Knowledge catalogue
arXiv:2510.01832v2 Announce Type: replace Abstract: Semi-structured content in HTML tables, lists, and infoboxes accounts for a substantial share of factual data on the web, yet the formatting complic
arXiv:2608.17426v1 Announce Type: cross Abstract: We introduce Semantic Task Completion Video Generation, an outcome-oriented video generation task. Under this formulation, success requires both achie
arXiv:2608.17333v1 Announce Type: cross Abstract: Modern probabilistic time-series forecasters often express uncertainty through forecast samples. While typically converted into nominal prediction reg
arXiv:2608.16918v1 Announce Type: cross Abstract: Patent prior-art retrieval is a recall-oriented search task over long and highly structured technical documents. Dense retrieval improves semantic mat
arXiv:2401.02020v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs), known for their biologically plausible architecture, face the challenge of limited performance. The self-atten
arXiv:2608.17598v1 Announce Type: new Abstract: Despite the rapid progress of deep neural networks in visual recognition, their adoption in high-risk medical applications remains limited due to reliab
arXiv:2608.17443v1 Announce Type: new Abstract: Knowledge Graph Reasoning (KGR) aims to discover latent facts by leveraging the structural evidence available in KGs, posing a challenge to the structur
arXiv:2608.16963v1 Announce Type: new Abstract: Learning analytics often treats unsupervised clusters of intelligent tutoring system (ITS) logs as learner types that should predict learning. We test t
arXiv:2608.17421v1 Announce Type: new Abstract: Deep snake is a promising family of instance segmentation methods that accurately predicts object-level contours, thereby overcoming common pixel-level
arXiv:2205.11930v3 Announce Type: replace-cross Abstract: Human ratings are the gold standard in NLG evaluation. The standard protocol is to collect ratings of generated text, average across annotator
arXiv:2608.18061v1 Announce Type: new Abstract: We give a two-player zero-sum repeated game between a learner and nature whose value identity generates Bayesian updating and an exact accounting of exp
arXiv:2608.17829v1 Announce Type: cross Abstract: LLMs increasingly rely on external contexts, such as pre-defined system prompts or retrieved documents, to improve generation quality. However, proces
arXiv:2608.17218v1 Announce Type: new Abstract: Works of literature are complicated; they balance plot, suspense, surprise, and artistic expression. Summaries of literature prioritize plot, and theref
arXiv:2608.16956v1 Announce Type: new Abstract: API buyers purchase a dated contract, not a model name alone: the contract includes the requested and served model, reasoning-effort term or its omissio
arXiv:2608.17747v1 Announce Type: new Abstract: Although text-to-image diffusion models exhibit remarkable generative power, concept erasure techniques are essential for preventing harmful content. Ex
arXiv:2608.17398v1 Announce Type: new Abstract: Persistent clouds blind optical satellites during floods. While Synthetic Aperture Radar (SAR) penetrates clouds, its raw data is noisy and lacks clear
arXiv:2608.17128v1 Announce Type: new Abstract: A personal AI system needs a model of the user's goals, constraints, and ongoing commitments to plan and act on their behalf, and the quality of that mo
arXiv:2608.17841v1 Announce Type: cross Abstract: Multi-armed bandit algorithms are evaluated by regret, yet comparable regret can coexist with different allocations across independent runs. We study
arXiv:2608.17153v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has significantly enhanced the performance of large language models (LLMs), yet these systems remain vulnerable to
arXiv:2510.08713v3 Announce Type: replace Abstract: Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typical
arXiv:2608.17268v1 Announce Type: cross Abstract: Curriculum learning has been widely adopted in the post-training of large language models by organizing training data from easy to hard. However, its
arXiv:2608.17283v1 Announce Type: new Abstract: Reconstructing dynamic 4D scenes requires jointly estimating correspondence, geometry, object motion, and camera motion. Existing feed-forward methods t
arXiv:2510.14462v3 Announce Type: replace Abstract: Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly explored for identifying pathological brain abnormalit
arXiv:2511.19759v3 Announce Type: replace Abstract: Semi-supervised learning (SSL) has emerged as an efficient paradigm for medical image segmentation, reducing the reliance on extensive expert annota
arXiv:2608.17325v1 Announce Type: new Abstract: Tokenization is a fundamental component of language modeling pipelines. Despite its importance, it is often fixed, even though it significantly impacts
arXiv:2608.17809v1 Announce Type: new Abstract: Humans naturally form and express beliefs in daily communication, e.g., 'I think the answer is 3' or 'I suppose that's right.' Such beliefs inevitably i
arXiv:2608.18025v1 Announce Type: cross Abstract: GPT-style models achieve strong performance by representing language with finite vocabularies of reusable discrete tokens. This success has motivated
arXiv:2608.17033v1 Announce Type: cross Abstract: Visual Place Recognition (VPR) aims to recognize the location of a query image by comparing it with a set of geo-referenced images. Although many data
arXiv:2608.14591v1 Announce Type: cross Abstract: The integration of artificial intelligence (AI) and wireless communications is widely regarded as a core objective of sixth-generation (6G) systems. H
arXiv:2608.15966v1 Announce Type: new Abstract: We study stochastic approximation of fixed points of a non-expansive operator when the oracle samples originate from a continuing Markovian trajectory.
arXiv:2404.15616v2 Announce Type: replace-cross Abstract: Grover's search algorithms, including various Partial Grover Searches (PGS), suffer from scaling issues when multiple solutions are sought, as
arXiv:2608.15828v1 Announce Type: cross Abstract: Current evaluation of metaphor explanations relies mainly on holistic quality ratings, revealing little about how explanation quality is structured or
arXiv:2608.15335v1 Announce Type: new Abstract: We consider for an arbitrary fixed rho and for each positive integer n a multilayer feedforward artificial neural network with rho layers, n neurons in
arXiv:2608.15558v1 Announce Type: cross Abstract: For mgeq 2, let c_p(m) be the all-dimensional best constant in $ left|sum_{k=1}^m A_kright|_p leq c_p(m)left|sum_{k=1}^m |A_k|right|_p. Tang and Zhang
arXiv:2608.16233v1 Announce Type: cross Abstract: Missing or degraded sequences can limit prostate multiparametric MRI. We developed MSCNet, a sequence-conditioned cross-modal generative framework for
arXiv:2608.15102v1 Announce Type: new Abstract: We investigate whether Mixture-of-Experts (MoE) language models develop linguistically structured expert routing during bilingual language acquisition.
arXiv:2608.14968v1 Announce Type: cross Abstract: We consider nonparametric regression when the association between a response and its covariates changes across an unknown partition of a spatial domai
arXiv:2601.08024v2 Announce Type: replace Abstract: Maintaining or improving the performance of Deep Neural Networks (DNNs) through fine-tuning requires labeling newly collected inputs, a process that
arXiv:2608.14622v1 Announce Type: new Abstract: People are increasingly using large language models (LLMs) to seek advice, including for parenting. Parenting is a critical and socially sensitive domai
arXiv:2608.16461v1 Announce Type: cross Abstract: Central Bank Digital Currency (CBDC)-based welfare schemes may be potentially privacy invasive as they process significant volumes of beneficiary pers
arXiv:2608.15363v1 Announce Type: new Abstract: Label uncertainty and annotator disagreement are common challenges in the field of computer vision, yet their study has largely been confined to the med
arXiv:2603.04288v2 Announce Type: replace Abstract: Colonic polyps are well-recognized precursors to colorectal cancer (CRC), typically detected during colonoscopy. However, the variability in appeara
arXiv:2608.14733v1 Announce Type: cross Abstract: Building on the foundation of single-hidden-layer neural networks, Fourier Feature Networks (FENs) are proposed, which incorporate Fourier features us
arXiv:2608.15809v1 Announce Type: new Abstract: Behavioral accuracy, linear decodability, and successful activation interventions do not by themselves show that a model carries an operation-level stru
arXiv:2608.16236v1 Announce Type: new Abstract: Collaborative inference (CI) splits a model between an edge device and a server, whereby the client computes an intermediate activation, transmits it, a
arXiv:2608.14689v1 Announce Type: new Abstract: Residual connections are a fundamental component of transformer architectures, yet the roles of the attention and feed-forward residual pathways remain
arXiv:2512.09005v2 Announce Type: replace Abstract: Body and face motion play an integral role in communication. They convey crucial information on the participants. Advances in generative modeling an
arXiv:2608.15160v1 Announce Type: cross Abstract: Automatic modulation recognition (AMR) faces distinct representation bottlenecks under varying observation lengths, where a single model architecture
arXiv:2608.15306v1 Announce Type: cross Abstract: High-throughput single-cell and spatial transcriptomic technologies provide high-resolution snapshots of heterogeneous cellular states, but their dest
arXiv:2608.15051v1 Announce Type: new Abstract: This paper proposes a Mamba surrogate model with mixture-of-experts (MoE) routing to represent the transient dynamics of inverter-based resources. A Mam
arXiv:2608.15440v1 Announce Type: new Abstract: Motion planning problems such as collision-free navigation and contact-rich manipulation can be naturally formulated as optimization problems that coupl
arXiv:2608.14631v1 Announce Type: new Abstract: As consumers increasingly turn to AI chatbots for skincare advice, the technical accuracy of Large Language Models (LLMs) in cosmetic chemistry remains
arXiv:2602.10204v2 Announce Type: replace Abstract: We introduce MVN-Grad (Momentum on Variance-Normalized Gradients), an Adam-style optimizer that improves stability and performance by combining two
arXiv:2608.16377v1 Announce Type: cross Abstract: Instance-level lesion detection has been an increasingly larger focal point in medical image segmentation besides the more standard voxel-level overla
arXiv:2608.16319v1 Announce Type: new Abstract: This first release of Prior Labs in relational learning shows our continued commitment to open science. We open-source three pieces of software that we
arXiv:2608.15153v1 Announce Type: cross Abstract: Differentially private federated learning must balance privacy protection against model accuracy and training efficiency. Static gradient clipping app
arXiv:2608.15721v1 Announce Type: new Abstract: This report describes our submission to the Big Cross-Modal Attenuation Correction (BIC-MAC) 2026 Challenge for CT-less PET attenuation correction throu
arXiv:2608.16690v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are widely used for automated annotation, yet their per-class accuracy varies widely (e.g., 12%-98% across the
arXiv:2608.16143v1 Announce Type: cross Abstract: We present AnyTalk, a novel method for generating 3D speech animations for arbitrary characters without requiring any animation data. While existing a
arXiv:2608.14866v1 Announce Type: cross Abstract: Objective: Small-sample molecular classification requires feature selectors that identify predictive, stable, and nonredundant subsets for binary and