Knowledge catalogue
arXiv:2604.12434v1 Announce Type: cross Abstract: In-context learning enables transformers to adapt to new tasks from a few examples at inference time, while grokking highlights that this generalizati
arXiv:2603.10559v2 Announce Type: replace Abstract: This paper studies cross-market return predictability through a machine learning framework that preserves economic structure. Exploiting the non-ove
arXiv:2407.17182v4 Announce Type: replace Abstract: In this work, we consider the non-invasive medical imaging modality of Electrical Impedance Tomography (EIT), where the goal is to recover the condu
arXiv:2604.12211v1 Announce Type: new Abstract: Ollivier-Ricci curvature (ORC), defined via the Wasserstein distance that captures rich geometric information, has received growing attention in both th
arXiv:2603.18640v3 Announce Type: replace-cross Abstract: The No-U-Turn Sampler (NUTS) is the computational workhorse of modern Bayesian software libraries, yet its qualitative and quantitative conver
arXiv:2604.11927v1 Announce Type: new Abstract: Digital breast tomosynthesis (DBT) is now the standard of care for breast cancer screening in the USA. Accurate segmentation of fibroglandular tissue in
arXiv:2405.04108v2 Announce Type: replace-cross Abstract: Recent booming development of Generative Artificial Intelligence (GenAI) has facilitated model commercialization to reinforce the model perfor
arXiv:2604.12989v1 Announce Type: new Abstract: Speculative decoding accelerates autoregressive language models by using a lightweight drafter to propose multiple future tokens, which the target model
arXiv:2604.12792v1 Announce Type: new Abstract: In tendon driven continuum manipulators (TDCMs), reconfiguring the tendon routing enables tailored spatial deformation of the backbone. This work presen
arXiv:2501.16154v4 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown impressive multilingual capabilities through pretraining on diverse corpora. Although these models sho
arXiv:2604.12497v1 Announce Type: new Abstract: Large language models (LLMs) can generate survey responses at low cost, but their reliability varies substantially across questions and is unknown befor
arXiv:2603.18104v3 Announce Type: replace Abstract: Prevailing AI training infrastructure assumes reverse-mode automatic differentiation over IEEE-754 arithmetic. The memory overhead of training relat
arXiv:2604.12647v1 Announce Type: cross Abstract: Automated respiratory audio analysis promises scalable, non-invasive disease screening, yet progress is limited by scarce labeled data and costly expe
arXiv:2602.04204v2 Announce Type: replace Abstract: Human trajectory forecasting requires capturing the multimodal nature of pedestrian behavior. However, existing approaches suffer from prior misalig
arXiv:2604.06812v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated impressive capabilities in long-form generation, yet their application is hindered by the hallucinati
arXiv:2604.12811v1 Announce Type: cross Abstract: Dense Associative Memory (DAM) generalizes Hopfield networks through higher-order interactions and achieves storage capacity that scales as O(N^{n-1})
ARC-AGI-3 is a new benchmark iteration designed so that any intelligent human applying genuine effort should achieve greater than 90% accuracy, maintaining the benchmark's core principle that tasks mu
This r/MachineLearning discussion examines a growing concern in the AI and gaming community: that certain video game 'simulators' may be deliberately designed — or repurposed — to harvest player actio
arXiv:2604.12274v1 Announce Type: new Abstract: A class of planar bipedal robots with unique mechanical properties has been proposed, where all links are balanced around the hip joint, preventing natu
arXiv:2604.12480v1 Announce Type: cross Abstract: In Gaussian model-based multichannel audio source separation, the likelihood of observed mixtures of source signals is parametrized by source spectral
arXiv:2507.11081v3 Announce Type: replace-cross Abstract: Ground penetrating radar (GPR) has become a rapid and non-destructive solution for road subsurface distress (RSD) detection. However, recogniz
The question is no longer whether to deploy AI — it’s why so many deployments stall before delivering returns. The answer usually comes down to a lack of trusted data foundation. As research from Qlik
arXiv:2602.18899v3 Announce Type: replace-cross Abstract: Self-supervised speech models (S3Ms) are known to encode rich phonetic information, yet how this information is structured remains underexplor
arXiv:2604.12898v1 Announce Type: new Abstract: Large Language Model-based Hyper Heuristic (LHH) has recently emerged as an efficient way for automatic heuristic design. However, most existing LHHs ju
arXiv:2604.12210v1 Announce Type: new Abstract: Simulating Standardized Patients with cognitive impairment offers a scalable and ethical solution for clinical training. However, existing methods rely
arXiv:2604.12307v1 Announce Type: new Abstract: The proliferation of highly realistic AI-Generated Image (AIGI) has necessitated the development of practical detection methods. While current AIGI dete
arXiv:2604.12966v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) perform well on many vision-language tasks but often struggle with vision-centric problems that require fine-gr
arXiv:2604.12660v1 Announce Type: new Abstract: In nonmonotonic reasoning from conditional belief bases, an inference operator satisfying syntax splitting postulates allows for taking only the relevan
arXiv:2603.28325v3 Announce Type: replace-cross Abstract: Biomedical knowledge resources often either preserve evidence as unstructured text or compress it into flat triples that omit study design, pr
The practice of privacy-led user experience (UX) is a design philosophy that treats transparency around data collection and usage as an integral part of the customer relationship. An undertapped oppor
arXiv:2604.12491v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed for tabular question answering, yet calibration on structured data is largely unstudied. This pap
arXiv:2604.11915v1 Announce Type: cross Abstract: Modern machine learning methods have been proposed to detect life in extraterrestrial samples, drawing on their ability to distinguish biotic from abi
arXiv:2509.15406v2 Announce Type: replace Abstract: AI generative models leave implicit traces in their generated images, which are commonly referred to as model fingerprints and are exploited for sou
arXiv:2604.12305v1 Announce Type: cross Abstract: Pneumonia remains a leading cause of childhood mortality worldwide, with a heavy burden in low-resource settings such as Bangladesh where radiologist
arXiv:2604.12318v1 Announce Type: new Abstract: Existing cell instance segmentation pipelines typically combine deterministic predictions with post-processing, which imposes limited explicit constrain
arXiv:2604.12190v1 Announce Type: cross Abstract: Many malicious actors responsible for disseminating synthetic non-consensual intimate imagery (SNCII) operate within internet forums to exchange resou
arXiv:2604.13024v1 Announce Type: new Abstract: The explosive growth of system logs makes streaming compression essential, yet existing log anomaly detection (LAD) methods incur severe pre-processing
arXiv:2604.12767v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) suffer from substantial computational overhead due to the high redundancy in visual token sequences. Existing
arXiv:2604.13022v1 Announce Type: cross Abstract: The Energy Conserving Descent (ECD) algorithm was recently proposed (De Luca & Silverstein, 2022) as a global non-convex optimization method. Unlike g
arXiv:2604.11971v1 Announce Type: new Abstract: Epileptic seizure detection from EEG signals remains challenging due to the high dimensionality and nonlinear, potentially stochastic, dynamics of neura
arXiv:2601.11047v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations.
arXiv:2604.12777v1 Announce Type: cross Abstract: The human brain constructs emotional percepts not by processing facial expressions in isolation, but through a dynamic, hierarchical integration of se
arXiv:2604.12342v1 Announce Type: cross Abstract: Training models on a carefully chosen portion of data rather than the full dataset is now a standard preprocess for modern ML. From vision coreset sel
arXiv:2604.13028v1 Announce Type: new Abstract: Urban areas are increasingly vulnerable to thermal extremes driven by rapid urbanization and climate change. Traditionally, thermal extremes have been m
arXiv:2604.12036v1 Announce Type: cross Abstract: We resolve a long-standing open question, about the existence of a constant-factor approximation algorithm for the average-case extsc{Decision Tree} p
arXiv:2510.19644v2 Announce Type: replace Abstract: Retrieval-augmented generation has emerged as one of the most effective approaches for code completion enhancement, especially when repository-level
arXiv:2511.19820v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) often struggle with tasks that require fine-grained image understanding, such as scene-text recognition or docum
arXiv:2604.12551v1 Announce Type: new Abstract: Vision-language models have been key to the development of open-vocabulary 2D semantic segmentation. Lifting these models from 2D images to 3D scenes, h
arXiv:2604.12364v1 Announce Type: cross Abstract: Future AI-based studies in particle physics will likely start from a foundation model to accelerate training and enhance sensitivity. As a step toward
From inside a money-laundering center in Cambodia, an employee opens a popular Vietnamese banking app on his phone. The app asks him to upload a photo associated with the account, so he clicks on a pi
arXiv:2604.12180v1 Announce Type: cross Abstract: Tropical cyclones (TCs) rank among the most destructive natural hazards, yet their forecasting faces fundamental trade-offs: numerical weather predict
arXiv:2602.15355v3 Announce Type: replace Abstract: The emergence of 3D Gaussian Splatting has fundamentally redefined the capabilities of photorealistic neural rendering by enabling high-throughput s
arXiv:2506.23104v2 Announce Type: replace Abstract: Interactive segmentation (IS) allows users to iteratively refine object boundaries with minimal cues, such as positive and negative clicks. While th
arXiv:2604.12260v1 Announce Type: new Abstract: We study decentralized learning over networks where data are distributed across nodes without a central coordinator. Random walk learning is a token-bas
arXiv:2603.25414v2 Announce Type: replace-cross Abstract: A prevailing assumption in machine learning is that model correctness must be enforced after the fact. We observe that the properties determin
arXiv:2604.12424v1 Announce Type: cross Abstract: Multimodal Large Language Models frequently suffer from inference hallucinations, partially stemming from language priors dominating visual evidence.
arXiv:1803.08375v3 Announce Type: replace-cross Abstract: The Rectified Linear Unit (ReLU) is a foundational activation function in artficial neural networks. Recent literature frequently misattribute
arXiv:2604.12490v1 Announce Type: cross Abstract: Deepfakes are synthetic media that superimpose or generate someone's likeness on to pre-existing sound, images, or videos using deep learning methods.
arXiv:2604.12411v1 Announce Type: new Abstract: Segmentation models based on deep neural networks demonstrate strong generalization for medical image segmentation. However, they often exhibit overconf
arXiv:2604.12832v1 Announce Type: cross Abstract: Deep learning-based medical image segmentation typically relies on ground truth (GT) labels obtained through manual annotation, but these can be prone