Search: “models”

arXiv:2606.21973v1 Announce Type: new Abstract: Physiological signals such as EEG, ECG, and PPG are widely used in clinical monitoring. Recent self-supervised learning (SSL) methods offer an attractiv

arXiv:2606.23254v1 Announce Type: new Abstract: Visual text editing aims to precisely modify text in images and videos while preserving stylistic consistency and visual realism. Despite significant ad

arXiv:2606.20856v1 Announce Type: new Abstract: Multi-view surface reconstruction is a core problem in computer vision. One prominent line of work represents the surface implicitly as a signed distanc

arXiv:2507.03318v3 Announce Type: replace Abstract: Explainable artificial intelligence approaches accelerate drug discovery by improving molecular representation learning, identifying key molecular s

arXiv:2606.23477v1 Announce Type: cross Abstract: Over the past decade, deep neural networks (DNNs) have achieved remarkable success on complex machine-learning tasks, yet the theoretical foundations

arXiv:2606.21866v1 Announce Type: new Abstract: Co-design of legged robots with elastic elements is challenging due to the non-differentiability of contact dynamics and mechanism engagement. This pape

arXiv:2606.20864v1 Announce Type: cross Abstract: Developing robust intrusion detection systems (IDS) for IoT environments requires large, labeled datasets capturing realistic traffic distributions ac

arXiv:2606.17055v2 Announce Type: replace Abstract: The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based

arXiv:2606.21189v1 Announce Type: new Abstract: Non-stationary partial differential equations (PDEs) arise throughout scientific computing, where the dominant frequency content and energy distribution

arXiv:2505.11579v3 Announce Type: replace-cross Abstract: As AI systems evolve from static tools to dynamic agents, traditional categorical governance frameworks -- based on fixed risk tiers, levels o

arXiv:2602.15136v2 Announce Type: replace-cross Abstract: We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achi

arXiv:2606.23503v1 Announce Type: new Abstract: Vision Transformers (ViT) dominate computer vision. However, their reliance on rigid patch projectors hinders transfer to Earth Observation (EO), where

arXiv:2606.22787v1 Announce Type: new Abstract: Current end-to-end multi-view 3D reconstruction methods achieve impressive results, but rely on a restrictive static assumption: the scenes is entire di

arXiv:2606.22371v1 Announce Type: cross Abstract: Recent generative video compression methods leverage powerful generative priors to achieve perceptually pleasing reconstructions. However, most existi

GLM-5.2 represents a significant advancement in open-source AI agent capabilities, marking a notable improvement over previous versions in terms of performance and functionality. The article from Inte

I have been trying Sakana Fugu Ultra-high and, first, it is incredibly slow: my typical coding tests (shaders, interactive scenes) take 30 minutes to run And the results are... fine. It does not match

🐡 Sakana Fugu リリース 🐡 マルチエージェントを指揮する、一つのモデル ブログ：https://sakana.ai/fugu-release/#Japanese 本日、Sakana AIは新しいプロダクト「Sakana Fugu」の提供を開始しました。Sakana Fuguは、最先端のモデル群からなるマルチエージェントシステム全体を、単一のモデルAPIとして提供します。 難しいタスク

Tried & liked it on http://archive.tw. Fugu Ultra pairs well as a advisor & planner with Composer 2.5. For scope/architecture, it’s on par with Fable orchestration. Advisor doesn’t slow the loop if th

Use Case 4: Computer Aided Design of Mechanical Iris Can an AI generate precise, functional mechanical designs? We tasked Fugu Ultra with creating a mechanical iris in CAD, similar to a camera apertur

this claim around creativity is too strong, IMHO. truly novel ideas from LLMs are surely rare but i don’t think that any math proves they are impossible. note that the objective function and the outpu

arXiv:2606.11390v1 Announce Type: new Abstract: Gaussian splatting methods have become increasingly popular for neural reconstruction of the real world. However, they are often limited in scale and re

arXiv:2606.12337v1 Announce Type: cross Abstract: Inverse problems governed by partial differential equations (PDEs) are central to computational mechanics and are commonly solved by adjoint-based opt

arXiv:2606.11793v1 Announce Type: cross Abstract: Uncertainty in the terrestrial carbon cycle remains a major constraint in climate projections, partly driven by the uncertainties affecting the land s

arXiv:2606.11238v1 Announce Type: cross Abstract: Ship finance is a data-intensive and document-heavy segment of asset-based lending, requiring the integration of financial, technical, contractual, an

arXiv:2606.12294v1 Announce Type: new Abstract: Automated image retrieval plays an increasingly critical role in modern forensic analysis, supporting investigative workflows that rely on efficient com

arXiv:2606.11711v1 Announce Type: new Abstract: Online learning with delayed feedback typically assumes that the learner can track all pending rounds until their feedback arrives. In practice, trackin

arXiv:2606.12281v1 Announce Type: cross Abstract: In Decentralized Training and Decentralized Execution (DTDE) for cooperative Multi-Agent Reinforcement Learning (MARL), action-advising-based knowledg

arXiv:2606.12352v1 Announce Type: cross Abstract: Multi-robot collaboration allows robots to efficiently take on a wide range of tasks, from moving a couch through a doorway to assembling structures o

arXiv:2603.09555v2 Announce Type: replace-cross Abstract: High-throughput Mamba-2 inference is usually tied to fused CUDA and Triton kernels, limiting portability across accelerator backends. We show

arXiv:2606.11925v1 Announce Type: new Abstract: Sign language translation (SLT) converts sign language video into spoken language text and holds significant promise for improving accessibility and ena

arXiv:2601.11670v3 Announce Type: replace-cross Abstract: Pseudo-label selection in semi-supervised learning is commonly driven by maximum-confidence thresholds, yet confidence alone can be unreliable

arXiv:2606.11651v1 Announce Type: new Abstract: Synthetic random heteropolymers (RHPs), consisting of a predefined set of monomers, offer an approach toward the design of protein-like materials. These

arXiv:2602.18291v2 Announce Type: replace Abstract: Online Multi-Agent Reinforcement Learning (MARL) is a prominent framework for efficient agent coordination. Crucially, enhancing policy expressivene

arXiv:2509.20241v2 Announce Type: replace Abstract: As AI inference scales to billions of queries, estimates of per-query energy use are increasingly important for capacity planning, efficiency interv

arXiv:2606.12032v1 Announce Type: new Abstract: Contemporary AI alignment research treats self-preservation as an instrumental nuisance to be suppressed by external mechanisms. We argue the framing is

arXiv:2606.11620v1 Announce Type: cross Abstract: Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approxi

arXiv:2606.11828v1 Announce Type: cross Abstract: Audio watermarking aims to embed identifiable information into audio while remaining imperceptible. Existing methods adopt high-fidelity, low-energy d

arXiv:2606.12070v1 Announce Type: new Abstract: State space projections and decompositions have emerged as powerful tools to tackle the curse of dimensionality in high-dimensional, multi-robot motion

arXiv:2606.12012v1 Announce Type: new Abstract: While diffusion-based virtual try-on has achieved impressive visual realism, most methods treat the task as 2D inpainting, prioritizing texture preserva

arXiv:2502.14894v5 Announce Type: replace-cross Abstract: Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with significant public health impacts, yet large-scale m

arXiv:2606.12303v1 Announce Type: new Abstract: Multimodal image fusion aims to integrate complementary information from different modalities into a fused image that preserves rich local details while

arXiv:2606.12200v1 Announce Type: cross Abstract: We study policy representation learning from unlabeled multi-policy behavioral data. Each episode is generated by a fixed policy, but policy labels ar

arXiv:2606.11287v1 Announce Type: cross Abstract: Skin cancer is among the most prevalent malignancies worldwiAdbe satnradcitts early detection is essential for improving patient survival and reducing

arXiv:2606.11675v1 Announce Type: new Abstract: Diagnosing pulmonary diseases requires integrating heterogeneous evidence amid phenotypic variability and cross-disease overlap. Although large language

arXiv:2606.11251v1 Announce Type: new Abstract: Many multivariate dynamical systems are observed only through trajectories, leaving the mechanisms governing their joint dynamics hidden. Existing appro

arXiv:2606.11645v1 Announce Type: new Abstract: Micro-gesture analysis attracts increasing attention for inferring spontaneous emotion from subtle body movements. Micro-gesture online recognition, whi