Knowledge catalogue
arXiv:2604.11615v1 Announce Type: cross Abstract: Matrix extensions have emerged as an essential feature in modern CPUs to address the surging demands of AI workloads. However, existing designs often
arXiv:2511.16428v3 Announce Type: replace Abstract: Self-supervised surround-view depth estimation enables dense, low-cost 3D perception with a 360{eg} field of view from multiple minimally overlappin
arXiv:2604.09728v1 Announce Type: new Abstract: Infrared thermography (IRT) is a widely used non-destructive testing technique for detecting structural features such as subsurface defects. However, mo
arXiv:2604.10514v1 Announce Type: cross Abstract: Surgical phase segmentation is central to computer-assisted surgery, yet robust models remain difficult to develop when labeled surgical videos are sc
arXiv:2507.15640v2 Announce Type: replace-cross Abstract: Continual pre-training on small-scale task-specific data is an effective method for improving large language models in new target fields, yet
arXiv:2502.02189v4 Announce Type: replace Abstract: Novel materials drive advancements in fields ranging from energy storage to electronics, with crystal structure characterization forming a crucial y
arXiv:2505.10319v2 Announce Type: replace-cross Abstract: We present a novel perspective on the NFA canonization problem, which introduces intermediate minimization steps to reduce the exploration spa
arXiv:2512.19049v2 Announce Type: replace Abstract: Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control.
arXiv:2508.08574v3 Announce Type: replace Abstract: We introduce DeepFleet, a suite of foundation models designed to support coordination and planning for large-scale mobile robot fleets. These models
arXiv:2504.05902v2 Announce Type: replace-cross Abstract: Backdoor attacks pose a serious threat to deep neural networks (DNNs), allowing adversaries to implant triggers for hidden behaviors in infere
arXiv:2604.09596v1 Announce Type: new Abstract: Dermatologic diseases impose a large and growing global burden, affecting billions and substantially reducing quality of life. While modern therapies ca
arXiv:2604.10283v1 Announce Type: cross Abstract: Cross-modal retrieval between audio recordings and symbolic music representations (MIDI) remains challenging because continuous waveforms and discrete
arXiv:2510.09389v2 Announce Type: replace-cross Abstract: Deep sequence models, ranging from Transformers and State Space Models (SSMs) to more recent approaches such as gated linear RNNs, fundamental
arXiv:2604.09644v1 Announce Type: cross Abstract: Corporate AI-washing-the strategic misrepresentation of AI capabilities via exaggerated or fabricated cross-channel disclosures-has emerged as a syste
arXiv:2604.10717v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems augment large language models with external knowledge, yet introduce a critical security vulnerability: R
arXiv:2604.10170v1 Announce Type: cross Abstract: The growing complexity of visuomotor policies poses significant challenges for deployment with heterogeneous robotic hardware constraints. However, mo
arXiv:2604.11258v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) in healthcare suffer from severe confirmation bias, often hallucinating visual details to support initial, pote
arXiv:2511.03015v2 Announce Type: replace Abstract: Generating graph-structured data is crucial in applications such as molecular generation, knowledge graphs, and network analysis. However, their dis
arXiv:2601.14346v2 Announce Type: replace-cross Abstract: Accurate prediction of drug response in precision medicine requires models that capture how specific chemical substructures interact with cell
arXiv:2604.11088v1 Announce Type: new Abstract: Developers increasingly guide AI coding agents through natural language instruction files (e.g., CLAUDE.md, .cursorrules), yet no controlled study has m
arXiv:2604.10690v1 Announce Type: new Abstract: Foundation models have shown remarkable performance across diverse tasks, yet their ability to construct internal spatial world models for reasoning and
arXiv:2604.11322v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive capabilities in utilizing external tools. In practice, however, LLMs are often exposed to to
arXiv:2604.09853v1 Announce Type: new Abstract: Understanding human motion processing is essential for building reliable, human-centered computer vision systems. Although deep neural networks (DNNs) a
arXiv:2604.09666v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) and its graph-based extensions (GraphRAG) are effective paradigms for improving large language model (LLM) reason
arXiv:2601.03926v2 Announce Type: replace Abstract: The deployment of Large Vision-Language Models (LVLMs) for real-world document question answering is often constrained by dynamic, user-defined poli
arXiv:2604.10077v1 Announce Type: new Abstract: In Document Understanding, the challenge of reconstructing damaged, occluded, or incomplete text remains a critical yet unexplored problem. Subsequent d
arXiv:2604.07389v2 Announce Type: replace Abstract: Crime pattern analysis is critical for law enforcement and predictive policing, yet the surge in criminal activities from rapid urbanization creates
arXiv:2604.11703v1 Announce Type: new Abstract: People experiencing homelessness (PEH) face substantial barriers to accessing timely, accurate information about community services. DreamKG addresses t
arXiv:2603.18806v2 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) introduce a new paradigm for language generation, which in turn presents new challenges for aligning them wi
arXiv:2604.10112v1 Announce Type: new Abstract: Remote sensing infrared image super-resolution aims to recover sharper thermal observations from low-resolution inputs while preserving target contours,
arXiv:2604.09599v1 Announce Type: cross Abstract: High-performance computing systems are complex machines whose behaviour is governed by the correct functioning of its many subsystems. Among these, th
arXiv:2604.11423v1 Announce Type: new Abstract: For the past decades medical robotic solutions were mostly based on the concept of tele-manipulation. While their design was extremely intelligent, allo
arXiv:2604.11094v1 Announce Type: cross Abstract: Contemporary microservice systems continue to grow in scale and complexity, leading to increasingly frequent and costly failures. While recent LLM-bas
arXiv:2604.11400v1 Announce Type: cross Abstract: High-speed autonomous racing presents extreme perception challenges, including large relative velocities and substantial domain shifts from convention
arXiv:2604.10567v1 Announce Type: cross Abstract: Diffusion-based language models (dLLMs) have emerged as a promising alternative to autoregressive language models, offering the potential for parallel
arXiv:2510.06965v2 Announce Type: replace-cross Abstract: Math word problems (MWPs) are critical K-12 educational tools, and customizing them to students' interests and ability levels can enhance lear
arXiv:2511.18957v2 Announce Type: replace Abstract: Video virtual try-on technology provides a cost-effective solution for creating marketing videos in fashion e-commerce. However, its practical adopt
arXiv:2604.10660v1 Announce Type: cross Abstract: Recent research has devoted considerable effort to verifying the intermediate reasoning steps of chain-of-thought (CoT) trajectories using process rew
arXiv:2604.11096v1 Announce Type: cross Abstract: Currently, large language models (LLMs) predominantly focus on the text modality. To enable more natural human-AI interaction, speech LLMs are emergin
arXiv:2604.11038v1 Announce Type: new Abstract: We present EgoFun3D, a coordinated task formulation, dataset, and benchmark for modeling interactive 3D objects from egocentric videos. Interactive obje
arXiv:2604.11043v1 Announce Type: new Abstract: Unified multimodal embedding spaces underpin practical applications such as cross-modal retrieval and zero-shot recognition. In many real deployments, h
arXiv:2604.10437v1 Announce Type: new Abstract: Vision--language models (VLMs) for radiology report generation (RRG) can produce long-form chest CT reports from volumetric scans and show strong potent
arXiv:2512.11811v3 Announce Type: replace-cross Abstract: Crowdsourced social media imagery provides real-time visual evidence of urban flooding but often lacks reliable geographic metadata for emerge
arXiv:2601.02956v3 Announce Type: replace Abstract: Multilingual Retrieval-Augmented Generation (mRAG) systems often exhibit a perceived preference for high-resource languages, particularly English, r
arXiv:2604.10911v1 Announce Type: new Abstract: Medium-to-long-horizon stock allocation presents significant challenges due toveak predictive structures, non-stadonary market regimes, and the degradat
arXiv:2604.09622v1 Announce Type: cross Abstract: The rapid adoption of generative artificial intelligence (AI) in educational assessment has created new opportunities for scalable item creation, pers
arXiv:2604.09799v1 Announce Type: cross Abstract: Human activity recognition (HAR) has become a key component of intelligent systems for healthcare monitoring, assistive living, smart environments, an
arXiv:2604.11209v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success across a wide range of applications especially when augmented by external knowledge thro
arXiv:2604.09868v1 Announce Type: cross Abstract: Industrial standards and normative documents exhibit intricate hierarchical structures, domain-specific lexicons, and extensive cross-referential depe
arXiv:2604.05320v2 Announce Type: replace Abstract: Mobile manipulators are increasingly deployed in human-centered environments to perform tasks. While completing such tasks, they should also be able
arXiv:2604.09689v1 Announce Type: cross Abstract: Machine learning progress has historically prioritized model-centric innovations, yet achievable performance is frequently capped by the intrinsic com
arXiv:2604.09656v1 Announce Type: cross Abstract: Despite there now being more than 1,000 FDA-authorised AI medical devices, formal equity assessments -- whether model performance is uniform across pa
arXiv:2604.10275v1 Announce Type: new Abstract: Real-time image denoising is essential for modern mobile photography but remains challenging due to the strict latency and power constraints of edge dev
arXiv:2604.11028v1 Announce Type: cross Abstract: As embodied robots move toward fleet-scale operation, multi-robot coordination is becoming a central systems challenge. Existing approaches often trea
arXiv:2408.07587v4 Announce Type: replace Abstract: Federated Learning (FL) enables the collaborative training of machine learning models without requiring centralized collection of user data. To comp
arXiv:2604.10391v1 Announce Type: cross Abstract: Vision foundation models (VFMs) and Bird's Eye View (BEV) representation have advanced visual perception substantially, yet their internal spatial rep
arXiv:2602.22822v2 Announce Type: replace Abstract: The identification and property prediction of chemical molecules is of central importance in the advancement of drug discovery and material science,
arXiv:2512.20642v2 Announce Type: replace-cross Abstract: Particle image velocimetry (PIV) and related optical-flow methods are widely used to quantify fluid motion, but their development and evaluati
arXiv:2604.11556v1 Announce Type: cross Abstract: LLM-assisted software development has become increasingly prevalent, and can generate large-scale systems, such as compilers. It becomes crucial to st
arXiv:2603.22911v2 Announce Type: replace-cross Abstract: Due to the great saving of computation and memory overhead, token compression has become a research hot-spot for MLLMs and achieved remarkable