Search: “applications”

Experimenting with GPUs: GKE managed DRANET and Inference Gateway AI Deployment

model-releasesgoogle-cloud-ai

Building and serving models on infrastructure is a strong use case for businesses. In Google Cloud, you have the ability to design your AI infrastructure to suit your workloads. Recently, I experiment

8 Apr 2026

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Modify and load custom VBIOS on Windows and Linux, on Blackwell 2.0 (RTX 50 Series)/Ada(RTX 40 Series)/Ampere (RTX 30 Series) without flasing, for example to lower power limits (and which cards were tested)

DGX agent

Hello guys, hoping you're doing fine. Today I want to share something that may affect your cards (? I have released 3 tools: A way to modify VBIOSes, so you can increase power limit, voltage, NVVDD of

model-releasesr-localllama

17 Oct 2026

Industry

Neuralink president DJ Seo says Elon’s aggressive schedules are rigorous first-principles engineering, and an all-green-light schedule shows…

Neuralink president DJ Seo says Elon’s aggressive schedules are rigorous first-principles engineering, and an all-green-light schedule shows 80 to 90% of delays are just assumed “What I’ve learned is

industryelon-musk--x

17 Oct 2026

A Model Ensemble-Based Post-Processing Framework for Fairness-Aware Prediction

arXiv:2603.18838v2 Announce Type: replace Abstract: Striking an optimal balance between predictive performance and fairness continues to be a fundamental challenge in machine learning. In this work, w

Activation-Adjacent Layer Normalization: Effects on Approximation Power

arXiv:2610.21527v1 Announce Type: new Abstract: Layer normalization (LN) and root mean square normalization (RMSNorm) depend on their inputs and remain nonlinear at inference. Inserting either next to

Band launches desktop app for developer collaboration and control of multiple AI coding agents

model-releasessiliconangle

Artificial intelligence agentic collaboration platform for multi-agent systems Thenovi AI Ltd., also known as Band, announced Thursday the launch of Band for Developers, a platform and new desktop app

CARE-SD: Explainable Reasoning Architecture for Local SLM Self-Disclosure Analysis in Textual Data

arXiv:2610.21151v1 Announce Type: cross Abstract: Cybersecurity interviews uncover critical security experiences, behaviors, and privacy concerns often not fully captured by conventional technical ass

CleanRM: Reward Modeling from Noisy Feedback with a Few Clean Feedback for RLHF

arXiv:2610.21138v1 Announce Type: new Abstract: Feedback noise is pervasive in preference data, arising from subjective human judgments, annotation mistakes, and imperfect LLM judges. Standard reward

Counterfactual Neighborhood Risk Fields: Evidence-Grounded Selective Safety for Vision-Language Models

arXiv:2610.20679v1 Announce Type: new Abstract: Representation-based safety defenses for vision-language models (VLMs) often learn to separate harmful from benign inputs, but separation alone does not

ESG-Kor: A Korean Dataset for ESG-related Information Extraction and Practical Use Cases

arXiv:2610.21368v1 Announce Type: cross Abstract: With the expansion of pre-trained language model usage in recent years, the importance of datasets for performing tasks in specialized domains has sig

researcharxiv-cs-ai

Feasibility Ceilings Before Learning: Sizing and Timing Bounds for Drone-Mesh Interception

arXiv:2610.20823v1 Announce Type: cross Abstract: A mesh of interceptors defending a fixed site must spread over the predicted arrival point of an approaching object. This is a recurring task in multi

Fractional Power-of-Two Quantization for Efficient and Effective Multiplier-Free LLM Inference

arXiv:2610.21257v1 Announce Type: cross Abstract: Large Language Models (LLMs) demand efficient inference, where the multiply-accumulate (MAC) operations in linear projections dominate compute and ene

Fractional Rotation, Full Potential? Investigating Performance and Convergence of Partial RoPE

arXiv:2603.11611v2 Announce Type: replace-cross Abstract: Rotary Positional Embedding (RoPE) is widely used in transformers to encode relative positional information, yet the effect of applying RoPE t

researcharxiv-cs-cl

From Documents to Spans: Span-Centric Learning for LLM-based Explainable Medical Coding

arXiv:2603.15270v3 Announce Type: replace-cross Abstract: Medical coding, which assigns standardized ICD codes to clinical documents, is a fundamental yet challenging task in modern healthcare. It req

Generalization Guarantees of Randomized Block Coordinate Descent for Nonconvex Learning

arXiv:2610.22213v1 Announce Type: new Abstract: Randomized block coordinate descent (RBCD) is a popular optimization algorithm for many large-scale machine learning problems. The existing theoretical

Tutorials

GeoPano: Towards Geometrically Accurate 3D Reconstruction from a Single Panorama

arXiv:2610.21297v1 Announce Type: new Abstract: Panoramic 3D reconstruction enables the holistic recovery of complete 360 ^irc scene geometry, offering significant benefits for robotics and AR/VR appl

tutorialsarxiv-cs-cv

Agents

Hierarchical Building-Floo-Room Framework for Privacy-Preserving Autonomous Delivery in Large-Scale Buildings

arXiv:2610.21361v1 Announce Type: new Abstract: Autonomous delivery in large scale buildings requires coordinated planning across multiple spatial levels, including building, floor, and room, while en

agentsarxiv-cs-ro

INCONVENIENT: A Benchmark to Assess LLM Generalization Capabilities from Convenience Samples

arXiv:2610.21038v1 Announce Type: cross Abstract: Machine learning models for tabular prediction typically assume that training data are representative of the population on which they will be deployed

ISW-Agent: Integrating LLM-Driven Dialogue with n8n Workflow for Internal Solitary Wave Remote Sensing Image Processing

arXiv:2610.21502v1 Announce Type: new Abstract: Internal solitary wave (ISW) remote sensing requires task parameters and spatial information to be transferred across image acquisition, detection, stri

Large Language Models Naively Recover Ethnicity from Individual Records

arXiv:2601.21132v2 Announce Type: replace Abstract: I demonstrate that large language models can infer ethnicity from names with accuracy exceeding that of Bayesian Improved Surname Geocoding (BISG) w

Machine-learning-based neutrino-event generation constrained by experimental measurements

arXiv:2610.20870v1 Announce Type: cross Abstract: We present a generative surrogate for charged-current (nu_mu)-nucleus scattering that can be calibrated to measured differential cross sections withou

Agents

MAI-Gym: An Open All-in-One Platform for GUI Agent Evaluation and RL Training across Mobile and Computer Environments

arXiv:2610.20939v1 Announce Type: new Abstract: Online reinforcement learning (RL) with verifiable rewards has driven rapid progress in mathematics, coding, and tool use, but scaling this success to G

agentsarxiv-cs-ai

Nemotron 3.5 Bolt Evaluation using real-world tasks

model-releasesr-localllama

I evaluate new models by giving them actual work tasks that have already been completed by a trusted model and then comparing the results. My typical workflow is to plan tasks/requests in Gemini and c

On the Last-Iterate Convergence of Clipped Gradient Methods

arXiv:2610.21026v1 Announce Type: cross Abstract: In stochastic (strongly) convex optimization, establishing last-iterate convergence guarantees for first-order methods has recently garnered increasin

PathFM: Fast Generative Forecasting of Multivariate Trajectories

arXiv:2610.22358v1 Announce Type: new Abstract: Time series foundation models are becoming increasingly popular for general-purpose forecasting. However, most leading models predict marginal quantiles

Personalized Projected Ascent for Federated Stackelberg Optimization

arXiv:2610.21295v1 Announce Type: new Abstract: Federated minimax problems, such as distributionally robust optimization and adversarial training, include an inner maximization variable built from eac

PiCo: Physics-Informed Concept Probing for Geo-Foundation Models

arXiv:2610.20973v1 Announce Type: new Abstract: Geo-foundation models (GFMs) are typically evaluated by downstream task predictive performance, revealing little about which physical features they are

researcharxiv-cs-cv

Real-time Chatbot Romance Scam Detection in Stage Classification

arXiv:2610.20631v1 Announce Type: cross Abstract: Romance scam has become a serious problem via social media, and the improvement of artificial intelligence enable to fake identify easily. In the stud

researcharxiv-cs-ai

RecSoup: Efficient Model Merging Approach for Controllable Multi-Objective Recommendation

arXiv:2610.21220v1 Announce Type: cross Abstract: Recommender systems often need to balance multiple conflicting objectives. Controllable Multi-Objective Recommendation (CMOR) enables dynamic adjustme

SCMerge: Spatial-Consistency-Aware Token Pair Merging for Efficient Semantic Segmentation

model-releasesarxiv-cs-cv

arXiv:2610.21642v1 Announce Type: new Abstract: Vision Transformer architectures have showcased impressive performance on semantic segmentation, yet their quadratic attention complexity hinders practi

Second Maximum of a Gaussian Random Field and Exact (t-)Spacing test

arXiv:2406.18397v4 Announce Type: replace-cross Abstract: In this article, we introduce the novel concept of the second maximum of a Gaussian random field defined on a Riemannian manifold: Once the fi

Slip-Induced Fall Suppression During Cornering for a Remotely Operated Motorcycle with a Rear-Wheel-Swing Mechanism

arXiv:2610.21089v1 Announce Type: new Abstract: Slip-induced falls when riding motorcycles are difficult to avoid even for expert riders and represent a major cause of single-vehicle accidents. Despit

researcharxiv-cs-ro

Soft Sensor for Bottom-Hole Pressure Estimation in Petroleum Wells Using Long Short-Term Memory and Transfer Learning

arXiv:2602.03737v2 Announce Type: replace Abstract: Monitoring bottom-hole variables in petroleum wells is essential for production optimization, safety, and emissions reduction. Permanent Downhole Ga

Task-Phase-Conditioned Expert Routing Is Not a Reliable Proxy for Quantization Sensitivity in MoE FFN Tensors

model-releasesarxiv-cs-lg

arXiv:2610.20826v1 Announce Type: new Abstract: We investigate whether per-layer, per-task-phase (prompt/reasoning/response) expert-routing statistics in a Mixture-of-Experts (MoE) language model can

Text-to-Image Synthesis: A Decade Survey

arXiv:2411.16164v2 Announce Type: replace Abstract: Text-to-image synthesis (T2I) focuses on generating high-quality images from textual descriptions In this survey, we review 490 papers on T2I spanni

safetyarxiv-cs-cv

Time-partitioning Gaussian Process Mixture Model

model-releasesarxiv-cs-lg

arXiv:2610.20860v1 Announce Type: cross Abstract: We propose the Time-partitioning Gaussian Process Mixture Model (TPGPMM), a Bayesian nonparametric framework for identifying persistent regimes and mo

VOiLA: Vectorized Online Planning with Learned Diffusion Models for POMDP Agents

arXiv:2606.19729v3 Announce Type: replace-cross Abstract: Planning under uncertainty is an essential capability for autonomous robots. The Partially Observable Markov Decision Process (POMDP) provides

Why Shallow Neural Networks Learn Sinusoidal Components First: An Orthogonal Polynomial Dynamics Framework

arXiv:2610.21964v1 Announce Type: cross Abstract: Neural networks often learn low-frequency components before high-frequency ones --- a phenomenon called spectral bias or termed F-principle. Many nume

A Versatile Variational Quantum Kernel Framework for Non-Trivial Classification

model-releasesarxiv-cs-lg

arXiv:2511.10831v3 Announce Type: replace Abstract: Quantum kernel methods are a promising branch of quantum machine learning, but their per- formance across data types and encoding choices remains in

Actionable Meta-Requirements for AI Robustness Auditing

arXiv:2610.14356v1 Announce Type: new Abstract: AI-enabled systems must remain dependable when the conditions under which they operate change (e.g., due to input perturbations, distribution shifts, or

researcharxiv-cs-ai

AdaptFuse: Training-Free Sequential Preference Inference via Externalized Bayesian Computation

arXiv:2604.03925v2 Announce Type: replace Abstract: Large language models (LLMs) struggle to accumulate evidence across multiple rounds of user interactions, failing to update their beliefs in a manne

Agency as a New Organizing Abstraction for Computer Science

arXiv:2610.17410v1 Announce Type: new Abstract: Advances in large-scale machine learning have enabled agentic AI systems: persistent, autonomous computational entities that pursue goals, initiate acti

AgentStripes: An Evidence-Graded Maturity Model for AI Agents

arXiv:2610.18603v1 Announce Type: new Abstract: Benchmarks report what an Artificial Intelligence (AI) agent can do on a task suite, but not whether one released version has been engineered with the c

AlignAudio: A Unified Dual-Alignment Framework for Noise-Robust Speech-Conditioned Generation

arXiv:2610.14697v1 Announce Type: cross Abstract: Speech-conditioned generation maps speech signals to target audio outputs. Prior end-to-end speech-conditioned generative models achieve high fidelity

Anuvani-Diarization: Zero Shot Speaker Diarization and Annotation Conventions Across 22 Languages

arXiv:2610.20327v1 Announce Type: new Abstract: India's 22 scheduled languages are spoken by over a billion people in conversations that mix languages, often within one turn, overlap freely, and take

Hardware

AReaL-RSI: Adaptive Scaling and Coordination of Recursive Self-Improvement

arXiv:2610.18083v1 Announce Type: new Abstract: Scaling recursive self-improvement requires additional computation to produce useful research progress in reaching persistent objectives. Intuitively, m

hardwarearxiv-cs-ai

Attention-Based Spatio-Temporal Approach for Fire and Smoke Detection

arXiv:2610.20141v1 Announce Type: new Abstract: In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is

safetyarxiv-cs-cv

Backpropagating Verifier Rewards Through Continuous Flow Language Models

arXiv:2610.19080v1 Announce Type: new Abstract: Reinforcement learning (RL) has substantially improved the reasoning of autoregressive and discrete-diffusion language models. Language models that gene