Search: “research”

arXiv:2504.17247v3 Announce Type: replace Abstract: Deep learning-based antimicrobial peptide (AMP) discovery faces critical challenges such as limited controllability, lack of representations that ef

OpenRouter is a platform that provides API access to multiple large language models and AI services through a unified interface. Sakana AI's Fugu-Ultra appears to be an AI model available through Open

arXiv:2606.25462v1 Announce Type: new Abstract: Abstractive text summarization is the technique of generating a short and concise summary comprising the salient ideas of a source text without making a

🎉 Our paper MJEPA has been accepted at #ECCV2026 !! Huge thanks to my awesome collaborators @AdrienBardes, @michaelrabbat , Sumit Chopra @mattmucklm and Nicolas Ballas Paper: https://arxiv.org/abs/260

arXiv:2606.25935v1 Announce Type: new Abstract: Was this person ever at that place, and if so, when? Answering such questions from noisy, multilingual historical documents is the central challenge of

arXiv:2507.01695v3 Announce Type: replace Abstract: Deep neural networks (DNNs) are widely used for their ability to model complex patterns across domains such as computer vision, speech recognition,

arXiv:2606.15053v2 Announce Type: replace Abstract: Surrogate models are central to scientific machine learning, where they enable fast prediction, simulation, inference, and control for complex physi

arXiv:2606.24938v1 Announce Type: cross Abstract: Tensor decomposition of donor imes cell-type imes gene single-cell data recovers multicellular programs: coordinated axes of inter-individual transcri

arXiv:2606.26021v1 Announce Type: cross Abstract: Tabular foundation models are commonly assumed to present limited privacy concerns as they are often pre-trained on large collections of synthetic dat

【採用情報】プロダクトチームのセールス、マーケティングのポジションをオープンしました🐟️ Product Sales & Account Executive：国内外のエンタープライズ顧客を開拓し、プロダクト収益を牽引するポジションです https://sakana.ai/careers/business-role-product-sales-account-executive/ Product M

arXiv:2603.01470v3 Announce Type: replace Abstract: We consider the optimization problem of an expensive-to-evaluate black-box function, in which we can obtain noisy function values in parallel. For t

arXiv:2606.25480v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV) can provide on-demand, high-capacity connectivity in disaster and normal situation. However, it faces a challenge of cur

arXiv:2606.25770v1 Announce Type: cross Abstract: Data scarcity is a major bottleneck in medical Multiple Instance Learning (MIL), especially for rare diseases or expensive modalities. We introduce a

arXiv:2606.24932v1 Announce Type: cross Abstract: Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this pap

arXiv:2511.05933v2 Announce Type: replace Abstract: Reinforcement learning (RL) is often credited with improving language model reasoning at the expense of knowledge. We challenge this narrative by sh

Artificial intelligence is rapidly reshaping retail, but not in the ways consumers might immediately notice. The biggest transformation may not be flashy virtual try-ons or chatbot shopping assistants

arXiv:2606.24985v1 Announce Type: new Abstract: Personalization in wearable-based stress detection remains challenging due to substantial inter-individual variability in physiological and behavioral r

arXiv:2606.24892v1 Announce Type: cross Abstract: Peer review is central to scientific quality control, yet it can undervalue papers that later achieve substantial citation impact. While frontier larg

arXiv:2606.25318v1 Announce Type: new Abstract: In this paper, we propose a discrete roto-reflection group equivariant vision transformer with convolutional attention. Roto-reflection equivariant netw

arXiv:2606.25568v1 Announce Type: new Abstract: Recent LLMs demonstrate strong mathematical reasoning capabilities, but existing gains rely heavily on English-centric training resources and benchmarks

arXiv:2201.01973v3 Announce Type: replace-cross Abstract: The problem of linear predictions has been extensively studied for the past century under pretty generalized frameworks. Recent advances in th

arXiv:2407.07239v3 Announce Type: replace Abstract: Linear recurrent neural networks, such as State Space Models (SSMs) and Linear Recurrent Units (LRUs), have recently shown state-of-the-art performa

arXiv:2606.25784v1 Announce Type: new Abstract: Data augmentation is known to improve generalization of deep visual models. Recent methods favor mixup strategies that generate interpolated samples to

arXiv:2606.24987v1 Announce Type: cross Abstract: Optimal transport (OT) has become a central language for comparing probability measures, but exact balanced OT is often both too rigid for data with m

arXiv:2606.25006v1 Announce Type: new Abstract: Target-specific peptide design requires sequence and structure co-design under full atom geometric constraints. Latent generative frameworks offer an ef

arXiv:2509.22193v2 Announce Type: replace Abstract: Distilling reasoning traces from strong teacher models has become the standard recipe for building capable small language models. Yet reasoning trac

arXiv:2603.20452v2 Announce Type: replace Abstract: Longitudinal neuroimaging is essential for modeling disease progression in Alzheimer's disease (AD), yet irregular sampling and missing visits pose

arXiv:2606.25959v1 Announce Type: cross Abstract: Conventional audio pipelines typically treat speech enhancement (SE) and automatic gain control (AGC) as discrete modules, which often limits overall

arXiv:2601.23147v2 Announce Type: replace Abstract: The integrity of time in distributed Internet of Things (IoT) devices is crucial for reliable operation in energy cyber-physical systems, such as sm

arXiv:2606.25348v1 Announce Type: new Abstract: Tactile sensing is essential for humanoid robots to achieve safe physical interaction, dexterous manipulation, and truly human-like responsiveness. Howe

arXiv:2606.24933v1 Announce Type: cross Abstract: Recent advances in quantum machine learning have motivated efficient models for sequential data processing. In this paper, we propose Self-Modulating

arXiv:2606.25232v1 Announce Type: cross Abstract: Ordered bottlenecks aim to provide utility at flexible budgets by assigning coarse information to early tokens and task-relevant detail to later ones.

arXiv:2606.24935v1 Announce Type: new Abstract: Thin-structure segmentation--power lines, cracks, lane markings at 1-3 pixel width--requires preserving connectivity that standard representations precl

arXiv:2606.25818v1 Announce Type: new Abstract: Shift-variant image degradation is frequently encountered in practical imaging systems where the point spread function (PSF) varies across the image fie

arXiv:2602.17104v2 Announce Type: replace-cross Abstract: We propose a streamlined spectral algorithm for community detection in the two-community stochastic block model (SBM) under constant edge dens

arXiv:2606.25777v1 Announce Type: cross Abstract: We initiate a resource-aware theory of extit{language generation in the limit} under the minimal constraint of space efficiency. In our framework, a l

arXiv:2606.25495v1 Announce Type: new Abstract: Saudi Telecom Company (STC) is among the most popular companies in Saudi Arabia, with many customers. Yet, there is still a big room for improvement in

arXiv:2312.00206v4 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has recently enabled real-time rendering of unbounded 3D scenes for novel view synthesis. However, this technique requi

arXiv:2512.05354v2 Announce Type: replace Abstract: The rise of 3D Gaussian Splatting has revolutionized photorealistic 3D asset creation, yet a critical gap remains for their interactive refinement a

arXiv:2606.25269v1 Announce Type: cross Abstract: As black-box models become foundational to modern research, ensuring their stability is paramount for the realization of trustworthy artificial intell

arXiv:2601.17917v3 Announce Type: replace-cross Abstract: Diffusion Large Language Models (dLLMs) offer a compelling paradigm for natural language generation, leveraging parallel decoding and bidirect

arXiv:2310.09149v3 Announce Type: replace-cross Abstract: We study the approximation of probability measures in the Wasserstein-p distance by structured classes of approximators, motivated by applicat

arXiv:2606.25234v1 Announce Type: new Abstract: What is the geometry of a visual percept? The most widely used protocols for decomposing neural network representations into interpretable parts treat c

arXiv:2511.22411v2 Announce Type: replace Abstract: 3D head stylization enables expressive reimagining of human faces for creative visual experiences in digital media. Existing 3D-aware methods often

arXiv:2602.22188v2 Announce Type: replace Abstract: Modelling rock-fluid interaction requires solving a set of partial differential equations (PDEs) to predict the flow behaviour and the reactions of

arXiv:2512.05337v2 Announce Type: replace-cross Abstract: We consider the problem of learning the parameters of a N-dimensional stochastic linear dynamics under both full and partial observations from