Knowledge catalogue
arXiv:2608.20337v1 Announce Type: cross Abstract: Accounting for information flow on the path space of trajectories of a nonnegative martingale yields exact variational identities for it, even at arbi
arXiv:2608.20281v1 Announce Type: cross Abstract: Large language models often fail to answer questions about a bounded document collection when the source documents are not retrieved at inference time
arXiv:2608.20220v1 Announce Type: new Abstract: Legal AI systems are increasingly used to answer legal questions, yet existing benchmarks assume queries arrive fully specified. In practice, users omit
arXiv:2608.20312v1 Announce Type: new Abstract: The capability to perceive and synthesize human-human interactions is fundamental to developing intelligent digital human systems. However, existing dat
arXiv:2608.19222v1 Announce Type: new Abstract: Social relationships shape access to resources, exposure to conflict and group stability, yet automated livestock monitoring typically treats behaviour
arXiv:2608.19881v1 Announce Type: cross Abstract: Radio frequency (RF) fingerprinting authenticates wireless devices from hardware-induced I/Q impairments, typically with deep learning feature extract
arXiv:2608.19893v1 Announce Type: cross Abstract: Where does the novelty a base language model produces with no task come from, and what can an LLM judge of a long stream actually see? We dismantle a
arXiv:2608.19584v1 Announce Type: new Abstract: We study landscapes for complex-parameterized networks. Our approach is motivated with an information-theoretic manifold perspective of the parameter an
arXiv:2608.19740v1 Announce Type: new Abstract: This paper presents an open-source software stack that restores ROS 2 support for the Franka Emika Panda robot while resolving the long-standing unrelia
arXiv:2603.18853v3 Announce Type: replace-cross Abstract: Autonomous aerial vehicles (AAVs) enable data collection for sixth-generation Internet-of-Things networks, but their trajectories couple nonli
arXiv:2505.05203v3 Announce Type: replace-cross Abstract: With the increasing penetration of renewable energy and inverter-based resources, traditional physics-based power-system operation faces growi
arXiv:2401.07468v4 Announce Type: replace-cross Abstract: The proposed model, CarSpeedNet, estimates scalar vehicle speed from a window of three-axis smartphone acceleration, without gyroscope, wheel-
arXiv:2608.19688v1 Announce Type: cross Abstract: We develop a geometric framework for learning deterministic and stochastic forced Hamiltonian systems with neural networks. Motivated by the Lagrange-
arXiv:2608.19953v1 Announce Type: new Abstract: Mixed-Integer Linear Programming (MILP) is a fundamental problem class in operations research and combinatorial optimization, with broad applications to
arXiv:2608.19684v1 Announce Type: new Abstract: Recent studies investigate how to leverage pre-collected datasets to improve the policy performance and sample efficiency of RL. One promising approach
arXiv:2608.19977v1 Announce Type: new Abstract: Although legged animals are capable of performing explosive motions while traversing confined spaces, replicating this behavior in quadrupedal robots ha
arXiv:2608.19920v1 Announce Type: new Abstract: A lot of prior work addressed key-value (KV) cache selection and compression by sparse attention to enable long-context inference for transformer langua
arXiv:2608.19785v1 Announce Type: cross Abstract: Discovering dynamical systems from trajectory data is a central problem in applied mathematics and engineering. Whilst recent advances in machine lear
arXiv:2608.19375v1 Announce Type: new Abstract: High-fidelity embodied AI simulators provide realistic evaluation of complex robotic systems, but their computational cost limits their direct use for l
arXiv:2608.19738v1 Announce Type: cross Abstract: Full-cycle biventricular geometry is essential for characterizing cardiac function. However, dense and temporally consistent 3D+t biventricular meshes
arXiv:2511.03996v2 Announce Type: replace Abstract: Humanoid soccer poses a representative challenge for embodied intelligence, requiring robots to coordinate agile locomotion with unreliable visual p
arXiv:2608.20256v1 Announce Type: new Abstract: Reasoning language models trained with reinforcement learning typically operate under a fixed token budget rather than an explicitly adaptive one, which
arXiv:2608.20061v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures significantly expand model capacity without a proportional increase in computational cost. However, optimizing
arXiv:2608.19522v1 Announce Type: cross Abstract: Scan-to-map LiDAR odometry drifts unboundedly along the unobservable axes of geometrically degenerate environments like tunnels and corridors, and exi
arXiv:2608.19369v1 Announce Type: new Abstract: Statistical watermarks for language models live in the freedom of the signifier: they choose among tokens that are nearly equivalent in meaning, and the
arXiv:2608.19863v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has driven substantial progress in audio representation learning, though existing methods have increasingly relied on e
arXiv:2608.19463v1 Announce Type: new Abstract: Anomaly detection in tabular data is challenging because abnormal samples often arise as violations of cross-feature dependencies rather than simple mar
arXiv:2608.19790v1 Announce Type: new Abstract: Discovering materials with desirable properties often requires searching large candidate spaces while experimental or computational evaluations remain c
arXiv:2608.19436v1 Announce Type: cross Abstract: Alzheimer's disease (AD) progresses as a continuous biological process, whereas most existing neuroimaging-based artificial intelligence methods remai
arXiv:2608.19800v1 Announce Type: cross Abstract: Low-Rank Adaptation (LoRA) is a prominent fine-tuning method for large models, achieving competitive performance with reduced memory overhead. However
arXiv:2608.19703v1 Announce Type: cross Abstract: Sequential agent search accumulates changes from its current champion but discards alternative branches; independent proposals preserve breadth but re
arXiv:2608.19227v1 Announce Type: cross Abstract: Market microstructure simulation aims to model how liquidity, prices, and order flow evolve in electronic financial markets. Since market data reveal
arXiv:2608.19635v1 Announce Type: new Abstract: Accurate and stable torque rendering is essential for safe and perceptive human--machine interaction. Magnetorheological fluid (MRF)-based actuators off
arXiv:2608.19901v1 Announce Type: cross Abstract: Agent Skills extend LLM agents with reusable instruction packages that may also include scripts, resources, and service configuration. This creates a
arXiv:2510.17529v3 Announce Type: replace-cross Abstract: Active Surveillance (AS) is a treatment option for managing low and intermediate-risk prostate cancer (PCa), aiming to avoid overtreatment whi
arXiv:2608.20011v1 Announce Type: new Abstract: Preference optimization is a standard alignment method for generative models, yet extending it to continuous-time dynamics remains non-trivial. In flow
arXiv:2608.19278v1 Announce Type: cross Abstract: The most capable general-purpose AI (GPAI) models are mostly built in two jurisdictions, the United States and China, but the risks they carry land gl
arXiv:2602.02710v2 Announce Type: replace Abstract: Reinforcement learning (RL) is the method of choice for training models in setups where the objective function can only be evaluated by sampling fro
arXiv:2608.19475v1 Announce Type: cross Abstract: This work introduces a formal semantic-block model for specifications and an execution-judged benchmark for evaluating specification quality independe
arXiv:2608.19338v1 Announce Type: cross Abstract: Mechanistic interpretability seeks quantities that models do not expose directly: represented states, component effects, interactions, and responses t
arXiv:2608.20202v1 Announce Type: new Abstract: Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions. However, existing
arXiv:2509.23689v2 Announce Type: replace Abstract: Model Merging (MM) has proven to be an effective alternative to multi-task learning, where several fine-tuned models are merged, without access to t
arXiv:2608.19419v1 Announce Type: cross Abstract: Microlensing can reveal populations of faint compact objects that are otherwise difficult to detect. Depending on their design, all-sky surveys have t
arXiv:2608.20314v1 Announce Type: new Abstract: Mid-training is increasingly recognized as a critical stage for shaping the capabilities of large language models. Recent work has shown that targeted m
arXiv:2608.19955v1 Announce Type: new Abstract: Enabling robots to walk on yielding terrain is vital for applications ranging from disaster response to planetary exploration. While bipedal robots hold
arXiv:2608.19803v1 Announce Type: cross Abstract: Credit assignment is challenging in long-horizon agentic reinforcement learning, where supervision often comes only from final rewards. Existing metho
arXiv:2501.14728v2 Announce Type: replace-cross Abstract: While generative artificial intelligence (GenAI) models have achieved significant success, their misuse for generating deceptive content raise
arXiv:2608.19621v1 Announce Type: new Abstract: Large language models (LLMs) offer a scalable approach to social simulation, but their credibility depends on how agents are constructed. Existing metho
arXiv:2608.19580v1 Announce Type: new Abstract: Vessel trajectory prediction is critical for maritime safety and accident prevention. While most existing trajectory prediction models rely on Automatic
arXiv:2512.06754v2 Announce Type: replace Abstract: Continuum manipulators offer intrinsic dexterity and safe geometric compliance for navigation within confined and obstacle-rich environments. Howeve
arXiv:2608.19788v1 Announce Type: cross Abstract: Trustworthy multimodal fusion in clinical settings requires handling incomplete and heterogeneous modality subsets across institutions, where privacy
arXiv:2608.20129v1 Announce Type: cross Abstract: Autonomous vehicles require robust perception and decision-making capabilities to operate in diverse and unseen scenarios. While reinforcement learnin
arXiv:2608.20187v1 Announce Type: cross Abstract: Practitioners inferring causality from observational data usually rely on a single method and treat its output as causal truth. Recent tools select an
arXiv:1905.11395v2 Announce Type: replace Abstract: Graph convolution network based approaches have been recently used to model region-wise relationships in region-level prediction problems in urban c
arXiv:2608.19914v1 Announce Type: new Abstract: Network topology inference from graph signals is central to graph signal processing with applications in neuroscience, sensor, and social networks. In p
arXiv:2608.19280v1 Announce Type: cross Abstract: The high photon flux at synchrotron beamlines allows for the measurement of fast dynamical processes. However, beamline radiation-safety protocols pro
arXiv:2608.19537v1 Announce Type: new Abstract: This paper presents a guide path-free multimodal trajectory planning framework for autonomous surface vehicles operating in dynamic environments. The pr
arXiv:2608.19666v1 Announce Type: new Abstract: Deep learning-based whole-body PET-CT lesion segmentation can support cancer staging, treatment planning, and response assessment, but generalization is
arXiv:2608.19957v1 Announce Type: new Abstract: Natural language code retrieval is a rapidly evolving task in computer science. However, the 1C:Enterprise ecosystem combines Russian syntax with highly
arXiv:2608.19212v1 Announce Type: new Abstract: Out-of-context (OOC) misinformation pairs authentic images with misleading captions to construct false narratives without image manipulation, making det