All entries

Time Series Network Utilization KPI Forecasting Using Advanced AI/ML Models

arXiv:2607.19974v1 Announce Type: cross Abstract: The rapid proliferation of data-intensive applications, cloud infrastructure, and IoT ecosystems has made proactive resource provisioning critical for

researcharxiv-cs-ai

Timeripple: Accelerating vDiTs by Understanding the Spatio-Temporal Correlations in Latent Space

DGX agent

arXiv:2511.12035v2 Announce Type: replace-cross Abstract: The recent surge in video generation has shown the growing demand for high-quality video synthesis using large vision models. Existing video g

researcharxiv-cs-cv

23 Jul 2026

Applications

TINY_SCHILLER: A Drop-In German Drama Corpus for Small Language Models

arXiv:2607.19992v1 Announce Type: cross Abstract: tiny_schiller closes the small-language-model prototyping, fine-tuning, education, and research gap for German literary text, providing a single-file,

applicationsarxiv-cs-ai

Total Variation Distance Estimation in Autoregressive Models

arXiv:2607.19510v1 Announce Type: new Abstract: Modern LLM deployments use a number of implementation choices and inference optimizations (e.g., batching, custom kernels, and quantization) on top of f

Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation

model-releasesarxiv-cs-cv

arXiv:2509.24739v4 Announce Type: replace Abstract: Vision-Language Foundation Models (VLMs), trained on large-scale multimodal datasets, have driven significant advances in Artificial Intelligence (A

Toward Adaptable Multi-Agent Reinforcement Learning: An Assumption-Aware Review

arXiv:2507.10142v2 Announce Type: replace Abstract: Multi-Agent Reinforcement Learning (MARL) has achieved strong performance in simulated benchmarks, yet real deployments often violate the assumption

safetyarxiv-cs-ai

Toward Anthropomorphic Dialogue: A Closed-Loop Framework for Human-Like Chat Generation, Evaluation, and Preference Alignment

arXiv:2607.17191v2 Announce Type: replace Abstract: Human-like private chat requires more than fluent response generation: a system must preserve persona, relationship, memory, bounded knowledge, medi

Toward Reliable RGB-D Semantic Segmentation: Handling Missing Modalities via Condition Dropout

arXiv:2607.20326v1 Announce Type: cross Abstract: RGB-D semantic segmentation has achieved remarkable progress, yet most models assume that RGB and depth are always available. In practice, failures or

researcharxiv-cs-ai

Toward Seasonal Guidelines for Robust Deep-Learning Sentinel-2 Building Detection in Different Area Types

arXiv:2607.19994v2 Announce Type: new Abstract: Sentinel-2 imagery offers open access, global coverage, and frequent revisit times, making it attractive for practical building mapping at scale; howeve

Towards Miniature Humanoid Tele-Loco-Manipulation Using Virtual Reality and Reinforcement Learning

arXiv:2607.20399v1 Announce Type: cross Abstract: Full-sized humanoid robot capabilities have grown exponentially in recent years, aiming towards general-purpose deployment in human environments. A po

Applications

Towards Practical Emotion Recognition: An Unsupervised Source-Free Approach for EEG Domain Adaptation

arXiv:2504.03707v2 Announce Type: replace-cross Abstract: Emotion recognition is crucial for advancing mental health, healthcare, and technologies such as brain-computer interfaces. EEG-based models,

applicationsarxiv-cs-lg

Towards Torque-Driven Reinforcement Learning for Quadruped Locomotion

arXiv:2607.18365v1 Announce Type: cross Abstract: Reinforcement learning (RL) for legged robots is advancing locomotion, demonstrating its ability to adapt to new and challenging terrain. Traditionall

safetyarxiv-cs-lg

Trace: A Taxonomy-Guided Environment for Multidomain Visual Reasoning

arXiv:2607.19790v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has substantially improved language-model reasoning, yet its extension to vision-language models r

Train the Model, Not the Reader: Decodability Supervision for Verifiable Activation Explanations

arXiv:2607.20379v1 Announce Type: new Abstract: Natural-language autoencoders score explanations of hidden activations by reconstruction: an explanation is deemed faithful if the activation can be reg

Trained a 32B FLUX.2 LoRA on a 24GB AMD 7900 XTX, native ROCm on Windows — full guide + patches

model-releasesr-stablediffusion

TL;DR: Everyone says QLoRA past ~13B is dead on a 24GB card. I got the full 32B FLUX.2 dev transformer QLoRA-training resident on the GPU on a 7900 XTX under native ROCm on Windows (no ZLUDA, no CUDA

Local Ai

TRELLIS.2 can now generate a high-quality 3D asset in under 7 minutes on a 6 GB VRAM CUDA GPU. No ComfyUI Node Nightmare.

local-air-stablediffusion

Not Self Promotion: Just sharing an open-source tool I built to democratize image to 3D creations. For OpenAI Build Week Hackathon I built a free, open-source local Image-to-3D Studio that makes TRELL

Trend strength predicts when generative foundation models win: a power-controlled benchmark, a mechanism, and an actionable selection rule

model-releasesarxiv-cs-lg

arXiv:2607.19383v1 Announce Type: cross Abstract: Pretrained generative foundation models cast forecasting as conditional generation from a learned predictive distribution and forecast unseen series z

TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis

model-releasesarxiv-cs-cl

arXiv:2607.19794v1 Announce Type: new Abstract: Production LLM-based financial sentiment analysis faces a structural cost trap: most queries are trivially classifiable, yet expensive cloud reasoners p

TRUST-ESD: A Risk-Calibrated and Governance-Aware AI Framework for Enterprise Strategic Decision Support Under Uncertainty

arXiv:2607.20065v1 Announce Type: new Abstract: Enterprise strategic decision support requires AI systems that are not only accurate, but also uncertainty-aware, risk-calibrated, explainable, and gove

safetyarxiv-cs-ai

Trusted Multi-View Deep Learning Classification of Fetal Congenital Heart Disease with Feature-level and Decision-level Fusion

model-releasesarxiv-cs-cv

arXiv:2606.15265v2 Announce Type: replace Abstract: Congenital heart disease (CHD) refers to the abnormal anatomical structure caused by the abnormal development of the heart and great vessels during

Trusting What You Cannot See: Auditable Fine-Tuning and Inference for Proprietary AI

arXiv:2603.07466v2 Announce Type: replace-cross Abstract: Cloud-based infrastructure has become the dominant platform for deploying large models, particularly large language models (LLMs). Fine-tuning

Trustworthy Privacy-Preserving Multimodal Federated Learning for Personalised Breast Cancer Prediction

arXiv:2607.19532v1 Announce Type: cross Abstract: Federated learning has emerged as a potential solution to privacy concerns associated with using sensitive health data for training predictive models,

safetyarxiv-cs-ai

Industry

Try the Tavily plugin for LLM-driven search inside Grok Build

Try the Tavily plugin for LLM-driven search inside Grok Build Tavily is now live as an official plugin in @grok Build. Bring real-time, LLM-optimized web search into your Grok Build workflows. You'll

industryelon-musk--x

Agents

Twin Agent: Context Residual Compression for Privilege Separated Agents

arXiv:2607.19595v1 Announce Type: cross Abstract: Large language model (LLM) agents are vulnerable to security risks, such as prompt injection attacks from untrusted context that manipulate downstream

agentsarxiv-cs-cl

Two-Step Occupation Coding

arXiv:2607.20101v1 Announce Type: new Abstract: Occupation coding links job titles in free text to occupational taxonomies and is a core task in labor market research. Existing approaches typically ad

researcharxiv-cs-cl

Understanding Developer Pain Points in Federated Learning: Insights from Stack Overflow and GitHub

arXiv:2607.19621v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative model training without centralizing raw data, but building and operating FL systems remains difficult du

researcharxiv-cs-ai

Understanding Generative AI-mediated User Engagement with Academic Library Resources

arXiv:2607.20328v1 Announce Type: cross Abstract: This study empirically analyzed generative AI as an emerging discovery pathway to academic library resources. Utilizing web analytics from August 2023

Local Ai

Understanding the Impact of Linguistic Realization Choices on LLM Stance with Causal Tracing

arXiv:2607.20115v1 Announce Type: new Abstract: Large language models (LLMs) are known to be sensitive to prompt and input formulations. However, existing studies have focused on lexical realization a

local-aiarxiv-cs-cl

Unified Prediction and Planning via Conflict-Aware Disjoint Parameter Training

model-releasesarxiv-cs-ro

arXiv:2607.19971v1 Announce Type: new Abstract: Accurate motion prediction of surrounding agents and safe motion planning are two closely coupled key tasks for social robot navigation in crowded envir

Universality Reconsidered: Rethinking the Validation of Foundation Models for General-Purpose 3D Medical Segmentation

model-releasesarxiv-cs-cv

arXiv:2602.07643v2 Announce Type: replace Abstract: Foundation models have emerged as a transformative paradigm in 3D medical imaging, with the promise of unified quantitative analysis across diverse

Unlearning as Distribution Restoration: A Controlled Counterfactual Study, a Validated Selective Screen, and the Limits of Oracle-Free Certification

arXiv:2607.19442v1 Announce Type: cross Abstract: Machine unlearning is commonly evaluated by matching a retrained oracle on trained probes. In a controlled nonce-fact testbed with a matched retrainin

User-Centric Modeling of Transactional Sequences with Explainable State Space Models

arXiv:2607.20228v1 Announce Type: new Abstract: We propose a hybrid approach for user-centric modeling of transactional event sequences that combines contrastive representation learning (CoLES) with S

UVFaceFusion: Fast Multi-view Topologically Consistent Face Reconstruction in the Wild via UV-space Neural Fusion

arXiv:2607.18798v1 Announce Type: new Abstract: Reconstructing high-fidelity facial geometry with an assigned topology is essential for digital avatar creation and animation, yet existing automated me

v0.32.3

model-releasesollama-releases

What's Changed mlx update by @dhiltgen in #17332 model/parsers: finalize incomplete GLM tool calls by @dhiltgen in #17250 docs: update retirements by @mxyng in #17289 model: align Laguna with upstream

V2F: Vision-Informed Grasp Force Prediction for Damage-Aware Robotic Handling of Date Fruits

arXiv:2607.19804v1 Announce Type: new Abstract: This paper presents a vision-informed grasp force prediction framework for robotic handling of date fruits. Addressing the dual challenge of high detach

researcharxiv-cs-ro

Variance-reduced Domain Adaptation using Paired Sampling

arXiv:2607.20367v1 Announce Type: new Abstract: Correlation alignment and the maximum mean discrepancy are two widely used distribution-matching frameworks for unsupervised domain adaptation (UDA). Ho

safetyarxiv-cs-lg

Vera: Identity-Faithful Human Subject-to-Video Generation

arXiv:2607.20247v1 Announce Type: new Abstract: Subject-to-video (S2V) generation has made substantial progress in preserving reference subjects across diverse categories, yet generic subject consiste

Hardware

Vera Rubin NVL72 vs GB200 NVL72? Inference TCO & Architecture Analysis

Vera Rubin NVL72 is Nvidia’s second‑generation, rack‑scale Oberon architecture that achieves inference gains through extreme co‑design. Early engineering‑sample data from CoreWeave show DeepSeek R1 de

hardwaresemianalysis

VG3S: Visual Geometry Grounded Gaussian Splatting for Semantic Occupancy Prediction

model-releasesarxiv-cs-ro

arXiv:2603.06210v2 Announce Type: replace-cross Abstract: 3D semantic occupancy prediction has become a crucial perception task for comprehensive scene understanding in autonomous driving. While recen

VizRAG: Enhancing Retrieval-Augmented Generation with Hypergraph Visualization

arXiv:2607.19830v1 Announce Type: new Abstract: Hypergraph-based RAG systems surpass traditional graph-based approaches by organizing complex n-ary atomic facts among entities, rather than relying sol

researcharxiv-cs-cl

VQ-Transplant: Efficient VQ-Module Integration for Pre-trained Visual Tokenizers

arXiv:2607.19575v1 Announce Type: new Abstract: Vector Quantization (VQ) underpins modern discrete visual tokenization. However, training quantization modules for state-of-the-art VQ-based models requ

Agents

Vultr Announces Support for AMD Helios™ Rackscale Solution Powered by AMD Instinct™ MI455X GPUs

Vultr has added support for the AMD Helios™ rackscale platform, which is driven by AMD Instinct™ MI455X GPUs. This allows the provider to offer high‑memory, GPU‑accelerated compute for enterprise work

agentsvultr

WanSong v1.0 Technical Report

arXiv:2607.14749v3 Announce Type: replace-cross Abstract: Music generation foundation models have recently attracted significant industry attention. However, achieving efficient generation and high-fi

Agents

WASABI: Whole-graph Assignment-based Stabilizer for lAne topology By Inter-frame tracking

arXiv:2607.19781v1 Announce Type: new Abstract: Autonomous driving requires understanding the road as a graph of drivable lanes and their connectivity, beyond the ego lane alone, to follow routes thro

agentsarxiv-cs-cv

Wave2Body: Rethinking mmWave Human Pose Estimation as Radar-to-Body Token Translation

arXiv:2607.18875v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar enables privacy-friendly human sensing, but its sparse point clouds are physical measurements of view-dependent electroma

safetyarxiv-cs-cv

Wavefront Parallelization for Efficient Learned Image Compression

arXiv:2607.19082v1 Announce Type: cross Abstract: Autoregressive context models are foundational for learned image compression,but they suffer from slow serial inference. Existing acceleration methods

We built this experience based on feedback from early testers and physicians. With your permission, ChatGPT can use relevant context you’ve …

We built this experience based on feedback from early testers and physicians. With your permission, ChatGPT can use relevant context you’ve connected in Health across your conversations — to help you

model-releasesopenai--x

Tutorials

Weakly Supervised Pathology-Informed Representation Learning for PET-Based Content Retrieval of Intra-Tumour Heterogeneity

arXiv:2607.18762v1 Announce Type: new Abstract: We propose a weakly supervised 18FFDG PET representation-learning framework for content based medical image retrieval, using H&E derived information dur

tutorialsarxiv-cs-cv