Monotonic anomaly detection
arXiv:2410.23158v3 Announce Type: replace Abstract: Semi-supervised anomaly detection is based on the principle that any record that looks different from normal training data is a potential anomaly. H
Knowledge catalogue
arXiv:2410.23158v3 Announce Type: replace Abstract: Semi-supervised anomaly detection is based on the principle that any record that looks different from normal training data is a potential anomaly. H
arXiv:2609.01987v1 Announce Type: new Abstract: Patient exams in the cancer diagnosis and staging process typically generate several whole slide images (WSIs). One of the initial steps in training mod
arXiv:2609.02493v1 Announce Type: new Abstract: Accurate scene understanding in confined, cluttered spaces such as shelves is essential for service robots, as many everyday tasks require them to locat
arXiv:2606.09435v2 Announce Type: replace Abstract: Multilingual dictionaries are among the most valuable documentary resources for low-resource and endangered languages, yet many remain available onl
arXiv:2609.01618v1 Announce Type: cross Abstract: Telecom Service and Network Operations Centers (SNOCs) rely on large collections of cloud documents, including Standard Operating Procedures (SOPs), v
arXiv:2609.02751v1 Announce Type: new Abstract: As generative AI tools become increasingly powerful and easy to use, people can easily edit portrait images with a prompt, necessitating the task of ima
arXiv:2609.02379v1 Announce Type: cross Abstract: While existing work on LLM authorship attribution (AA) has made progress, available benchmarks remain limited, often focusing on English, controlled s
arXiv:2602.06504v2 Announce Type: replace-cross Abstract: Vision-based models for robotic grasping automate critical, repetitive, and draining industrial tasks. Existing approaches are typically limit
arXiv:2505.00759v3 Announce Type: replace-cross Abstract: The steady improvements of text-to-image (T2I) generative models lead to slow deprecation of automatic evaluation benchmarks that rely on stat
arXiv:2609.02854v1 Announce Type: new Abstract: The 3D center of mass (CoM) is a primary quantity in the biomechanical analysis of sport, rehabilitation, and clinical movement, yet existing 3D pose tr
arXiv:2609.02717v1 Announce Type: new Abstract: Large-scale training and refined optimization techniques have greatly improved sparse multi-view 3D reconstruction. Despite their relevance to surgery,
arXiv:2609.02366v1 Announce Type: cross Abstract: Named Entity Recognition (NER) has achieved substantial progress since the advent of large language models (LLMs). Nevertheless, the recognition of lo
arXiv:2609.01657v1 Announce Type: cross Abstract: Multimodal models often build on architectures designed for generative vision-language modeling, typically combining separately pretrained vision enco
arXiv:2609.01957v1 Announce Type: cross Abstract: Enterprise wireless access points (APs) are promising platforms for predictive machine learning (ML), but their primary responsibility remains providi
arXiv:2609.02727v1 Announce Type: cross Abstract: We approximate strongly continuous convex monotone semigroups by learning their Chernoff-type one-step operators with neural operators. First, we intr
arXiv:2510.10268v3 Announce Type: replace-cross Abstract: In many applications, one must propagate parameter uncertainty from an earlier (upstream) analysis, available as samples, to subsequent (downs
arXiv:2508.11180v2 Announce Type: replace-cross Abstract: Multi-view learning is widely applied to real-life datasets, but it often suffers from both missing views and missing labels. Prior probabilis
arXiv:2502.09884v4 Announce Type: replace-cross Abstract: We consider linear two-time-scale stochastic approximation algorithms driven by martingale noise. Recent applications in machine learning moti
arXiv:2609.01662v1 Announce Type: cross Abstract: For embodied systems, predictive agreement alone does not determine whether evidence warrants action; evidential origin matters. Repeated inference ov
arXiv:2609.01971v1 Announce Type: new Abstract: AI is rapidly advancing neuroscience, yet many laboratories fail to fully unleash its potential due to significant interdisciplinary barriers. While pre
arXiv:2603.09542v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are formulated to ground instructions in visual context and generate action sequences for robotic manipulation.
arXiv:2609.02158v1 Announce Type: cross Abstract: Legal Judgment Prediction (LJP) models are typically trained on documents that describe facts from a prosecutorial perspective. Existing datasets furt
arXiv:2609.02672v1 Announce Type: new Abstract: Hyper-Connections (HC) replace the single residual stream of a Transformer with n parallel ones, mixing them at every layer with a learned n imes n resi
arXiv:2609.01633v1 Announce Type: cross Abstract: A composite structural index summarises a network in one number; for a triangle-based index it is spectrally redundant: Tr(A^3) is the third moment of
arXiv:2609.02149v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly evolving from conversational assistants into agents capable of operating external digital environments.
arXiv:2512.19067v2 Announce Type: replace-cross Abstract: We introduce Cost-Aware (CA) Sequential Hypothesis Testing (CASHT), in which an active decision-maker selects sensing actions with differing,
arXiv:2609.01947v1 Announce Type: cross Abstract: Compact instruction-following rerankers are attractive for deployment, but conventional distillation pipelines typically train students by offline imi
arXiv:2609.01938v1 Announce Type: new Abstract: Dexterous manipulation with multi-fingered robot hands promises human-level dexterity, but collecting large-scale dexterous robot hand data remains diff
arXiv:2607.19128v2 Announce Type: replace Abstract: Vision-language models (VLMs) provide a unified representation space for textual and visual information, yet their potential as general-purpose back
arXiv:2609.02145v1 Announce Type: cross Abstract: We study online maximization of nonnegative, non-monotone DR-submodular functions over compact convex down-closed subsets of the d-dimensional unit cu
arXiv:2609.02566v1 Announce Type: new Abstract: Machine-learnt corrections can complement numerical weather prediction only if they adapt to the evolving model state while preserving dynamical consist
arXiv:2609.01933v1 Announce Type: new Abstract: Modern supply chain operations can require coordinating replenishment across thousands of heterogeneous items under correlated stochastic demand, hetero
arXiv:2609.02638v1 Announce Type: new Abstract: Knowledge graphs have become an important source of structured knowledge for Web applications, including search, question answering, and recommender sys
arXiv:2609.02333v1 Announce Type: cross Abstract: Brain cancer remains one of the most significant challenges in modern medicine, where the accuracy of early stage diagnosis is a decisive factor in pa
arXiv:2609.02510v1 Announce Type: new Abstract: We study body-only, 12-class acted-emotion classification from skeleton motion under leave-performer-out (LPO) evaluation, a hard, underdetermined setti
arXiv:2606.15255v2 Announce Type: replace Abstract: Coordinating heterogeneous multi-robot systems (MRS) for complex, long-horizon tasks requires both flexible high-level reasoning and efficient execu
arXiv:2609.01896v1 Announce Type: cross Abstract: Power-outage planning requires scenarios before an event occurs. These scenarios must represent uncertainty in magnitude, timing, and duration while p
arXiv:2607.17499v2 Announce Type: replace Abstract: The evolution of e-commerce has fundamentally transformed how users search for products, shifting from simple text-based keyword queries to complex
arXiv:2609.02272v1 Announce Type: cross Abstract: Faithfully translating research papers into repository-level implementations remains challenging because papers often describe methods at a high level
arXiv:2503.00287v3 Announce Type: replace Abstract: Reinforcement learning (RL) has achieved remarkable success in various robotic tasks; however, its deployment in real-world scenarios, particularly
arXiv:2609.02216v1 Announce Type: new Abstract: Inductive knowledge graph completion (IKGC) aims to predict missing links involving entities unseen during training, requiring models to learn transfera
arXiv:2609.02016v1 Announce Type: cross Abstract: Image super-resolution, which aims to reconstruct high-resolution images from their low-resolution observations, is fundamental to medical imaging, re
arXiv:2609.02373v1 Announce Type: cross Abstract: We study the dynamics of Stochastic Gradient Descent (SGD), which is known to steer deep neural networks toward invariant sets that correspond to simp
arXiv:2607.17117v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) decompose language model activations into sparse features, yet these models traditionally encode each token indepen
arXiv:2609.02236v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has become an effective paradigm for LLM post-training, but in multi-turn agentic tasks with sparse terminal rew
arXiv:2609.02231v1 Announce Type: new Abstract: Interview assessment requires per-criterion judgments grounded in behavioral evidence, yet surging applicant volumes have made human-only evaluation cos
arXiv:2609.02654v1 Announce Type: new Abstract: Low-dose computed tomography (LDCT) measurements contain mixed Poisson-Gaussian noise. However, most self-supervised methods rely on generic image stati
arXiv:2607.27287v2 Announce Type: replace Abstract: Planning over Temporal Dynamic Knowledge Graphs (TDKGs) presents theoretical challenges in open-world environments with incomplete information. Exis
arXiv:2606.23092v2 Announce Type: replace Abstract: Humans possess an innate ability to understand fine-grained interpersonal relationships, which is central to everyday social interactions. Although
arXiv:2609.02860v1 Announce Type: new Abstract: Modern crop breeding demands precise organ-level analysis for trait quantification, making plant point cloud segmentation (PPCS) increasingly important.
arXiv:2607.18151v2 Announce Type: replace Abstract: We present a novel Generalized Scene Reconstruction (GSR) approach called Plenoptic Condensation (PCon). PCon uses a multi-stage reconstruction pipe
arXiv:2508.00259v2 Announce Type: replace Abstract: While 3D Gaussian Splatting (3DGS) has established new standards for high-fidelity 3D scene modeling, interpreting massive, unstructured Gaussian pr
arXiv:2609.02328v1 Announce Type: cross Abstract: The PGM-index (Ferragina and Vinciguerra, VLDB'20) is one of the most practical learned indexes, owing to its theoretical elegance and consistently st
arXiv:2609.02391v1 Announce Type: cross Abstract: Political evasion refers to responses that engage with a question while withholding the requested information. Recent NLP work frames political evasio
arXiv:2609.01761v1 Announce Type: cross Abstract: A system often has to act long before it learns whether the act worked: a recommender sees a click in seconds and a purchase in days. With K actions a
arXiv:2609.02849v1 Announce Type: cross Abstract: Competitive programming has become a key test of large language model reasoning, with international competitions such as IOI and ICPC representing its
arXiv:2609.01962v1 Announce Type: new Abstract: Ultra-low-bit language models can reduce storage and memory bandwidth, but a nominal '1.58-bit' label does not fully describe the stored representation,
arXiv:2609.01999v1 Announce Type: cross Abstract: We study a variant of the Thompson Sampling (TS) algorithm, called alpha-TS, for solving stochastic generalized linear bandit problems. Existing analy
arXiv:2609.02480v1 Announce Type: new Abstract: Synthetic dialogue generation can support research in privacy-restricted service settings, but generated conversations must preserve communicative inten
arXiv:2609.02575v1 Announce Type: new Abstract: This paper investigates how a production transitional autonomous vehicle (tAV) develops and executes mandatory lane-change decisions. Using 150 controll