Knowledge catalogue
arXiv:2608.04260v1 Announce Type: new Abstract: Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require r
arXiv:2502.15952v3 Announce Type: replace Abstract: Recent works exploring the training dynamics of homogeneous neural network weights under gradient flow with small initialization have established th
arXiv:2608.04955v1 Announce Type: new Abstract: Multi-stage boundary representation (B-Rep) generation leverages intermediate wireframes to synthesize CAD models. However, geometric and topological ri
arXiv:2608.04230v1 Announce Type: cross Abstract: Deep learning models for scientific spatio-temporal downscaling often minimize reconstruction error while failing to preserve physically meaningful mu
arXiv:2608.04606v1 Announce Type: new Abstract: Understanding complex surgical scenes requires recognizing multiple interdependent entities, such as instruments, actions, and targets, while maintainin
arXiv:2608.04154v1 Announce Type: cross Abstract: Mapping paddy rice from very-high-resolution imagery in mountainous and hilly regions is difficult because terrain alters optical appearance and incre
arXiv:2608.04174v1 Announce Type: new Abstract: Time series data are ubiquitous in practical applications, where classification (TSC) and extrinsic regression (TSER) have emerged as essential tasks fo
arXiv:2508.04780v2 Announce Type: replace-cross Abstract: The increasing frequency of extreme weather events, such as hurricanes, highlights the urgent need for efficient and equitable power system re
arXiv:2608.04173v1 Announce Type: new Abstract: Deep neural networks (DNNs) deployed on resource-constrained neuromorphic hardware face three concurrent challenges: the need for model compression thro
arXiv:2608.04055v1 Announce Type: cross Abstract: The minimum change principle provides an information-theoretic characterization of the Bayes reversal channel in classical probability theory and has
arXiv:2608.04935v1 Announce Type: new Abstract: Recent work has shown that a simple linear probe on frozen representations from modern vision foundation models (VFMs) can achieve state-of-the-art AIGI
arXiv:2608.04882v1 Announce Type: new Abstract: We introduce a variational approach to a finite-temperature continuous-spin perceptron trained on a Gaussian mixture. The model allows for a broad class
arXiv:2608.04623v1 Announce Type: new Abstract: Zero-shot Skeleton Action Recognition (ZSAR) remains ambiguous when unseen actions share similar skeleton joint dynamics but differ in objects or scene
arXiv:2608.04591v1 Announce Type: cross Abstract: Large language models (LLMs) are often asked whether something is absent from a record, list, or retrieved context. Yet non-observation licenses a neg
arXiv:2608.04448v1 Announce Type: cross Abstract: Diffusion transformers deliver strong image generation, but their training cost grows superlinearly with resolution. Recent work justifies training or
arXiv:2510.20351v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly exposed to data contamination, i.e., performance gains driven by prior exposure of test datasets
arXiv:2608.04052v1 Announce Type: cross Abstract: Backdoor attacks in multimodal contrastive learning (MCL) have garnered growing attention in recent years, as many downstream tasks critically depend
arXiv:2608.04021v1 Announce Type: new Abstract: Cloze-style probes that vary how often a target token appears implicitly assume that more copies of a target affect prediction the same way regardless o
arXiv:2608.04393v1 Announce Type: new Abstract: Scientific machine learning often relies on proxy targets computed from known domain factors when direct observations are limited. When those same facto
arXiv:2608.04642v1 Announce Type: new Abstract: Slice-wise 2D object detectors are increasingly applied to volumetric data due to their computational efficiency and scalability, yet they often yield f
arXiv:2608.03353v1 Announce Type: cross Abstract: For a Markov kernel T with an invariant probability measure pi, we give a self-contained proof of the Markov chain convergence theorem via a criterion
arXiv:2608.02835v1 Announce Type: new Abstract: Historical lenticular films, such as those created with the Kodacolor process, encode color information in a distinctive spatial format. This structure
arXiv:2608.02799v1 Announce Type: cross Abstract: Score-based diffusion models are typically formulated using continuous-time stochastic differential equations and measure-theoretic stochastic calculu
arXiv:2608.03444v1 Announce Type: cross Abstract: Sign language recognition (SLR) enhances communication between hearing and hearing-impaired individuals. Although deep learning (DL) has achieved prom
arXiv:2608.03617v1 Announce Type: new Abstract: The personal archive of Konstantin Tsiolkovsky (1857-1935) is held as fond 555 of the Archive of the Russian Academy of Sciences. The archive scanned th
arXiv:2311.17815v3 Announce Type: replace-cross Abstract: Given their increasing size and complexity, the need for efficient execution of deep neural networks has become increasingly pressing in the d
arXiv:2608.03620v1 Announce Type: cross Abstract: Activation patching and weight-space ablation both claim a component is causally responsible for a behavior, yet they act on different objects: one fo
arXiv:2608.03107v1 Announce Type: new Abstract: Laser line-scanning microscopy enables fast volumetric imaging but produces anisotropic lateral resolution. Orthogonal line scans provide complementary
arXiv:2608.03067v1 Announce Type: new Abstract: Changes in spontaneous speech provide an early signal of cognitive dysfunction in Alzheimer's disease (AD) that large language models (LLMs) can detect.
arXiv:2608.03677v1 Announce Type: new Abstract: Supportive continuum robots (SCRs) enhance the load-bearing capability of an operative continuum robot by mechanically coupling it with a supportive arm
arXiv:2608.03475v1 Announce Type: cross Abstract: Multimodal intent recognition combines linguistic, acoustic, and visual evidence, but individual modalities may be noisy, missing, semantically confli
arXiv:2412.08394v2 Announce Type: replace Abstract: Deep neural networks (DNNs) are vulnerable to adversarial samples crafted by adding imperceptible perturbations to clean data, potentially leading t
arXiv:2608.03742v1 Announce Type: cross Abstract: Sound effects play a crucial role in conveying actions, events, and environmental cues across digital applications, often requiring a high degree of v
arXiv:2608.03520v1 Announce Type: cross Abstract: AI systems are increasingly involved in decisions and actions that may later require investigation. When an AI related incident occurs, investigators
Ai2 is expanding its partnership with Hugging Face to give its growing portfolio of fully open models, datasets, benchmarks, and applications the storage, bandwidth, and integrations needed to reach m
arXiv:2608.03047v1 Announce Type: new Abstract: Generating natural-language coaching feedback on motor skills can accelerate learning, yet expert coaches are scarce and expensive. Existing reference-b
arXiv:2608.02901v1 Announce Type: cross Abstract: The key-value (KV) cache is the primary memory bottleneck in long-context LLM inference. Existing approaches attack it from opposite ends: eviction me
arXiv:2608.02703v1 Announce Type: new Abstract: Weight-only quantization substantially reduces the storage of large language model (LLM) transformer blocks, but practical backends often retain the fin
arXiv:2509.24457v1 Announce Type: cross Abstract: Objective speech-quality metrics are widely used to assess codec performance. However, for neural codecs, it is often unclear which metrics provide re
arXiv:2603.19087v2 Announce Type: replace Abstract: Creativity is the ability to come up with novel ideas, a capacity crucial for human development and flourishing. Are large language models (LLMs) cr
arXiv:2608.03711v1 Announce Type: cross Abstract: In human visual perception, uppercase lettering serves as a natural salience cue that captures attention within lowercase text. In this paper, we pres
arXiv:2608.03086v1 Announce Type: cross Abstract: Microwave ablation (MWA) is a promising minimally invasive treatment for liver tumors, but its therapeutic outcome strongly depends on patient-specifi
arXiv:2608.02907v1 Announce Type: new Abstract: Multimodal retrievers are essential for knowledge-based visual question answering, where they retrieve external evidence for image-question pairs. Howev
arXiv:2608.03531v1 Announce Type: new Abstract: Institutions increasingly rely on browser lockdown, webcam monitoring, and behavioral analytics to secure high-stakes digital assessments, yet these mec
arXiv:2608.03386v1 Announce Type: new Abstract: Contemporary deep learning methods generalize well even when they fit their training data perfectly, a phenomenon known as benign interpolation. This ph
arXiv:2608.02791v1 Announce Type: new Abstract: MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-pre
arXiv:2608.03038v1 Announce Type: new Abstract: Statistical reasoning is multidimensional, yet evaluations of large language models (LLMs) typically emphasize response accuracy while overlooking how m
arXiv:2608.02618v1 Announce Type: new Abstract: Recent studies have identified an ``Artificial Hivemind'' effect in Large Language Models (LLMs) causing models to converge on a narrow, homogenized con
arXiv:2503.04263v2 Announce Type: replace Abstract: Motivated by applications to the simulation of quantum many-body systems by neural networks, researchers have suggested several models which are ant
arXiv:2608.03855v1 Announce Type: new Abstract: Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extende
arXiv:2608.02834v1 Announce Type: new Abstract: We present a biconvex approach for minimum-time motion planning around convex obstacles that is guaranteed to converge, is anytime, and supports derivat
arXiv:2607.17447v2 Announce Type: replace-cross Abstract: As generative artificial intelligence enters scientific and professional work, its uncertainty must be defined on the states that matter for i
arXiv:2608.02705v1 Announce Type: cross Abstract: Comparing stochastically trained models requires estimating both a performance difference and its uncertainty from repeated runs. We study whether tra
arXiv:2608.03160v1 Announce Type: cross Abstract: When asked which of two events came first, video large language models can fail in two opposite ways: cave to a false claim, or reject a true one. Pri
arXiv:2608.02935v1 Announce Type: new Abstract: Arabic script uses 28 letters, many of which share a common base shape (rasm) and are distinguished only by dot placement. Because early Arabic manuscri
arXiv:2608.02955v1 Announce Type: cross Abstract: This research paper describes an exploratory study on the effectiveness of Chat Debugging: troubleshooting malfunctioning analog circuits on breadboar
arXiv:2608.03507v1 Announce Type: cross Abstract: Historical language change affects morphology, syntax, semantics, and pragmatics, yet computational studies typically examine these levels with incomp
arXiv:2608.03252v1 Announce Type: new Abstract: Multi-focus image fusion (MFIF) aims to generate an all-in-focus image from multiple images of the same scene focused at different regions. Most existin
arXiv:2403.09281v3 Announce Type: cross Abstract: We propose CLIP-EBC, the first fully CLIP-based model for accurate crowd density estimation. While the CLIP model has demonstrated remarkable success
arXiv:2608.03559v1 Announce Type: new Abstract: In multimodal crack segmentation for industrial facilities, the key challenge is preventing missing modalities from degrading pixel-level performance wh