Knowledge catalogue
arXiv:2607.04608v1 Announce Type: new Abstract: Lensless imaging enables compact and versatile computational cameras by replacing bulky optics with thin coded elements. However, reconstruction from th
arXiv:2507.03670v2 Announce Type: replace-cross Abstract: Writing longer prompts for an AI assistant to generate a story increases psychological ownership, a user's feeling that the writing belongs to
arXiv:2607.02553v1 Announce Type: new Abstract: Introduction: Objective neuroimaging biomarkers may improve Parkinson's disease motor assessment by capturing brain variation not directly observable fr
arXiv:2605.11012v2 Announce Type: cross Abstract: Programming the static friction of mechanical interfaces is critical for soft robotics, haptics, and precision gripping. Static friction is governed b
arXiv:2512.05672v2 Announce Type: replace-cross Abstract: Recent approaches in controllable novel view video generation often rely on fine-tuning pre-trained Video Diffusion Models (VDMs). This domina
arXiv:2512.08854v3 Announce Type: replace Abstract: It has been hypothesized that achieving the data efficiency of human visual perception requires a generative approach in which internal representati
arXiv:2601.22378v3 Announce Type: replace-cross Abstract: Maximum likelihood estimators (MLE) and control variate estimators (CVE) have been used in conjunction with known information across sketching
@__JohnNguyen__ and I are presenting the Beyond Language Modeling paper as an ICML spotlight in 30 minutes at the 10:30 AM poster session! I’ll also be at the AMI Mixer on Thursday and hanging around
arXiv:2607.02862v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) and Dialect Identification (DID) are crucial for Indian languages, many of which are low-resource and exhibit signifi
arXiv:2511.18613v2 Announce Type: replace-cross Abstract: This study presents a controlled comparison of baseline Kolmogorov-Arnold Networks (KAN), implemented via PyKAN, and Long Short-Term Memory (L
arXiv:2607.04820v1 Announce Type: new Abstract: Decoding hand kinematics from surface electromyography (EMG) is a core challenge in wearable biosignal processing with clinical relevance for prosthetic
arXiv:2607.05013v1 Announce Type: new Abstract: Although LLMs have made significant progress in mathematical reasoning, determining whether a mathematical problem is solvable remains a fundamental yet
arXiv:2603.11784v2 Announce Type: replace Abstract: As scaling laws push the training of frontier large language models (LLMs) toward ever-growing data requirements, training pipelines are approaching
arXiv:2603.23844v2 Announce Type: replace Abstract: Recent work provides overwhelming evidence that LLMs, even those trained to scale their reasoning trace, quickly deteriorate at planning as problems
arXiv:2607.04525v1 Announce Type: cross Abstract: How concepts are represented in neural networks is a fundamental question in machine learning. The dominant view treats concept representations as sta
arXiv:2603.04795v2 Announce Type: replace-cross Abstract: Medical image analysis depends on accurate segmentation and controllable synthesis, but both tasks face severe spatial imbalance: lesions occu
arXiv:2607.04819v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables computation on encrypted data, but practical encrypted Transformer inference is bottlenecked by the sequentia
arXiv:2607.03320v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) generates natural-language descriptions of semantic changes between paired remote sensing images (RSIs),
arXiv:2607.04603v1 Announce Type: cross Abstract: Infrared small target detection (IRSTD) aims to identify long distance small targets from complex infrared backgrounds, and is a fundamental task in r
arXiv:2607.03481v1 Announce Type: new Abstract: Modernizing cancer registries with deep learning is opening new opportunities to automate labor-intensive tasks such as the coding of pathology reports.
arXiv:2602.10099v2 Announce Type: replace-cross Abstract: Leveraging representation encoders for generative modeling offers a path for efficient, high-fidelity synthesis. However, standard diffusion t
arXiv:2406.14340v2 Announce Type: replace-cross Abstract: The standard stochastic gradient descent (SGD) optimization method, as well as adaptive methods such as the Adam optimizer fail to converge if
arXiv:2607.02909v1 Announce Type: cross Abstract: Taxonomies provide key information about the semantic relationships between concepts and the inherent organization of vision and language. Despite the
arXiv:2603.00968v2 Announce Type: replace-cross Abstract: The Nash-Sutcliffe efficiency (ext{NSE}) is a widely used, positively oriented relative measure for evaluating forecasts across multiple time
arXiv:2607.04486v1 Announce Type: cross Abstract: Diagnosing and monitoring diseases frequently involves the analysis of human biological samples, with blood analysis being pivotal. Specifically, leuk
arXiv:2506.02212v2 Announce Type: replace-cross Abstract: Natural Language Processing (NLP) has transformed various fields beyond linguistics by applying techniques originally developed for human lang
arXiv:2607.03715v1 Announce Type: new Abstract: Medical imaging models often degrade when deployed at new clinical sites due to differences in imaging equipment, protocols, and patient populations. Te
arXiv:2607.03062v1 Announce Type: new Abstract: While lightweight polyp segmentation is highly desirable for low-cost deployment, reported performance gains often stem from upgraded backbone encoders,
arXiv:2603.13334v4 Announce Type: replace-cross Abstract: Lipschitz-based robustness certification bounds a network's sensitivity through concrete numerical computation rather than symbolic reasoning,
arXiv:2603.07965v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) for high-dimensional constrained problems remains a significant challenge due to the curse of dimensionality. We pr
arXiv:2506.19136v4 Announce Type: replace Abstract: We show that the out-of-equilibrium driving protocol of score-based generative models (SGMs) can be learned via local learning rules. The gradient w
arXiv:2607.03751v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models acquire broad embodied capabilities through large-scale pretraining, yet their generalization remains far more fragi
arXiv:2607.03699v1 Announce Type: new Abstract: In many multisensor systems, measurements from different sensors are subject to unknown relative time delays. Accurate state estimation requires that de
arXiv:2607.03682v1 Announce Type: cross Abstract: Convection-dominated convection-diffusion problems often develop thin layers, where the solution has sharp transition profiles and its derivatives are
arXiv:2607.04531v1 Announce Type: cross Abstract: Low-precision neural networks are attractive for resource-constrained hardware, but fixed-point arithmetic introduces failure modes that are often hid
arXiv:2510.25147v3 Announce Type: replace Abstract: To mitigate acute wildfire ignition risks, utilities de-energize power lines in high-risk areas. The Optimal Power Shutoff (OPS) problem optimizes l
arXiv:2502.05684v5 Announce Type: replace-cross Abstract: How can we effectively remove or ``unlearn'' undesirable information, such as specific features or the influence of individual data points, fr
arXiv:2510.02208v3 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative priors for solving inverse imaging problems. However, their practical deployment is hinde
arXiv:2407.20893v2 Announce Type: replace-cross Abstract: Cardiac arrhythmia, a condition characterized by irregular heartbeats, often serves as an early indication of various heart ailments. With the
arXiv:2607.04403v1 Announce Type: cross Abstract: Binary change detection in remote sensing requires both complete changed-region localization and accurate boundary delineation. We present MambaRefine
arXiv:2607.03973v1 Announce Type: new Abstract: Concept erasure aims to remove a target concept from a representation while preserving the other information encoded in it. This is difficult because re
arXiv:2607.04535v1 Announce Type: new Abstract: Orthogonal and Stiefel layers give neural weights exact spectral control, but they also impose a strong modeling constraint: all represented singular va
arXiv:2603.19048v2 Announce Type: replace Abstract: Recent generative models can produce high-fidelity videos, yet they often exhibit 3D spatial geometric inconsistencies. Existing evaluation methods
arXiv:2602.14469v3 Announce Type: replace Abstract: Reverse Chain-of-Thought Generation (RCG) synthesizes reasoning traces from query-answer pairs, but it risks producing post-hoc rationalizations: wh
arXiv:2607.04600v1 Announce Type: new Abstract: Graph eXplainable AI (G-XAI) is increasingly important for making Graph Neural Networks interpretable and accountable. While a growing number of explain
arXiv:2606.16337v3 Announce Type: replace Abstract: Predictive modeling for clinical decision support requires not only strong predictive performance but also transparent decision logic. Although deep
arXiv:2607.04747v1 Announce Type: new Abstract: Survival analysis on Whole Slide Images (WSIs) is important in computational pathology for prognosis estimation and treatment planning. However, existin
arXiv:2211.10872v2 Announce Type: replace Abstract: Open-set recognition refers to the problem in which classes that were not seen during training appear at inference time. This requires the ability t
arXiv:2511.13039v2 Announce Type: replace Abstract: Open-Vocabulary Temporal Action Localization (OV-TAL) aims to recognize and localize instances of any desired action categories in videos without ex
arXiv:2409.07589v2 Announce Type: cross Abstract: EEG-based emotion recognition holds significant potential in the field of brain-computer interfaces. A key challenge lies in extracting discriminative
arXiv:2607.04597v1 Announce Type: new Abstract: In this paper, we study the universal approximation property of residual neural networks, and obtain some new results. For input and output dimensions d
arXiv:2607.02938v1 Announce Type: new Abstract: Clinical time series prediction in intensive care units remains challenging due to heterogeneous physiological variables and informative missingness. Th
arXiv:2607.03643v1 Announce Type: cross Abstract: Purpose: Early screening for eye diseases is critical in low- and middle-income countries where access to care is limited. We investigate whether a co
arXiv:2603.29499v2 Announce Type: replace-cross Abstract: Classical proportional--integral--derivative (PID) control remains widely used in industrial control systems, while model predictive control (
arXiv:2607.02929v1 Announce Type: cross Abstract: Visual brand language is the set of visual properties that convey brand identity for a product. What is the impact of visual brand language on a perso
arXiv:2607.05238v1 Announce Type: new Abstract: JEPA world models predict the next latent state with a single deterministic predictor trained by latent regression. We show that this fails structurally
arXiv:2607.02764v1 Announce Type: new Abstract: Infrastructure maintenance, contact-based inspection, and emergency response can benefit from aerial vehicles that act as a flying human hand with extre
arXiv:2601.23038v3 Announce Type: replace Abstract: Mobile robots have become indispensable for exploring hostile environments, such as in space or disaster relief scenarios, but often remain limited
arXiv:2601.08828v2 Announce Type: replace-cross Abstract: Despite the rapid progress of video generation models, the role of data in influencing motion is poorly understood. We present Motive (MOTIon
arXiv:2607.03576v1 Announce Type: cross Abstract: Point cloud compression relies on techniques to compress both geometry and attributes. Motion-based approaches for dynamic solid point cloud geometry