Knowledge catalogue
arXiv:2606.30220v1 Announce Type: new Abstract: High benchmark accuracy does not guarantee genuine use of visual evidence. We study this problem in traffic accident Video Question Answering (VideoQA),
arXiv:2606.30191v1 Announce Type: new Abstract: How does an agent that can tell self from world come to be durably shaped by that distinction? Recent work shows that a predictive system can detect its
arXiv:2606.30059v1 Announce Type: new Abstract: Industry-scale video and live-streaming moderation imposes requirements that are difficult to satisfy with generic pretrained public models or external
arXiv:2606.29093v1 Announce Type: new Abstract: A deep defogging pipeline pretrained on controlled laboratory fog and fine-tuned with domain-randomized synthetic fog applied to clear outdoor scenes ge
arXiv:2601.08341v2 Announce Type: replace Abstract: Single Image Super-Resolution (SISR) is a fundamental computer vision task that aims to reconstruct a high-resolution (HR) image from a low-resoluti
arXiv:2606.29461v1 Announce Type: new Abstract: We propose a self-supervised pretraining framework for learning sub-surface scattering (SSS) light transport representations from minimal input. Our met
arXiv:2606.28353v1 Announce Type: cross Abstract: Linking FDA-approved medical devices to their underlying United States Patent and Trademark Office (USPTO) patents enables critical applications such
arXiv:2606.29073v1 Announce Type: cross Abstract: Model Context Protocol (MCP)-style ecosystems give language-model applications a practical connection layer for tools, resources, prompts, and transpo
arXiv:2606.29726v1 Announce Type: cross Abstract: With the rapid development of Artificial Intelligence Generated Content (AIGC) platforms, users increasingly show cross-platform usage intentions. Exi
arXiv:2601.07988v2 Announce Type: replace-cross Abstract: While NLP typically treats documents as independent and unordered samples, in longitudinal studies, this assumption rarely holds: documents ar
arXiv:2606.29793v1 Announce Type: new Abstract: Demand for personalized financial advising is growing, but consistent advisor expertise is difficult to obtain, scale, and encode in LLM systems. Simple
arXiv:2606.30367v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining sp
arXiv:2606.29646v1 Announce Type: cross Abstract: Sleeper agents are the canonical model organism of deception: models trained to behave normally but to emit an unsafe behaviour on a specific trigger.
arXiv:2511.13216v2 Announce Type: replace Abstract: Deployment of legged robots for navigating challenging terrains (e.g., stairs, slopes, and unstructured environments) has gained increasing preferen
arXiv:2606.29535v1 Announce Type: new Abstract: Online product listings for garments often include an overview photo and a close-up to show garment details. However, each photo focuses on either field
arXiv:2403.15212v3 Announce Type: replace Abstract: Skeleton-based action recognition (SAR) in videos is an important but challenging task in computer vision. The recent state-of-the-art (SOTA) models
arXiv:2602.11395v2 Announce Type: replace-cross Abstract: Steering diffusion models toward conditions unseen during training typically requires either retraining with conditional inputs or per-step gr
arXiv:2606.29256v1 Announce Type: cross Abstract: In recent years, models based on the Transformer architecture have seen widespread applications and have become one of the core tools in the field of
arXiv:2406.13944v2 Announce Type: replace-cross Abstract: This paper establishes the generalization error of pooled min-ell_2-norm interpolation in transfer learning, where data from diverse distribut
arXiv:2606.28354v1 Announce Type: new Abstract: The classic paradigm of language identification in the limit models learning as a game between an adversary, who reveals strings from an unknown target
arXiv:2603.19235v2 Announce Type: replace Abstract: While Multimodal Large Language Models demonstrate impressive semantic capabilities, they often suffer from spatial blindness, struggling with fine-
arXiv:2409.11972v4 Announce Type: replace-cross Abstract: Enabling robots to autonomously discover high-level spatial concepts (e.g., rooms and walls) from primitive geometric observations (e.g., plan
arXiv:2606.28510v1 Announce Type: cross Abstract: Across social and online platforms, people are increasingly exposed to AI-generated images. As a consequence, the task of distinguishing AI-generated
arXiv:2407.02351v3 Announce Type: replace Abstract: The rapid spread of false and misleading information on online platforms poses a growing societal challenge, overwhelming the capacity of manual fac
arXiv:2606.28769v1 Announce Type: new Abstract: Emotional body motion expressions are an essential element of non-verbal communication. Effectively conveying these expressions through technology is of
arXiv:2506.18295v2 Announce Type: replace-cross Abstract: Neural ray tracing (RT) has emerged as a promising paradigm for channel modeling by integrating physical propagation principles with neural ne
arXiv:2606.30003v1 Announce Type: new Abstract: Precisely manipulating objects in a single photograph (translation, rotation, scaling) while obeying 3D physical constraints remains unsolved for diffus
arXiv:2606.28371v1 Announce Type: new Abstract: The problem of localization on a large-scale satellite image given a frame of query ground view point clouds remains challenging. Existing LiDAR-to-imag
arXiv:2606.29584v1 Announce Type: cross Abstract: Cl(3,0) interatomic potentials, despite their algebraic elegance, predict force magnitudes accurately but force directions poorly. Across ten rMD17 mo
arXiv:2606.28572v1 Announce Type: cross Abstract: The axiom of choice has divided the foundations of mathematics for over a century, but the distinction between classical and constructive proofs has r
arXiv:2510.01878v2 Announce Type: replace Abstract: Low-rank gradient optimization for large language models is currently divided into two categories: structured methods that rigorously identify subsp
arXiv:2606.29161v1 Announce Type: new Abstract: Predicting tandem mass spectra (MS/MS) from molecular structures represents a central task in analytical chemistry with direct relevance to clinical met
arXiv:2606.29773v1 Announce Type: new Abstract: Graphs are widely used to model relational systems, with applications in domains such as social networks, finance, and biomedicine. Graph neural network
arXiv:2606.30599v1 Announce Type: new Abstract: Existing instruction-based video editing datasets commonly focus on single-task appearance editing, failing to meet the complex creative demands of real
arXiv:2606.29889v1 Announce Type: new Abstract: Timely intensive care dictates survival, yet emergency infrastructure remains unevenly distributed across Sri Lanka. While pre-hospital services have ex
arXiv:2505.20928v2 Announce Type: replace Abstract: Manually refining radiological segmentation masks is highly resource-intensive. To determine when this expert commitment is truly justified for the
arXiv:2606.22528v2 Announce Type: replace Abstract: Modern LLM agents increasingly rely on context compaction, summarization, or eviction to keep long-running sessions within a token budget. We show t
arXiv:2606.29148v1 Announce Type: cross Abstract: Developing controllers capable of completing a wide range of tasks in a natural and life-like manner is a key challenge in enabling practical applicat
arXiv:2606.28514v1 Announce Type: new Abstract: Multimodal models are increasingly deployed to solve tasks collaboratively with humans or other artificial agents. Existing benchmarks show that these m
arXiv:2606.28394v1 Announce Type: new Abstract: The physical anastylosis of collapsed architectural monuments -- the meticulous reassembly of fallen stone elements into their original structural confi
arXiv:2606.30497v1 Announce Type: cross Abstract: We present a comparative study of CUDA optimization strategies applied to forward and backward propagation in a shallow neural network. Three stacked
arXiv:2511.00217v2 Announce Type: replace-cross Abstract: We introduce Gradient Boosted Mixed Models (GBMixed), a framework which extends boosting to clustered data by jointly modeling the mean and va
arXiv:2606.29326v1 Announce Type: cross Abstract: Gradient boosting in the form of decision tree ensembles has successfully been applied to a variety of problems using simple objective functions based
arXiv:2304.11171v5 Announce Type: replace-cross Abstract: To overcome the limitations of point-based inputs, overly fine computation and limited adaptability in existing artificial intelligence method
arXiv:2606.29782v1 Announce Type: new Abstract: Merging multiple 3D Gaussian Splatting (3DGS) scenes into a single unified Gaussian representation is essential for large-scale 3D mapping and long-term
arXiv:2501.17559v2 Announce Type: replace Abstract: After the achievement of solving two-player zero-sum games, more AI researchers focus on solving multiplayer games. Urban Network Security Games (ex
arXiv:2606.30474v1 Announce Type: new Abstract: Non-prehensile manipulation is often used as a preparatory step for robotic grasping, yet existing approaches typically require a predefined target obje
arXiv:2606.30117v1 Announce Type: cross Abstract: We investigate the reconstruction of holographic duals for strongly coupled quantum field theories in regimes characterized by large hierarchies and t
arXiv:2606.28334v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) and social media data have led to growing optimism about the ability to detect suicide risk at scale.
arXiv:2606.28828v1 Announce Type: new Abstract: Learning a 4D scene representation from a single monocular video that supports dynamic novel-view synthesis while maintaining faithful geometry over tim
arXiv:2606.30247v1 Announce Type: new Abstract: Knowledge graphs can guide large language models (LLMs) reasoning, but the graph seen by a system is usually a retrieved, linked, temporally scoped, and
arXiv:2603.22876v2 Announce Type: replace-cross Abstract: Learning a generalist control policy for robotic manipulation typically relies on large-scale datasets. Given the high cost of real-world data
arXiv:2606.30632v1 Announce Type: cross Abstract: Can the robot use a plate to cut a cake if no knife is available? Tool use greatly expands robot capabilities, but to use tools creatively beyond thei
arXiv:2606.29705v1 Announce Type: new Abstract: Data, as the fundamental substrate of modern intelligence, has greatly driven the development of current foundation models. Naturally, researchers aim t
arXiv:2507.00719v3 Announce Type: replace-cross Abstract: Typically, numerical simulations of Earth systems are coarse, and Earth observations are sparse and gappy. We apply four generative diffusion
arXiv:2606.29915v1 Announce Type: new Abstract: Vision-Language Models (VLMs) often achieve high performance on benchmarks while remaining 'black boxes', yet they remain prone to hallucination or rely
arXiv:2511.05879v5 Announce Type: replace-cross Abstract: Hydrogen crossover is a critical safety and efficiency constraint in high-pressure polymer electrolyte membrane water electrolysis (PEMWE), bu
arXiv:2606.28831v1 Announce Type: cross Abstract: Long-context LLM inference faces a fundamental conflict: head-adaptive compression algorithms (e.g., Top-p nucleus sampling) offer superior accuracy b
arXiv:2606.29518v1 Announce Type: cross Abstract: With the widespread adoption of AI in various IoT scenarios such as smart sensing and processing, AI chips have become a common component at the edge.
arXiv:2606.30516v1 Announce Type: new Abstract: Deploying large convolutional neural networks (CNNs) on resource-constrained devices is challenging due to their high computational cost. While dynamic