operational knowledge that no single search index covers: electronic logbooks, technical documents, i
arXiv:2607.23869v1 Announce Type: cross Abstract: Randomized features provide a scalable approximation to kernel machines, but their performance depends strongly on the choice of feature distribution.
arXiv:2607.24031v1 Announce Type: new Abstract: Brain-Machine Interfaces (BMIs), which link the brain to external devices, hold great potential in rehabilitation, human performance augmentation, and h
arXiv:2607.22740v1 Announce Type: new Abstract: Weakly supervised pipelines for medical imaging have become increasingly popular over the years. These systems often include multiple stages and compone
arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi
arXiv:2607.23784v1 Announce Type: cross Abstract: While vision-language-action models have demonstrated impressive zero-shot manipulation capabilities, they remain fundamentally black box policies tha
arXiv:2607.22567v1 Announce Type: cross Abstract: Zeroth-order Newton-type methods are useful when gradients and Hessians are unavailable, but they behave quite differently from first-order gradient-f
arXiv:2607.23806v1 Announce Type: cross Abstract: Improving a language model today means retraining it: enormous compute, a new opaque model each cycle, non-deterministic output. We take the opposite
arXiv:2509.10847v3 Announce Type: replace-cross Abstract: As artificial intelligence (AI) companions become capable of human-like communication, including telling jokes, understanding how people cogni
arXiv:2603.19322v2 Announce Type: replace-cross Abstract: While deep learning (DL)-based methods have achieved remarkable success in continuous wireless resource allocation, efficient solutions for pr
arXiv:2601.09624v2 Announce Type: replace-cross Abstract: Machine unlearning is becoming essential for building trustworthy and compliant language models. Yet unlearning success varies considerably ac
arXiv:2607.24622v1 Announce Type: cross Abstract: We study imbalanced crowdsourcing with a focus on class-dependent annotator accuracy, a setting that, to the best of our knowledge, remains relatively
arXiv:2607.24525v1 Announce Type: cross Abstract: Automated solar filament detection using deep learning faces several challenges. Semantic segmentation of solar filaments is a complicated multiscale
arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy
arXiv:2607.23480v1 Announce Type: new Abstract: Variational autoencoders (VAEs) transform high-dimensional, often noisy data into a compact latent representation, making downstream optimization more t
arXiv:2607.22722v1 Announce Type: cross Abstract: Almost all adversarial attacks add an imperceptible perturbation to fool a model. We instead study the opposite: a large, clearly visible perturbation
arXiv:2607.24223v1 Announce Type: new Abstract: Relevance is a query-dependent estimate of whether a document or excerpt contains useful evidence. Existing retrieval agents use relevance to select top
arXiv:2607.24317v1 Announce Type: new Abstract: The dynamics of a holonomically constrained rigid body can be modeled by Newton-Euler equations subjected to geometric constraints. This is frequently f
arXiv:2607.23235v1 Announce Type: new Abstract: Image captioning is a primary task in vision--language research, yet assessing how faithfully a caption preserves image semantics without relying on ref
arXiv:2607.23321v1 Announce Type: cross Abstract: Evaluating camera image signal processing (ISP) pipelines requires measuring low-level artifacts introduced by operations such as denoising, demosaici
arXiv:2607.22858v1 Announce Type: new Abstract: Personalization of impedance controllers for powered prosthetic legs is critical to accommodating individual gait biomechanics but remains challenging.
arXiv:2607.22620v1 Announce Type: cross Abstract: Yun, Sra, and Jadbabaie (COLT 2021, open question) conjectured the SS--RS--GD inequalities: for well-conditioned symmetric matrices A_1,ots,A_n, the o
arXiv:2607.23120v1 Announce Type: cross Abstract: Stock recommendation systems face the dual challenge of adapting to rapidly changing market conditions while maintaining low-latency predictions for e
arXiv:2607.23183v1 Announce Type: cross Abstract: Neurological disorders are a leading cause of global disability and are increasingly linked to environmental chemical exposures. Yet neurotoxicity ass
arXiv:2512.23190v3 Announce Type: replace Abstract: Online eXp-concave Optimization (OXO) is a fundamental problem in online learning, where the goal is to minimize regret when loss functions are expo
arXiv:2607.23397v1 Announce Type: new Abstract: Hierarchical neural networks are widely used in artificial intelligence, yet their mathematical properties remain incompletely understood. In the infini
arXiv:2502.16533v3 Announce Type: replace-cross Abstract: Graph Transformers (GTs) have demonstrated a strong capability in modeling graph structures by addressing the intrinsic limitations of graph n
arXiv:2607.24024v1 Announce Type: new Abstract: Stereo matching and surface normal estimation are fundamental tasks in 3D vision. However, existing feed-forward stereo methods still struggle to produc
arXiv:2607.22682v1 Announce Type: new Abstract: We introduce a vocabulary for automated research systems built from one or more agents to make their design choices easier to describe and compare. The
arXiv:2607.24268v1 Announce Type: new Abstract: Language-model benchmarks collapse two distinct measurement questions into a single accuracy score: whether a response reached an evaluable state, and w
arXiv:2607.24409v1 Announce Type: new Abstract: Accurate and reliable pose information with respect to a reference frame is increasingly demanded across applications such as autonomous navigation, sur
arXiv:2607.23809v1 Announce Type: new Abstract: Agentic tasks are inherently long-horizon and multi-turn, constantly accumulating context through interactions with the environment. Existing context co
arXiv:2607.24062v1 Announce Type: cross Abstract: Reinforcement Learning (RL) training for Large Language Models (LLMs) often suffers from instability due to the discrepancy between training and infer
Across eight case studies spanning industry and academia, we explore what this shift means for scientific computing—and why human verification, stewardship, and long-term maintenance matter. https://o
Cloud security startup Act Security Ltd. says it’s primed and ready to help enterprises safely deploy artificial intelligence agents at large scale after raising 60 million in funding across two round
arXiv:2603.05147v2 Announce Type: replace Abstract: Current research on Vision-Language-Action (VLA) models predominantly focuses on enhancing generalization through reasoning techniques. While effect
arXiv:2607.23602v1 Announce Type: cross Abstract: Controllers based on sampling and latent world models assign a predicted terminal cost to each candidate action sequence, choose the minimum, execute
arXiv:2601.22496v2 Announce Type: replace-cross Abstract: In offline goal-conditioned reinforcement learning (GCRL), hierarchical approaches decompose long-horizon tasks into high-level subgoal predic
arXiv:2607.23040v1 Announce Type: cross Abstract: This work proposes an actuator-aware spatiotemporal tube (STT) synthesis framework to accomplish temporal reach-avoid-stay (T-RAS) tasks for an unknow
arXiv:2607.23058v1 Announce Type: cross Abstract: Multilingual reasoning evaluation overwhelmingly relies on translating English benchmarks, a practice that introduces linguistic artifacts and fails t
arXiv:2607.22891v1 Announce Type: new Abstract: Medical image segmentation is a fundamental task in computer-aided diagnosis, yet it remains challenging due to the complexity of anatomical structures
arXiv:2601.18350v5 Announce Type: replace-cross Abstract: Large language models fine-tuned via a two-stage pipeline (domain adaptation followed by instruction alignment) can exhibit non-trivial interf
arXiv:2607.23987v1 Announce Type: cross Abstract: We study streaming federated learning with limited client memory, where newly generated training data incur time-varying sampling costs and must be se
arXiv:2607.23165v1 Announce Type: cross Abstract: We propose ABF-T-GLCP, a model-agnostic framework for forecasting and uncertainty quantification in nonstationary multivariate time series. The centra
arXiv:2607.22746v1 Announce Type: cross Abstract: Rapid post-disaster response requires timely, building-level information on whether structures remain intact, are damaged, or are destroyed. Post-even
arXiv:2607.23882v1 Announce Type: new Abstract: Modern System-on-Chip (SoCs) often contain hundreds of millions to tens of billions of gates, making existing Hardware Trojan (HT) detection methods imp
arXiv:2607.23002v1 Announce Type: cross Abstract: Large language models increasingly write both code and the tests meant to check it; coverage records what ran, not what was verified. We study an adve
arXiv:2607.22917v1 Announce Type: new Abstract: Large Language Model (LLM) agents have significantly improved coding and programming workflows. Claude Code, in particular, is one of the most powerful