Knowledge catalogue
arXiv:2608.02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and inco
arXiv:2507.21449v2 Announce Type: replace-cross Abstract: Degeneracy is an inherent feature of the loss landscape of neural networks, but it is not well understood how stochastic gradient MCMC (SGMCMC
arXiv:2608.02100v1 Announce Type: cross Abstract: As AI increasingly participates in human decision making, understanding how decision-making authority is distributed between humans and AI has become
arXiv:2608.01104v1 Announce Type: new Abstract: Whole slide image (WSI) classification is an evidence-driven task, where diagnostic cues are often sparse, spatially organized, and class-dependent. Exi
arXiv:2608.00084v1 Announce Type: new Abstract: We present PixCell, a neurosymbolic system in which multimodal agents convert a visually presented photonic component into a parametric program over a s
arXiv:2602.10719v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) driving augments end-to-end (E2E) planning with language-enabled visual backbones, yet it remains unclear how vis
arXiv:2603.28067v2 Announce Type: replace Abstract: Digital testing has emerged as a key paradigm for the development and verification of autonomous maritime navigation systems, yet the availability o
arXiv:2603.03320v2 Announce Type: replace Abstract: Effective communication often relies on aligning a message with an audience's narrative and worldview. Narrative shift involves transforming text to
arXiv:2608.01202v1 Announce Type: new Abstract: Fruit ripeness prediction (FRP) is a classification-based agricultural computer vision task that has attracted much attention, thanks to its wide-rangin
arXiv:2608.01007v1 Announce Type: new Abstract: Dual-target drug design aims to generate 3D molecules that can simultaneously interact with two target proteins, offering a promising route for discover
arXiv:2606.17020v2 Announce Type: replace Abstract: Remote sensing vision-language models have advanced Earth observation, but available large-scale vision-language resources remain RGB-centered, leav
Editor's Note: Our Future Mode series will give businesses insight into how Chrome Enterprise is approaching AI in the browser. Stay tuned for more blogs in this series.Future Mode Part 2: The foundat
arXiv:2608.01726v1 Announce Type: new Abstract: 3D Gaussian Splatting has achieved remarkable success in photorealistic and efficient rendering, leading to a rapid increase in 3D assets represented by
arXiv:2608.00932v1 Announce Type: new Abstract: The integration of artificial intelligence into medical question-answering systems has advanced rapidly; however, research remains predominantly focused
arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev
arXiv:2608.01492v1 Announce Type: new Abstract: Selecting a complete 3D object from a reconstructed scene with minimal user effort is essential for practical scene editing and embodied interaction. Ex
arXiv:2608.02378v1 Announce Type: new Abstract: Private inference protects both user inputs and server models during neural network inference, but existing solutions remain too slow for practical depl
arXiv:2608.00829v1 Announce Type: new Abstract: We present an autonomous robotic portrait-generation system combining real-time face detection, AI-based sketch generation, and robotic drawing. The sys
arXiv:2608.01552v1 Announce Type: cross Abstract: Quadratic Gradient (QG) is a Newton-type optimization framework that bridges first-order gradient descent and second-order optimization by incorporati
NVIDIA Alpamayo 2 Super is a publicly available 34‑billion‑parameter vision–language–action model that merges a 32‑B Cosmos 3 Super Reasoner with a 2‑B action‑expert diffusion network. It produces uni
arXiv:2608.00716v1 Announce Type: new Abstract: Robust detection of generated images is critical to counter the misuse of generative models. Existing methods primarily depend on learning from human-an
arXiv:2608.01686v1 Announce Type: new Abstract: In recent years, generative AI has attracted significant public attention, and its use has been rapidly expanding across a wide range of domains. From c
arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn
arXiv:2608.00156v1 Announce Type: cross Abstract: The push for broader coverage in future cellular networks depends on reliable service, yet this is increasingly harder to do as we encounter more inst
arXiv:2608.00776v1 Announce Type: new Abstract: Traditional reaction yield prediction is constrained by 1D quantum descriptors that lack explicit spatial information. To address this gap, a dual-modal
arXiv:2608.02236v1 Announce Type: new Abstract: Zero-shot skeleton-based action recognition (ZSAR) aims to recognize unseen action categories by aligning skeleton features with textual semantics. Howe
arXiv:2608.01410v1 Announce Type: cross Abstract: General-purpose humanoid trackers can execute diverse references, but their zero-shot coverage depends on large embodied corpora that are costly to ex
arXiv:2608.00877v1 Announce Type: new Abstract: Remote-sensing multimodal large language models (MLLMs) often assert facts that imagery cannot establish, such as a facility's identity or function. Coo
arXiv:2608.01896v1 Announce Type: new Abstract: Existing generative models for earth observation (EO) predominantly rely on fine-tuning natural image priors, which limits their scalability and introdu
arXiv:2608.02315v1 Announce Type: new Abstract: Geospatial foundation models aim to learn representations that transfer across regions and sensors, yet evaluating them on specific tasks requires large
arXiv:2602.01893v2 Announce Type: replace-cross Abstract: We present a geometric framework for analysing multi-head attention in large language models (LLMs). Without altering the mechanism, we view s
arXiv:2603.07564v2 Announce Type: replace Abstract: Satellite video object tracking (SVOT) remains fundamentally challenging due to texture scarcity, arbitrary rotation, aspect ratio changes, and seve
arXiv:2608.00663v1 Announce Type: new Abstract: Audio-driven emotional talking face generation aims to synthesize realistic videos with expressive facial dynamics. However, existing methods struggle t
arXiv:2608.02064v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) account for a large fraction of Transformer parameters, yet their hidden width is usually constant across depth. We ask w
arXiv:2608.02068v1 Announce Type: new Abstract: Monocular depth foundation models, benefiting from large-scale synthetic training data, have demonstrated strong generalization. However, they often hal
arXiv:2603.23179v2 Announce Type: replace Abstract: Diffusion models provide powerful priors for 2D image completion, but these priors are learned on bounded planar images and do not transfer directly
I would love some feedback on this work in progress. Create, dialog with, mash up, and evolve spirit guides based on real concepts spanning psychological, philosophical, and religious origins. Honestl
Given today, it is surprising how daring Microsoft & Google were initially with AI. Microsoft released GPT-4 before OpenAI, didn't back down after Sydney & got Copilot to market quickly (the 1st profe
arXiv:2608.02366v1 Announce Type: new Abstract: Multivariate time series imputation is fundamental to downstream analysis, yet modeling inter-variable dependencies with incomplete observations remains
arXiv:2608.02353v1 Announce Type: new Abstract: Recent advances in agentic workflow optimization automate workflow design through task-specific workflow search or input-conditioned architecture select
arXiv:2608.02322v1 Announce Type: new Abstract: Accurate and efficient reconstruction of cloud-contaminated and noise-corrupted NDVI time series remains a challenge in remote sensing. Deep learning pr
arXiv:2509.22910v2 Announce Type: replace Abstract: Given that Visual SLAM relies on appearance cues for localization and scene understanding, texture-less or visually degraded environments (e.g., pla
arXiv:2603.13418v2 Announce Type: replace Abstract: Structured pruning is widely applied to compress large language models (LLMs), but its performance depends heavily on how neuron importance is estim
It is one of the best local models ever released, in both 20B and 120B versions. I always come back to it, especially the 120B version. Its only competition is, in my opinion, Qwen 3.5 122B, but that
arXiv:2608.02585v1 Announce Type: cross Abstract: Optimization-based latent reasoning improves large language model outputs by optimizing instance-specific continuous states at test time while keeping
arXiv:2608.01528v1 Announce Type: new Abstract: Vector symbolic architectures (VSA) are widely used for reasoning in neuro-symbolic (NeSy) AI, yet high-dimensional codebooks often create severe memory
arXiv:2608.01633v1 Announce Type: new Abstract: Large language models (LLMs) enable neural architecture search (NAS) directly over executable neural network programs. However, code-level flexibility d
arXiv:2608.00946v1 Announce Type: cross Abstract: Existing 6-DoF grasp detectors typically rank grasp candidates by detector confidence. However, our analysis on GraspNet-1Billion shows that detector
arXiv:2608.00600v1 Announce Type: new Abstract: Standard multifingered grasp execution architectures plan a collision-free trajectory to a selected grasp pose and track it with a feedback law. Executi
arXiv:2608.01660v1 Announce Type: new Abstract: Long-video question answering requires identifying sparse yet critical evidence from videos containing thousands of frames under a constrained visual-to
arXiv:2608.02497v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models excel in robotic manipulation but suffer catastrophic performance drops when canonical instructions are simply parap
arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees
arXiv:2608.02470v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly deployed as reasoning agents in real-world visual assessment pipelines, yet their spatial grounding remai
arXiv:2608.01988v1 Announce Type: new Abstract: Rapid advances in image generation models call for interpretable AI-generated image detection methods that not only determine authenticity but also prov
arXiv:2608.02392v1 Announce Type: new Abstract: A wearable assistant should both answer questions about its visual history and recognize when that history is useful to the present situation. Existing
arXiv:2608.02177v1 Announce Type: new Abstract: Existing rainfall simulation methods for autonomous driving remain limited in physical controllability and multi-view consistency. This paper presents G
arXiv:2608.00518v1 Announce Type: new Abstract: 3D visual grounding aims to localize the target object in a 3D scene from a natural language query, requiring both fine-grained semantic understanding a
arXiv:2608.00065v1 Announce Type: cross Abstract: Terminology-intensive retrieval, especially in medical settings, depends on preserving multi-word entities, abbreviations, numerical constraints, and
arXiv:2608.02124v1 Announce Type: cross Abstract: Vision-language models (VLMs) remain unreliable when predictions require fine-grained visual evidence. We identify a previously overlooked cause: spec
HappyRobot Inc., a San Francisco-based artificial intelligence startup that automates enterprise operations, said today it raised 150 million, led by Prysm Capital and co-led by Eurazeo, bringing the