Knowledge catalogue
arXiv:2604.26351v1 Announce Type: new Abstract: Language models (LMs) behave more like humans when their cognitive resources are restricted, particularly in predicting sentence processing costs such a
arXiv:2510.08278v3 Announce Type: replace Abstract: Embodied Reference Understanding requires identifying a target object in a visual scene based on both language instructions and pointing cues. While
arXiv:2604.26230v1 Announce Type: new Abstract: I developed a new version of Latent Semantic Scaling (LSS) employing word2vec as a masked language model. Unlike original spatial models, it assigns pol
arXiv:2603.25980v2 Announce Type: replace-cross Abstract: Transition states, the first-order saddle points on the potential energy surfaces, govern the kinetics and mechanisms of chemical reactions an
arXiv:2604.25979v1 Announce Type: cross Abstract: We present a quantitative analysis of character-pair substitution ratios in the Voynich manuscript, testing whether Currier's A/B language distinction
arXiv:2604.07387v2 Announce Type: replace-cross Abstract: We present a design automation framework for analog circuit sizing that produces calibrated, topology-specific analytical equations from raw c
arXiv:2604.26348v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success in image generation, yet their training is predominantly driven by full-reference objectives that en
arXiv:2604.26492v1 Announce Type: cross Abstract: Visual data compression is shifting from human-centered reconstruction to machine-oriented representation coding. In this setting, an image is often m
arXiv:2604.26326v1 Announce Type: cross Abstract: Reinforcement learning (RL) has unlocked complex reasoning abilities in large language models (LLMs). However, most RL algorithms suffer from performa
arXiv:2604.26571v1 Announce Type: new Abstract: Municipal solid waste incineration is increasingly central to urban waste management, yet its sustainability benefit depends on controlling carbon emiss
AI automates tasks, not jobs, and when a task gets cheaper, demand for the job grows. AI cannot automate jobs end-to-end because it lacks autonomy and cannot operate without supervision. There is stil
arXiv:2604.25931v1 Announce Type: new Abstract: We identify a previously unknown calibration property of large language models: providing one confirmed intermediate fact toward a multi-step reasoning
arXiv:2604.26237v1 Announce Type: new Abstract: This study applied the Apriori algorithm to analyze behavioral interaction patterns associated with learned helplessness (LH) in mathematics tutoring sy
arXiv:2604.26437v1 Announce Type: new Abstract: Purpose: Rapid and reliable diagnostic tools are crucial for managing respiratory diseases like COVID-19, where chest X-ray analysis coupled with artifi
arXiv:2603.13589v2 Announce Type: replace-cross Abstract: Estimating motion from spatiotemporal geoscientific data is a fundamental component of many environmental modeling and forecasting tasks. In t
arXiv:2604.26349v1 Announce Type: cross Abstract: We present a learning-augmented online algorithm for the preemptive FIFO buffer management problem, where packets arrive online to a finite-capacity b
arXiv:2604.26809v1 Announce Type: new Abstract: Federated Unlearning (FU) is an emerging paradigm in Federated Learning (FL) that enables participating clients to fully remove their contributions from
arXiv:2509.26184v5 Announce Type: replace-cross Abstract: Generation of citation-backed reports is a primary use case for retrieval-augmented generation (RAG) systems. While open-source evaluation too
arXiv:2604.26310v1 Announce Type: new Abstract: Fine-grained emotion classification, which identifies specific emotional states such as happiness, anger, sadness, and fear, remains a challenging task
arXiv:2604.26148v1 Announce Type: cross Abstract: AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality
arXiv:2604.26910v1 Announce Type: new Abstract: This paper presents a planning pipeline framework for locomotion in rope-assisted robots climbing vertical surfaces. The proposed framework is formulate
arXiv:2604.26048v1 Announce Type: new Abstract: This paper presents a principled and scalable framework for systematically generating complex Question Answering (QA) data. In the core of this framewor
arXiv:2604.26209v1 Announce Type: cross Abstract: Some text generation tasks, such as Attribute Value Extraction (AVE), require decoding multiple independent sequences from the same document context.
arXiv:2604.02021v2 Announce Type: replace Abstract: Voxel-grid reinforcement learning is widely adopted for path planning in redundant manipulators due to its simplicity and reproducibility. However,
arXiv:2601.19216v2 Announce Type: replace-cross Abstract: The emerging applications of next-generation wireless networks demand high-fidelity environmental intelligence. 3D radio maps bridge physical
arXiv:2604.26169v1 Announce Type: new Abstract: Treatment allocation under budget constraints is a central challenge in digital advertising: advertisers must decide which users to show ads to while sp
arXiv:2604.26176v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answerin
arXiv:2604.26241v1 Announce Type: new Abstract: Passive RFID tags offer a cost-effective and scalable solution for tracking numerous deployed assets. However, in forested environments, signal attenuat
arXiv:2601.13606v2 Announce Type: replace Abstract: Chart reasoning is a critical capability for Vision Language Models (VLMs). However, the development of open-source models is severely hindered by t
arXiv:2604.26301v1 Announce Type: new Abstract: Graph Contrastive Learning (GCL) has emerged as a prominent framework for unsupervised graph representation learning. However, relying on augmentation d
arXiv:2604.26664v1 Announce Type: cross Abstract: Traditional iterative reconstruction methods are accurate but computationally expensive, limiting their use in high-throughput and real-time ptychogra
arXiv:2604.25928v1 Announce Type: new Abstract: Professional domain knowledge underpins human civilization, serving as both the basis for industry entry and the core of complex decision-making and pro
arXiv:2405.13729v3 Announce Type: replace-cross Abstract: In this paper, we study an under-explored but important factor of diffusion generative models, i.e., the combinatorial complexity. Data sample
arXiv:2503.02332v3 Announce Type: replace-cross Abstract: Accurate segmentation of 3D vascular structures is essential for various medical imaging applications. The dispersed nature of vascular struct
arXiv:2604.26229v1 Announce Type: new Abstract: This study compares machine learning and deep learning approaches for cyberbullying detection in Indonesian-language Instagram comments. Using a balance
arXiv:2511.22958v2 Announce Type: replace Abstract: Deep learning has revolutionized solar image analysis, yet most approaches train task-specific encoders from scratch or rely on natural-image pretra
arXiv:2506.20876v4 Announce Type: replace Abstract: Technological progress has led to concrete advancements in tasks that were regarded as challenging, such as automatic fact-checking. Interest in ado
arXiv:2309.13722v3 Announce Type: replace-cross Abstract: Recently, several deep learning (DL) methods for approximating high-dimensional partial differential equations (PDEs) have been proposed. The
arXiv:2604.26558v1 Announce Type: cross Abstract: Deep learning methods have proved highly effective for classification and image recognition problems. In this paper, we ask whether this success can b
arXiv:2604.26419v1 Announce Type: cross Abstract: Large Vision-Language Models (VLMs) have achieved remarkable multimodal performance yet remain prone to factual hallucinations, particularly in long-t
arXiv:2604.26281v1 Announce Type: cross Abstract: To preserve or not to preserve prosody is a central question in voice anonymization. Prosody conveys meaning and affect, yet is tightly coupled with s
arXiv:2604.26656v1 Announce Type: new Abstract: Differential Privacy (DP) for text matured from disjointed word-level substitutions to contiguous sentence-level rewriting by leveraging the generative
arXiv:2207.06229v3 Announce Type: replace-cross Abstract: Massive vector field datasets are common in multi-spectral optical and radar sensors, among many other emerging areas of application. We devel
arXiv:2604.26766v1 Announce Type: cross Abstract: Accurate and consistent Emergency Severity Index (ESI) assignment remains a persistent challenge in emergency departments, where highly variable free-
arXiv:2511.10816v3 Announce Type: replace Abstract: Search and rescue (SAR) robots are required to quickly traverse terrain and perform high-force rescue tasks, necessitating both terrain adaptability
arXiv:2604.26219v1 Announce Type: cross Abstract: The security of open-source software repositories is increasingly threatened by next-gen software supply chain attacks. These attacks include multipha
arXiv:2604.26238v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has been widely adopted for scene reconstruction, where training inherently constitutes a highly coupled and non-convex opt
arXiv:2604.26285v1 Announce Type: new Abstract: Face liveness detection has been extensively studied using RGB cameras, achieving strong performance under controlled conditions but often failing to ge
The ultimate plan to live forever is a brand new body. This subscriber-only eBook explores R3 Bio, a small startup that has pitched a startling and ethically charged vision for “brainless clones” to s
arXiv:2604.26881v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) models offer high capacity with efficient inference cost by activating a small subset of expert models per input. However, de
arXiv:2509.20265v3 Announce Type: replace-cross Abstract: In this paper, we show that Simple Preference Optimization (SimPO) can be derived as Maximum Entropy Reinforcement Learning, providing a theor
arXiv:2604.26186v1 Announce Type: new Abstract: Fashion AI systems routinely encode the aesthetic logic of specific houses, editors, and historical moments without disclosing it. We present FASH-iCNN,
arXiv:2604.26488v1 Announce Type: new Abstract: One of the most exciting applications of vision models involve pixel-level reasoning. Despite the abundance of vision foundation models, we still lack r
arXiv:2604.26324v1 Announce Type: new Abstract: Exploiting deep learning in medical imaging faces critical challenges, including strict privacy constraints, heterogeneous imaging devices with varying
arXiv:2604.26160v1 Announce Type: cross Abstract: Nonlinear Mixed Effects models (NLME) models are widely used in pharmacometrics and related fields to analyze hierarchical and longitudinal data. Howe
arXiv:2604.26190v1 Announce Type: cross Abstract: We introduce Flashback, a reversible string decomposition that repeatedly peels the maximal leading and trailing character runs from a sentinel-wrappe
arXiv:2602.13780v2 Announce Type: replace Abstract: Remote sensing (RS) change detection is essential for interpreting surface dynamics. Semantic change detection (SCD) further enables pixel-level und
arXiv:2604.26671v1 Announce Type: cross Abstract: Trust in clinical artificial intelligence (AI) cannot be reduced to model accuracy, fluency of generation, or overall positive user impression. In med
arXiv:2604.26084v1 Announce Type: cross Abstract: Accurate fruit maturity identification is essential for determining harvest timing, as incorrect assessment directly affects yield and post-harvest qu
arXiv:2604.26598v1 Announce Type: new Abstract: Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to security and surveillance. Such applications rely o