Knowledge catalogue
arXiv:2608.18919v1 Announce Type: new Abstract: Tabular machine learning benchmarks typically summarize performance by averaging scores, ranks, or pairwise wins across datasets. Such aggregates are us
arXiv:2608.18341v1 Announce Type: cross Abstract: Persistent acoustic monitoring can detect machine faults without physical contact, but always-on inference is constrained by power, latency, and deplo
arXiv:2608.19059v1 Announce Type: cross Abstract: Long-term robot operation in evolving environments requires object-level understanding that persists across repeated revisits. Existing systems either
arXiv:2608.18215v1 Announce Type: new Abstract: Existing 3D relighting methods operate through either explicit material decomposition, diffusion-based view-space generation, or a combination of both,
arXiv:2608.18810v1 Announce Type: new Abstract: An optimizer is usually chosen before training a deep neural network and then kept fixed. Treating optimizer choice as a hyperparameter could boost perf
arXiv:2608.18546v1 Announce Type: new Abstract: Multimodal urban data has expanded the applications of urban region representation learning, such as functional zone identification and real estate appr
arXiv:2608.18096v1 Announce Type: new Abstract: Assessing whether multimodal content aligns with macro-societal values, such as peace, justice, and freedom, has become an increasingly urgent challenge
arXiv:2608.18336v1 Announce Type: new Abstract: When evaluating language models on human exams, benchmarks typically score each response as right or wrong and report the overall accuracy. This approac
arXiv:2608.18419v1 Announce Type: cross Abstract: Recent work has shown that large language models (LLMs) exhibit strong numerical sequence modeling capabilities and show promise in time-series predic
arXiv:2608.18937v1 Announce Type: cross Abstract: Recent Multimodal Large Language Models (MLLMs) are rapidly evolving into unified understanding and generation (UAG) frameworks. However, extending th
arXiv:2608.18704v1 Announce Type: cross Abstract: Long-term memory is essential for agents that operate across extended interactions, yet existing memory systems and benchmarks predominantly focus on
arXiv:2608.18744v1 Announce Type: new Abstract: Agents improve quickly against a reliable automatic metric and stall without one, and the applications that need them most, report generation among them
arXiv:2608.18160v1 Announce Type: cross Abstract: Background: Python has become the dominant language in software and data science, yet embedded systems have remained tied to C/C++ due to performance
arXiv:2608.18774v1 Announce Type: new Abstract: Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical
arXiv:2606.17809v2 Announce Type: replace Abstract: Automated pollen identification from microscopy remains a bottleneck in aerobiology, palaeoecology and biodiversity monitoring, because scalable sys
arXiv:2608.19000v1 Announce Type: new Abstract: Automating graphic design synthesis from user-provided elements requires both a coherent overall composition and the exact preservation of each asset. E
arXiv:2608.18489v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) and knowledge-graph-based retrieval-augmented generation (KG-RAG) aim to ground answers in explicit graph evid
arXiv:2608.18141v1 Announce Type: cross Abstract: Predicting underwater acoustic transmission loss rapidly and accurately is crucial for real-time ocean acoustic applications. While Fourier Neural Ope
arXiv:2608.18827v1 Announce Type: cross Abstract: Reward function design remains a bottleneck in reinforcement learning. While large language models (LLMs) have enabled automated reward generation, ex
arXiv:2506.01367v4 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly integrated into agentic AI systems, yet their propensity to generate hallucinations remains a critical
arXiv:2608.18274v1 Announce Type: cross Abstract: OpenAI Privacy Filter is a compact, bidirectional token-classification model for detecting and redacting personally identifiable information (PII) and
arXiv:2608.18982v1 Announce Type: new Abstract: Bioassay activity prediction is often data-limited because drug-discovery datasets rely on time-consuming and expensive wet-lab experiments for data gen
arXiv:2608.18448v1 Announce Type: cross Abstract: More context does not require a larger retrieval budget. Under the same ceiling, a retrieval system can recover more of the evidence a question requir
arXiv:2608.18558v1 Announce Type: cross Abstract: The prediction of equilibrium beach profiles under tidal influence is of fundamental importance for sustainable coastal development, informing shoreli
arXiv:2608.18579v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong potential for image quality assessment (IQA) by improving consistency between quality ratin
arXiv:2608.19049v1 Announce Type: new Abstract: Deep reinforcement learning (DRL) has recently gained a great attention due to its real-time adaptation and effectiveness in complex optimization proble
arXiv:2608.18716v1 Announce Type: new Abstract: Diagnosing faults in rotating machinery is essential for ensuring the reliability of industrial processes. Random convolutional kernel-based Time Series
arXiv:2608.18429v1 Announce Type: cross Abstract: This work presents a data-driven methodology for multi-objective optimization under uncertainty of process parameters in the fused filament fabricatio
arXiv:2608.18851v1 Announce Type: new Abstract: Convolution integrals widely exist in applications, and to enable fast and accurate computations, this paper introduces two general multi-stage neural o
arXiv:2608.18401v1 Announce Type: cross Abstract: Evaluating interaction quality in real-world HRI is an important challenge. If interaction quality can be estimated reliably, the results can be used
arXiv:2608.18571v1 Announce Type: new Abstract: Sleep stage classification from single-channel electroencephalography (EEG) is essential for wearable and home-based sleep monitoring. However, many dee
arXiv:2608.18094v1 Announce Type: cross Abstract: Large pretrained language models have demonstrated remarkable capabilities across diverse languages, yet critically underrepresented low-resource lang
arXiv:2608.18090v1 Announce Type: cross Abstract: Inside a modern language model sits a single internal direction that tracks how positive or negative a sentence feels. We show how to find this valenc
arXiv:2608.18597v1 Announce Type: new Abstract: Protein language models are widely used priors for protein sequence design, and a growing body of work controls them at inference time as an alternative
arXiv:2608.18474v1 Announce Type: new Abstract: Cross-lingual sequence alignment is fundamental for building and exploiting parallel corpora, spanning mappings from documents and sentences down to wor
arXiv:2608.18586v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) are increasingly used as OCR systems in document and knowledge-processing pipelines, but their ability to fai
arXiv:2602.16125v3 Announce Type: replace Abstract: Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneo
arXiv:2510.09253v2 Announce Type: replace Abstract: Automatic systems for document understanding require multimodal models that accurately identify sensitive visual content, even in the presence of im
arXiv:2608.18910v1 Announce Type: new Abstract: Hard combinatorial optimization problems, many of which are NP-hard, present fundamental algorithmic challenges. Average-case analysis on random instanc
arXiv:2608.18194v1 Announce Type: new Abstract: This paper presents new theoretical results on generalizing the Jaccard distance for lattices and real valuations. We demonstrate that when the valuatio
arXiv:2608.18360v1 Announce Type: cross Abstract: Agentic AI systems take consequential actions governed by more than one pre-action control at once: authority, resource, and evidence gates that can a
arXiv:2608.19014v1 Announce Type: cross Abstract: Autonomous vehicles depend on fast and reliable perception systems to detect surrounding vehicles, pedestrians, cyclists, traffic signs, and other roa
arXiv:2608.18130v1 Announce Type: cross Abstract: We study online bipartite matching with reusable server capacity and non-stationary rewards. Jobs arrive sequentially, reveal compatible servers, rewa
arXiv:2505.01783v2 Announce Type: replace Abstract: Online anomaly detection is essential in fields such as cybersecurity, healthcare, industrial monitoring, and telecommunications, where promptly ide
arXiv:2603.25954v2 Announce Type: replace Abstract: The use of satellite networks has increased significantly in recent years due to their advantages over purely terrestrial systems, such as higher av
arXiv:2608.19098v1 Announce Type: cross Abstract: Multi-teacher on-policy distillation (M-OPD) has emerged as a promising paradigm for consolidating domain-specialized reinforcement learning (RL) expe
arXiv:2608.18109v1 Announce Type: new Abstract: Narrative Entropy (S_n) is a proposed quantitative descriptor within the Bulut Doctrine, intended to capture the rate at which a narrative text imposes
arXiv:2608.18367v1 Announce Type: cross Abstract: Accurate localization and segmentation of the optic disc (OD) are important for retinal image analysis and glaucoma assessment, yet remain challenging
arXiv:2608.18133v1 Announce Type: new Abstract: Reliable transformer fault diagnosis is essential for maintaining power system stability. The IEEE Key Gas Method (KGM), a widely utilized approach in D
arXiv:2608.18126v1 Announce Type: cross Abstract: This study evaluates the potential of electric vehicle (EV) charging flexibility to enhance both energy efficiency and power grid stability. Using rea
arXiv:2608.18516v1 Announce Type: cross Abstract: Precise segmentation of the optic disc and cup is critical for the early detection and diagnosis of glaucoma. However, achieving consistently high per
arXiv:2608.18846v1 Announce Type: new Abstract: Last-mile delivery aims to handle dynamically arriving orders with couriers while modeling complex spatial and temporal correlations. Recent learning-ba
arXiv:2608.18672v1 Announce Type: cross Abstract: We present the orienteering problem with uncertain time-varying rewards (OP-UTVR), a novel variant of the orienteering problem (OP). While most existi
arXiv:2608.19021v1 Announce Type: new Abstract: Global Covariance Pooling (GCP) improves deep networks by capturing second-order feature statistics, and is especially effective for fine-grained recogn
arXiv:2506.03079v3 Announce Type: replace Abstract: Recent embodied intelligence suffers from data scarcity, while conventional simulators lack visual realism. Controllable video generation is emergin
arXiv:2608.18820v1 Announce Type: new Abstract: Arguments often omit premises or claims, forming enthymemes. We study pairwise logical selection between two candidates for the omitted component. Exist
arXiv:2608.18531v1 Announce Type: new Abstract: Industrial explainable-recommendation systems built on LLMs incur a substantial serving cost: each request triggers an LLM generation, with latency in t
arXiv:2608.18622v1 Announce Type: new Abstract: Automatic portrait retouching has advanced rapidly, yet its objective is inherently subjective: the same portrait admits multiple professionally valid r
arXiv:2608.19188v1 Announce Type: new Abstract: Dual-arm robotic grasping is essential for manipulating large, heavy, and geometrically complex objects that cannot be reliably handled using a single m
arXiv:2608.18484v1 Announce Type: cross Abstract: Training-free block-sparse attention can accelerate video transformers, but row-wise attention concentration does not by itself specify an executable