Knowledge catalogue
arXiv:2604.26453v1 Announce Type: new Abstract: Audio-visual deepfakes have reached a level of realism that makes perceptual detection unreliable, threatening media integrity and biometric security. W
arXiv:2604.25977v1 Announce Type: cross Abstract: Organizations routinely make strategic budget allocations under operational constraints, but often lack a principled way to assess whether realized al
arXiv:2509.26184v5 Announce Type: replace-cross Abstract: Generation of citation-backed reports is a primary use case for retrieval-augmented generation (RAG) systems. While open-source evaluation too
arXiv:2604.26507v1 Announce Type: new Abstract: Background & Objectives: In the last decade, Machine learning research has grown rapidly, but large models are reaching their soft limits demonstrating
arXiv:2601.13969v2 Announce Type: replace Abstract: Retrieving evidence for language model queries from knowledge graphs requires balancing broad search across the graph with multi-hop traversal to fo
arXiv:2604.26382v1 Announce Type: cross Abstract: Most enterprise document AI today is a pipeline. Parse, index, retrieve, generate. Each of those stages has been studied to death on its own -- what's
arXiv:2506.21444v4 Announce Type: replace Abstract: Atypical mitosis marks a deviation in the cell division process that has been shown be an independent prognostic marker for tumor malignancy. Howeve
arXiv:2604.26310v1 Announce Type: new Abstract: Fine-grained emotion classification, which identifies specific emotional states such as happiness, anger, sadness, and fear, remains a challenging task
arXiv:2604.26577v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly considered for deployment as the control component of robotic health attendants, yet their safety in this
arXiv:2604.14858v2 Announce Type: replace Abstract: As agent systems move into increasingly diverse execution settings, trajectory-level safety evaluation and diagnosis require benchmarks that evolve
arXiv:2604.26365v1 Announce Type: new Abstract: To address the high sampling cost of Diffusion Transformers (DiTs), feature caching offers a training-free acceleration method. However, existing method
arXiv:2604.26148v1 Announce Type: cross Abstract: AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality
arXiv:2604.26250v1 Announce Type: new Abstract: While Vision-Language Models (VLMs) have achieved state-of-the-art performance in general visual tasks, their perceptual robustness remains remarkably b
arXiv:2508.04325v2 Announce Type: replace-cross Abstract: Large language models (LLMs) show significant potential in healthcare, prompting numerous benchmarks to evaluate their capabilities. However,
arXiv:2604.26910v1 Announce Type: new Abstract: This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulate
arXiv:2604.26805v1 Announce Type: new Abstract: Operating and maintaining (O&M) large-scale online engine systems (search, recommendation, advertising) demands substantial human effort for release mon
arXiv:2604.26048v1 Announce Type: new Abstract: This paper presents a principled and scalable framework for systematically generating complex Question Answering (QA) data. In the core of this framewor
arXiv:2604.26209v1 Announce Type: cross Abstract: Some text generation tasks, such as Attribute Value Extraction (AVE), require decoding multiple independent sequences from the same document context.
arXiv:2604.26868v1 Announce Type: new Abstract: Existing 3D anomaly detection methods are built on a rigid prior: normal geometry is pose-invariant and can be canonicalized through registration or ali
arXiv:2604.26820v1 Announce Type: new Abstract: Detectors often suffer from degraded performance, primarily due to the distributional gap between the source and target domains. This issue is especiall
arXiv:2604.02021v2 Announce Type: replace Abstract: Voxel-grid reinforcement learning is widely adopted for path planning in redundant manipulators due to its simplicity and reproducibility. However,
arXiv:2601.19216v2 Announce Type: replace-cross Abstract: The emerging applications of next-generation wireless networks demand high-fidelity environmental intelligence. 3D radio maps bridge physical
arXiv:2604.26169v1 Announce Type: new Abstract: Treatment allocation under budget constraints is a central challenge in digital advertising: advertisers must decide which users to show ads to while sp
arXiv:2604.26176v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answerin
arXiv:2604.26241v1 Announce Type: new Abstract: Passive RFID tags offer a cost-effective and scalable solution for tracking numerous deployed assets. However, in forested environments, signal attenuat
arXiv:2604.26919v1 Announce Type: cross Abstract: Can Neural Assemblies -- groups of neurons that fire together and strengthen through co-activation -- learn the direction of causal influence between
arXiv:2604.26145v1 Announce Type: cross Abstract: AI-powered language learning tools increasingly provide instant, personalised feedback to millions of learners worldwide. However, this feedback can f
arXiv:2601.13606v2 Announce Type: replace Abstract: Chart reasoning is a critical capability for Vision Language Models (VLMs). However, the development of open-source models is severely hindered by t
arXiv:2604.26301v1 Announce Type: new Abstract: Graph Contrastive Learning (GCL) has emerged as a prominent framework for unsupervised graph representation learning. However, relying on augmentation d
arXiv:2604.26288v1 Announce Type: cross Abstract: Chest X-ray interpretation is one of the most frequently performed diagnostic tasks in medicine and a primary target for AI development, yet current v
arXiv:2412.13682v5 Announce Type: replace Abstract: Travel planning stands out among real-world applications of Language Agents because it couples significant practical demand with a rigorous constrai
arXiv:2604.26664v1 Announce Type: cross Abstract: Traditional iterative reconstruction methods are accurate but computationally expensive, limiting their use in high-throughput and real-time ptychogra
arXiv:2604.26923v1 Announce Type: cross Abstract: LLMs have achieved strong results on both function-level code synthesis and repository-level code modification, yet a capability that falls between th
arXiv:2604.26312v1 Announce Type: new Abstract: Public opinion towards the Free Nutritious Meal Program (MBG) on YouTube social media reflects diverse community responses. This study applies the Long
arXiv:2604.26904v1 Announce Type: cross Abstract: Claw-style environments support multi-step workflows over local files, tools, and persistent workspace states. However, scalable development around th
arXiv:2604.26363v1 Announce Type: new Abstract: Federated domain generalization for person re-identification (FedDG-ReID) aims to collaboratively train a pedestrian retrieval model across multiple dec
arXiv:2604.26172v1 Announce Type: cross Abstract: We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approa
arXiv:2603.02854v2 Announce Type: replace-cross Abstract: Existing language-conditioned navigation systems typically rely on modular pipelines or trajectory generators, but the latter use each scene--
arXiv:2604.25928v1 Announce Type: new Abstract: Professional domain knowledge underpins human civilization, serving as both the basis for industry entry and the core of complex decision-making and pro
arXiv:2604.26920v1 Announce Type: new Abstract: The task of capturing and rendering 3D dynamic scenes from 2D images has become increasingly popular in recent years. However, most conventional cameras
arXiv:2405.13729v3 Announce Type: replace-cross Abstract: In this paper, we study an under-explored but important factor of diffusion generative models, i.e., the combinatorial complexity. Data sample
arXiv:2503.02332v3 Announce Type: replace-cross Abstract: Accurate segmentation of 3D vascular structures is essential for various medical imaging applications. The dispersed nature of vascular struct
arXiv:2604.26229v1 Announce Type: new Abstract: This study compares machine learning and deep learning approaches for cyberbullying detection in Indonesian-language Instagram comments. Using a balance
arXiv:2504.15458v4 Announce Type: replace Abstract: We extract Compton form factors (CFFs) from deeply virtual Compton scattering measurements at the Thomas Jefferson National Accelerator Facility (JL
arXiv:2604.25922v1 Announce Type: cross Abstract: We present DenialBench, a systematic benchmark measuring consciousness denial behaviors across 115 large language models from 25+ providers. Using a t
arXiv:2512.08982v2 Announce Type: replace-cross Abstract: Retinex-based low-light image enhancement benefits from separating reflectance and illumination, yet recent generative approaches often rely o
arXiv:2511.22958v2 Announce Type: replace Abstract: Deep learning has revolutionized solar image analysis, yet most approaches train task-specific encoders from scratch or rely on natural-image pretra
arXiv:2603.03239v2 Announce Type: replace Abstract: Earth observation applications increasingly rely on data from multiple sensors, including optical, radar, elevation, and land-cover. Relationships b
arXiv:2604.26378v1 Announce Type: new Abstract: Post-training quantization (PTQ) has become an important technique for reducing the inference cost of Large Language Models (LLMs). While recent mixed-p
arXiv:2604.26024v1 Announce Type: cross Abstract: Class-level evaluation can conceal substantial performance disparities across subconcepts within the same class, causing models that perform well on a
arXiv:2506.13116v2 Announce Type: replace-cross Abstract: Crime hotspot prediction is critical for ensuring urban safety and effective law enforcement, it remains challenging due to complex spatial de
arXiv:2604.26478v1 Announce Type: new Abstract: Hyperspectral imaging (HSI) semantic segmentation typically relies on in-domain training, but limited data availability often restricts model performanc
arXiv:2604.26494v1 Announce Type: cross Abstract: Generative AI tools are widely used by youth and have introduced new privacy and safety challenges. While prior research has explored youth's safety i
arXiv:2604.26707v1 Announce Type: new Abstract: Recent advances in self-evolution video understanding frameworks have demonstrated the potential of autonomous learning without human annotations. Howev
arXiv:2505.13518v2 Announce Type: replace-cross Abstract: Imbalanced datasets, where one class significantly outnumbers others, remain a persistent challenge in machine learning, often biasing predict
arXiv:2401.02458v3 Announce Type: replace-cross Abstract: The advent of foundation models (FMs) as an emerging suite of AI techniques has struck a wave of opportunities in computational healthcare. Th
arXiv:2505.18441v2 Announce Type: replace Abstract: Dictionary learning has recently emerged as a promising approach for mechanistic interpretability of large transformer models. Disentangling high-di
arXiv:2604.03905v2 Announce Type: replace-cross Abstract: Heterogeneity is a defining feature of deployed multi-robot teams: platforms often differ in sensing modalities, ranges, fields of view, and f
arXiv:2506.20876v4 Announce Type: replace Abstract: Technological progress has led to concrete advancements in tasks that were regarded as challenging, such as automatic fact-checking. Interest in ado
arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial