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Cut-ViT: Task-Specific Model Pruning via Gram Anchoring Subspace Consistency

arXiv:2608.28205v1 Announce Type: new Abstract: Pruning visual foundation models has attracted considerable attention. However, existing methods focus on rigid point-to-point token alignment on a sing

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Cyc3D: Evaluating Cyclic Structural Stability and Asset Usability in Image-to-3D Generation

DGX agent

arXiv:2608.28080v1 Announce Type: new Abstract: Image-conditioned 3D generation has advanced rapidly, yet existing evaluation protocols largely judge rendered-view plausibility and semantic alignment,

model-releasesarxiv-cs-cv

31 Aug 2026

D-TAIA: Domain-Aware LLM Adaptation for Multi-Task Predictive Process Monitoring

arXiv:2608.28236v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) enables organizations to forecast future process behavior, such as the next activity and remaining time of ongoing c

Hardware

DAMP: Decay-Aware Mixed-Precision Recurrent-State Quantization

arXiv:2608.27513v1 Announce Type: new Abstract: Softmax attention stores key and value vectors for every preceding token, causing inference memory to grow with sequence length. Recent language models

hardwarearxiv-cs-lg

Dandelion: A Spherical Flower for Neural Simulation of Planetary Dynamics

arXiv:2608.27521v1 Announce Type: new Abstract: Many dynamical processes unfold on the sphere but the default scientific machine learning architectures are Euclidean. Applying these architectures on a

DART-FL: Burst-Aware Multitask Federated Learning under Dynamic Inference Demand at the Edge

arXiv:2608.27713v1 Announce Type: new Abstract: Edge intelligence systems increasingly require model training and online inference to coexist on resource-constrained devices, while inference demand ca

DARTS: Decoder-Aware Representation Tuning via Surgery for Model Merging

arXiv:2608.28547v1 Announce Type: new Abstract: Model merging combines multiple task-specific fine-tuned LLMs into a single multi-task model without additional training. However, merged models are kno

Debian won’t ban AI code from its Linux distribution

Debian voted to allow developers to use AI tools in their contributions to the Linux distribution's 'development, maintenance, [and] documentation.' The new policy on AI acknowledges that 'responsible

safetythe-verge-ai

Deflation-PINNs: Learning Multiple Solutions for PDEs and Landau-de Gennes

arXiv:2603.27936v3 Announce Type: replace-cross Abstract: Nonlinear Partial Differential Equations (PDEs) are ubiquitous in mathematical physics and engineering. Although Physics-Informed Neural Netwo

Deflickering Vision-Based Occupancy Networks through Lightweight Spatio-Temporal Correlation

arXiv:2502.15438v5 Announce Type: replace Abstract: Vision-based occupancy networks (VONs) provide an end-to-end solution for reconstructing 3D environments in autonomous driving. However, existing me

DeicticVLA: Unifying Instruction Modes Based on Language and Deictic Gestures in a Single VLA

arXiv:2608.28108v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) allow users to specify manipulation tasks in natural language, but distinguishing a target or placement goal amon

Denoising-Aware Temporal Point Cloud Completion for 3D Crop Architecture Recovery and Phenotypic Trait Extraction

arXiv:2608.28343v1 Announce Type: new Abstract: High-throughput phenotyping depends on accurate 3D reconstruction of plants across growth stages, yet the development and evaluation of temporal complet

DensityKV: Density-Guided KV Cache Compression for Long Video Generation

arXiv:2608.27922v1 Announce Type: new Abstract: Autoregressive video diffusion models enable streaming generation through sliding-window attention, but each generated block is conditioned on previousl

Depth-Aware Pothole Detection Using YOLO and RT-DETR at the Edge

arXiv:2608.27633v1 Announce Type: new Abstract: Pothole detection and its severity measurement is still an important challenges in urban infrastructure management, where late maintenance directly cont

Deriving Scaling Laws for OpenEuroLLM Models: Learning Rate, Batch Size and Loss

arXiv:2608.28308v1 Announce Type: new Abstract: We study the scaling behavior of learning rate and batch size in pretraining dense large language models on English-prevalent corpora. Beyond scaling ex

Destroy Me: Automatic Artifact Generation for Histopathology Images

arXiv:2608.27516v1 Announce Type: cross Abstract: Deep learning's diagnostic utility in pathology is constrained by model vulnerability to real-world data imperfections. While current strategies favor

applicationsarxiv-cs-cv

Differentiable Dynamics and Fast Simulation of Continuous Elastic Robotic Fish

arXiv:2509.16145v3 Announce Type: replace Abstract: Body flexibility plays a critical role in fish-like swimming, as the spatial distribution of stiffness governs body deformation, hydrodynamic loadin

researcharxiv-cs-ro

Diffusion Distillation for Efficient Weather Ensembles

arXiv:2608.27728v1 Announce Type: new Abstract: Diffusion models generate skillful weather ensembles but require costly iterative sampling. We introduce a supervised energy-distance distillation metho

Diffusion models as plug-and-play priors

arXiv:2206.09012v4 Announce Type: replace-cross Abstract: We consider the problem of inferring high-dimensional data mathbf{x} in a model that consists of a prior p(mathbf{x}) and an auxiliary differe

DisCTI: Who Needs to Know Timely? Automated Sector-Aware Cyber Threat Intelligence Dissemination

arXiv:2608.27967v1 Announce Type: cross Abstract: The timely dissemination of cyber threat intelligence (CTI) is critical for organizations to mount swift and effective incident response. When valid C

applicationsarxiv-cs-cl

Agents

Distributed Model-Based Diffusion: Finite Horizon Contraction under Bounded Delay

arXiv:2608.27685v1 Announce Type: new Abstract: Simultaneously optimizing the trajectories of multiple agents is a challenging problem plagued by nonlinearity, nonconvexity, and the curse of dimension

agentsarxiv-cs-ro

Diverging Transformer Predictions for Human Sentence Processing: A Comprehensive Analysis of Agreement Attraction Effects

arXiv:2603.16574v2 Announce Type: replace Abstract: Transformers underlie almost all state-of-the-art language models in computational linguistics, yet their cognitive adequacy as models of human sent

researcharxiv-cs-cl

Do Medical Vision Models Reason About Anatomy? Probing the Spatial Inductive Biases of Learned Visual Representations

arXiv:2608.28092v1 Announce Type: cross Abstract: Interpreting a CT scan means comparing structures on either side, judging how far apart organs sit, and knowing where each one belongs. Medical vision

Does anyone have real experience with Ornith-1.5-9B for coding

model-releasesr-localllama

I'm very happy with Qwen-3.8-27B, I run it on my work machine and switched for major part of real coding tasks from cloud subscriptions to it. I use one dedicated headless RTX 3090, and get maybe 1000

Does Finetuning with Scientific Data Increase Hallucinations? A Multi-domain Factuality Evaluation of LLMs

arXiv:2606.21359v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used to communicate and explain scientific concepts, yet their tendency to hallucinate poses significa

Hardware

Doesn't this look like NVIDIA is price fixing?

According to this article Samsung has locked up the 70% of it's future ram production in contracts to companies like Microsoft, Google, and Nvidia. Everyone knows this is driving the ram price increas

hardwarer-localllama

Dual-Stream Semantic Guidance with Prototype Anchor Calibration for Source-Fully-Free Adaptation of Vision-Language Models

arXiv:2608.28145v1 Announce Type: new Abstract: Source-Fully-Free Domain Adaptation (SFF-DA) has emerged as a strategic paradigm to adapt Vision-Language Models (VLMs) without any access to source dat

Dynamic Alignment Compensation for Hallucination Mitigation in Large Vision-Language Models

arXiv:2608.28058v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) remain prone to hallucinations, producing responses that are irrelevant or inconsistent with the multimodal input.

Effectiveness of IoT and Deep Learning for Detection and Severity Assessment of Postelectrotermes militaris in Tea Plantations

arXiv:2608.27480v1 Announce Type: cross Abstract: Tea plantations are vulnerable to Postelectrotermes militaris, commonly known as the Upcountry Live Wood Termite (ULWT), which can cause substantial d

Efficient Online Continual Foundation Model Fine-Tuning for Predictive Process Monitoring

arXiv:2608.28237v1 Announce Type: new Abstract: Predictive Process Monitoring (PPM) models are increasingly deployed in dynamic environments where concept drift causes the underlying process distribut

applicationsarxiv-cs-lg

Embedding Models for Stance-Aware Argument Retrieval

arXiv:2608.28283v1 Announce Type: new Abstract: In computational argumentation, obtaining arguments that explicitly support or attack given claims is a critical precursor to downstream reasoning tasks

safetyarxiv-cs-cl

Emergent aggregation from collective foraging

arXiv:2608.28046v1 Announce Type: cross Abstract: Collective behaviour in living systems is usually modelled as the outcome of a direct social drive: agents are rewarded, or hard-wired, to align with

Local Ai

Empowering Local Agriculture: A Deep Learning-Powered Web System for Identifying Bangladeshi Mango Varieties

arXiv:2608.28161v1 Announce Type: new Abstract: Mango variety identification in Bangladesh is challenging because closely related cultivars can have similar visual characteristics and images are often

local-aiarxiv-cs-cv

Energy-Efficient Collaborative Transport of Tether-Suspended Payloads via Rotating Equilibrium

arXiv:2603.06955v2 Announce Type: replace Abstract: Collaborative aerial transportation of tethered payloads is fundamentally limited by space, power, and weight constraints. Conventional approaches r

researcharxiv-cs-ro

Enterprises pull AI workloads back on-premises as costs and threats mount

Enterprise infrastructure strategy is being rewritten around the private AI cloud, as security exposure, spiking hardware prices and rising token costs push artificial intelligence workloads back insi

applicationssiliconangle

Entity-Memory Graph Retrieval Improves Evidence Coverage in Long-Conversation Question Answering

arXiv:2608.27925v1 Announce Type: new Abstract: Entity-Memory graph retrieval keeps dialogue turns as verbatim Memory nodes, links repeated mentions through shared Entities, and connects adjacent Memo

Ethical Asymmetry in Human-Robot Interaction - An Empirical Test of Sparrow's Hypothesis

arXiv:2602.02745v2 Announce Type: replace-cross Abstract: The ethics of human-robot interaction (HRI) have been discussed extensively based on three traditional frameworks: deontology, consequentialis

researcharxiv-cs-ro

Tutorials

Euclidean Fourier Neural Operators

arXiv:2608.28425v1 Announce Type: new Abstract: Fourier neural operators (FNOs) provide an efficient framework for learning mappings between function spaces as they are, by construction, independent o

tutorialsarxiv-cs-lg

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

arXiv:2305.12474v4 Announce Type: replace Abstract: Large Language Models(LLMs) have demonstrated remarkable performance across various natural language processing tasks; however, how to comprehensive

Even if you aren't interested, you should read an account of the Hugging Face Incident updated with what we learned last week, it is really …

applicationsethan-mollick--x

Even if you aren't interested, you should read an account of the Hugging Face Incident updated with what we learned last week, it is really eye opening about AI. If not mine then read the more detaile

EvoHarmBench: Breaking Content Moderation with Iterative Human-Like Evasion

arXiv:2608.27844v1 Announce Type: new Abstract: Existing evaluations of harmful content detection rely predominantly on static benchmarks, which struggle to reflect the interactive adversarial ecosyst

Ex-Sim(3)-Reg: 2D-3D Correspondence Pruning via Extended Sim(3) Registration

arXiv:2608.28096v1 Announce Type: new Abstract: Learning-based image-to-point-cloud (I2P) registration has garnered increasing attention in recent years. Nevertheless, existing methods still struggle

Exact Risk Ratios for Weighted Data Selection in Linear Regression

arXiv:2608.28007v1 Announce Type: new Abstract: Hanneke, Moran, Shlimovich and Yehudayoff (COLT 2025) posed the following open problem. A selector sees a finite dataset D subseteq R^d imes R, picks at

Examining the robustness of Physics-Informed Neural Networks to noise for Inverse Problems

arXiv:2509.20191v2 Announce Type: replace-cross Abstract: Approximating solutions to partial differential equations (PDEs) is fundamental for the modeling of dynamical systems in science and engineeri

Excited to welcome @greptile, the AI code reviewer trusted by 11,000+ teams, as a Together AI customer. Greptile's agents review and test pu…

applicationstogether-ai--x

Excited to welcome @greptile, the AI code reviewer trusted by 11,000+ teams, as a Together AI customer. Greptile's agents review and test pull requests with full context of your codebase, and running

Explainable Diabetic Retinopathy Classification Using Vision Foundation Models

arXiv:2608.28207v1 Announce Type: new Abstract: Diabetic retinopathy (DR) is a major cause of preventable blindness, creating a need for accurate and trustworthy automated screening. This study invest

Explainable Uncertainty Estimation for Reliable Medical AI

arXiv:2608.28052v1 Announce Type: new Abstract: Artificial intelligence has strong potential to support clinical decision-making, yet its adoption in healthcare remains limited due to a lack of trust.

safetyarxiv-cs-lg

EXPOSE: Explainable and Domain-Robust Embeddings from Pathology Vision Foundation Models using Sparse Autoencoders

arXiv:2608.28191v1 Announce Type: new Abstract: Vision Foundation Models (VFMs) are widely used in computational pathology but remain sensitive to domain shifts arising from variations in staining, ti