Drifting Fields are not Conservative
arXiv:2604.06333v1 Announce Type: new Abstract: Drifting models generate high-quality samples in a single forward pass by transporting generated samples toward the data distribution using a vector val
Knowledge catalogue
arXiv:2604.06333v1 Announce Type: new Abstract: Drifting models generate high-quality samples in a single forward pass by transporting generated samples toward the data distribution using a vector val
arXiv:2601.07994v4 Announce Type: replace Abstract: Large Language Models (LLMs) increasingly operate over long-form dialogues with frequent topic shifts. While recent LLMs support extended context wi
arXiv:2604.08543v1 Announce Type: new Abstract: Event cameras offer multiple advantages in monocular egocentric 3D human pose estimation from head-mounted devices, such as millisecond temporal resolut
arXiv:2510.05261v2 Announce Type: replace Abstract: The Lipschitz constant is a key measure for certifying the robustness of neural networks to input perturbations. However, computing the exact consta
arXiv:2507.06949v3 Announce Type: replace Abstract: Ancient populations inhabited and transformed neotropical forests, yet the spatial extent of their ecological influence remains underexplored at hig
arXiv:2604.08063v1 Announce Type: new Abstract: Reconstructing visual stimuli from non-invasive electroencephalography (EEG) remains challenging due to its low spatial resolution and high noise, parti
arXiv:2604.07239v1 Announce Type: cross Abstract: While Learned Data Compression (LDC) has achieved superior compression ratios, balancing precise probability modeling with system efficiency remains c
arXiv:2505.15960v3 Announce Type: replace Abstract: Process Reward Models (PRMs) have emerged as a promising approach for improving LLM reasoning capabilities by providing process supervision over rea
arXiv:2604.08052v1 Announce Type: new Abstract: Linguistic steganography involves embedding secret messages within seemingly innocuous texts to enable covert communication. Provable security, which is
arXiv:2604.06515v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) allows scaling of language and vision models efficiently by activating only a small subset of experts per input. While
arXiv:2604.06893v1 Announce Type: cross Abstract: Deep convolutional neural networks achieve remarkable performance by exhaustively processing dense spatial feature maps, yet this brute-force strategy
arXiv:2604.08456v1 Announce Type: cross Abstract: Despite rapid progress, pretrained vision-language models still struggle when answers depend on tiny visual details or on combining clues spread acros
European leaders are learning there is no point trying to appease Trump. He has an insatiable appetite for flattery no matter how transparently false. Like any bully, he sees weakness as an invitation
arXiv:2604.07320v1 Announce Type: cross Abstract: Low-resource languages pose a challenge for machine translation with large language models (LLMs), which require large amounts of training data. One p
arXiv:2604.06942v1 Announce Type: cross Abstract: Ensuring ciphertext indistinguishability is fundamental to cryptographic security, but empirically validating this property in real implementations an
arXiv:2604.06172v1 Announce Type: cross Abstract: Cold-start cross-domain recommender (CDR) systems predict a user's preferences in a target domain using only their source-domain behavior, yet existin
arXiv:2603.11703v2 Announce Type: replace Abstract: We introduce EvoFlows, a variable-length protein sequence-to-sequence modeling approach designed for protein engineering. Existing protein language
arXiv:2604.06208v1 Announce Type: cross Abstract: A significant amount of data held in Oncology Electronic Medical Records (EMRs) is contained in unstructured provider notes -- including but not limit
arXiv:2604.06732v1 Announce Type: new Abstract: Recent developments in hardware, such as photonic integrated circuits and optical devices, are driving demand for research on constructing machine learn
arXiv:2511.08409v4 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) frequently suffer from unfaithfulness, generating reasoning chains that drift from visual evidence or contr
arXiv:2604.07350v1 Announce Type: cross Abstract: Large Chunk Test-Time Training (LaCT) has shown strong performance on long-context 3D reconstruction, but its fully plastic inference-time updates rem
arXiv:2601.21708v2 Announce Type: replace Abstract: Large language models (LLMs) excel across many tasks, yet inference is still dominated by strictly token-by-token autoregression. Existing accelerat
arXiv:2604.06723v1 Announce Type: cross Abstract: In today's AI-assisted software engineering landscape, developers increasingly depend on LLMs that are highly capable, yet inherently imperfect. The t
arXiv:2408.09369v3 Announce Type: replace-cross Abstract: As the rapid development of computer vision and the emergence of powerful network backbones and architectures, the application of deep learnin
arXiv:2604.08275v1 Announce Type: new Abstract: Metaphor pervades everyday language, allowing speakers to express abstract concepts via concrete domains. While prior work has studied metaphors cogniti
arXiv:2604.08485v1 Announce Type: cross Abstract: The purpose of this paper is two-fold. First we show that Kim's building-up construction of binary self-dual codes is equivalent to Chinburg-Zhang's H
arXiv:2512.21602v2 Announce Type: replace-cross Abstract: Millions of patients pass through emergency departments and intensive care units each year, where clinicians must make high-stakes decisions u
arXiv:2411.18084v2 Announce Type: replace-cross Abstract: Mobile apps are essential in daily life but frequently employ deceptive patterns, such as visual emphasis or linguistic nudging, to manipulate
arXiv:2604.06262v1 Announce Type: cross Abstract: Contextual clinical reasoning demands robust inference grounded in complex, heterogeneous clinical records. While state-of-the-art fine-tuning, in-con
arXiv:2604.06448v1 Announce Type: cross Abstract: Prime Video regularly conducts load tests to simulate the viewer traffic spikes seen during live events such as Thursday Night Football as well as vid
arXiv:2604.08322v1 Announce Type: new Abstract: Fundus imaging such as CFP, OCT and UWF is crucial for the early detection of retinal anomalies and diseases. Fundus image understanding, due to its kno
arXiv:2604.07323v1 Announce Type: cross Abstract: In this paper, we derive rates of convergence in the high-dimensional central limit theorem for Polyak-Ruppert averaged iterates generated by the asyn
arXiv:2604.07728v1 Announce Type: new Abstract: High-fidelity interactive digital assets are essential for embodied intelligence and robotic interaction, yet articulated objects remain challenging to
arXiv:2604.07928v1 Announce Type: new Abstract: While AI-based numerical weather prediction (NWP) enables rapid forecasting, generating high-resolution outputs remains computationally demanding due to
arXiv:2604.06989v1 Announce Type: cross Abstract: We present the first generative approach to photomosaic creation. Traditional photomosaic methods rely on a large number of tile images and color-base
I was unable to retrieve the specific Reddit post at the provided URL through search results. The search did not surface the content of that particular thread (reddit.com/r/MachineLearning/comments...
Great to see this on X. This is something I created during my PhD time 20 years ago. This is a healing grid by Japanese artist Ryota Kanai. If you stare at the center, the irregularities start to heal
arXiv:2604.08301v1 Announce Type: new Abstract: The performance of visual anomaly inspection in industrial quality control is often constrained by the scarcity of real anomalous samples. Consequently,
arXiv:2604.08046v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) significantly enhances Large Language Models (LLMs) by providing access to external knowledge. However, current res
arXiv:2604.06195v1 Announce Type: cross Abstract: Large language models often produce unsupported claims. We frame this as a misclassification error at the output boundary, where internally generated
arXiv:2604.07937v1 Announce Type: new Abstract: Cross-document relation extraction (RE) aims to identify relations between the head and tail entities located in different documents. Existing approache
Nous Research draws its name from the ancient Greek concept of *nous* — the faculty of directly perceiving truth, reason, and divine reality — while its flagship model series, **Hermes**, is named ...
arXiv:2504.13015v3 Announce Type: replace Abstract: Deep learning-based point cloud modeling has been widely investigated as an indispensable component of general shape analysis. Recently, transformer
arXiv:2511.09170v2 Announce Type: replace Abstract: This article presents HOTFLoc++, an end-to-end hierarchical framework for LiDAR place recognition, re-ranking, and 6-DoF metric localisation in fore
arXiv:2604.07233v1 Announce Type: new Abstract: We provide a computational complexity lens to understand the power of machine learning models, particularly their ability to model complex systems. Mach
arXiv:2604.08435v1 Announce Type: new Abstract: It remains challenging to assess driver fatigue from untrimmed videos under constrained computational budgets, due to the difficulty of modeling long-ra
arXiv:2604.07357v1 Announce Type: new Abstract: Recognizing emotions from speech using machine learning has become an active research area due to its importance in building human-centered applications
arXiv:2604.06481v1 Announce Type: cross Abstract: This study introduces a hybrid deep learning model for intrusion detection in Industrial IoT (IIoT) systems, combining ResNet-1D, BiGRU, and Multi-Hea
arXiv:2604.07795v1 Announce Type: new Abstract: Recent generative models can create visually plausible 3D representations of objects. However, the generation process often allows for implicit control
arXiv:2405.03420v2 Announce Type: cross Abstract: This paper introduces a novel approach to enhance the performance of pre-trained neural networks in medical image segmentation using gradient-based Ne
arXiv:2601.02627v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are becoming useful in many domains due to their impressive abilities that arise from large training datasets and
arXiv:2402.08267v3 Announce Type: replace Abstract: Image coding for machines (ICM) aims to compress images for machine analysis using recognition models rather than human vision. Hence, in ICM, it is
arXiv:2604.06495v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are widely used in mechanistic interpretability to project LLM activations onto sparse latent spaces. However, sparsity alo
arXiv:2604.07958v1 Announce Type: new Abstract: Current video editing models often rely on expensive paired video data, which limits their practical scalability. In essence, most video editing tasks c
arXiv:2604.06356v1 Announce Type: cross Abstract: In-Context Learning (ICL) has been extensively studied in text-only Language Models, but remains largely unexplored in the speech domain. Here, we inv
In the middle of a historic mission back to the Moon, this Administration is proposing to a 47% cut to NASA science and a 23% cut to NASA’s budget overall. Last week’s launch showed our country and wo
arXiv:2604.06263v1 Announce Type: cross Abstract: Generative advertising in large language model (LLM) responses requires optimizing sponsorship configurations under two strict constraints: the strate
arXiv:2604.06485v1 Announce Type: cross Abstract: 'Best-of-N' selection is a popular inference-time scaling method for code generation using Large Language Models (LLMs). However, to reliably identify
arXiv:2507.09309v4 Announce Type: replace Abstract: Optimal path planning in nonconvex free spaces poses substantial computational challenges. A common approach formulates such problems as mixed-integ
arXiv:2602.22545v2 Announce Type: replace Abstract: Tau positron emission tomography (tau-PET) is an important in vivo biomarker of Alzheimer's disease, but its cost, limited availability, and acquisi