All entries

Explainable Failure Prediction and Prevention in Maritime

arXiv:2610.08363v1 Announce Type: new Abstract: Maritime systems operate in highly dynamic environments where unexpected equipment failures can compromise safety, reliability, and operational efficien

Explainable Rule Mining of IPv6 Extension-Header Presence Patterns from Paired-Vantage Captures

Content type

All Blog X Post Paper YouTube Reddit GitHub

DGX agent

arXiv:2610.08090v1 Announce Type: cross Abstract: IPv6 extension headers (EHs), such as fragmentation, segment routing, and in-situ telemetry, are operationally important yetwidely dropped in transit,

researcharxiv-cs-lg

7 Oct 2026

Explicit Asymptotic Bounds for Sequential Calibration Beyond T^{2/3}

arXiv:2610.07623v1 Announce Type: cross Abstract: Probability forecasts are calibrated when predicted probabilities match empirical outcome frequencies: among events assigned a probability p, we'd hop

Exploiting Acoustic and Content-Oriented Speaker Verification Attacks Against Multilingual Voice Anonymization

arXiv:2610.08107v1 Announce Type: cross Abstract: Attacker ASV systems for voice anonymization have been studied primarily in English, leaving their behavior in multilingual settings largely unexplore

Tutorials

Explore ideas through interactive visuals that respond as you learn, try, and discover.

On October 7, 2026 OpenAI released a session titled “Explore ideas through interactive visuals that respond as you learn, try, and discover.” The webcast showcased real‑time visual tools that adapt to

tutorialsopenai--x

Explore the top AI papers of the week with our brand-new MCP tools. Connect it to Codex, Claude Code, or Grok Bot.

Explore the top AI papers of the week with our brand-new MCP tools. Connect it to Codex, Claude Code, or Grok Bot. Introducing MCP tools for @dair_ai. Connect the MCP to your Codex/Claude/Grok Bot to

model-releasesdair-ai--x

Explore, Then Commit: Measurement-Efficient Scientific Law Discovery with Language Models

arXiv:2610.07620v1 Announce Type: new Abstract: Scientific law discovery requires selecting measurements and converting evidence into a governing equation. We evaluate an explore-then-commit protocol

Expressiveness, Equivalence, and Uncertainty in Velocity Obstacles and Closest Point of Approach Metrics

arXiv:2610.07371v1 Announce Type: new Abstract: Time to Closest Point of Approach (TCPA), Distance to Closest Point of Approach (DCPA), and Velocity Obstacles (VOs), are widely used to assess and miti

agentsarxiv-cs-ro

Extending Music Annotation Schemas: Zero-Shot Prediction or Few-Shot Adaptation?

arXiv:2610.06920v1 Announce Type: cross Abstract: Automatic music annotation is typically tackled under the assumption of a fixed annotation schema. In practice, commercial music catalogs often need t

Extending Pathwise Gradients to Discrete Random Variables via Finite-Order Relaxation

arXiv:2610.07786v1 Announce Type: new Abstract: Pathwise gradients are preferred for continuous random variables because they are unbiased, low variance, and work with a single sample. For discrete va

FactorBench: A Portfolio-Aware Benchmark for Automated Factor Mining

arXiv:2610.06947v1 Announce Type: cross Abstract: Factor mining seeks to discover signals from financial data that predict future asset returns and guide portfolio construction. Automated factor minin

Fast and Efficient Asynchronous Gossip Algorithm for Robust and Non-Smooth Convex Decentralized Learning

arXiv:2601.20571v3 Announce Type: replace-cross Abstract: Asynchronous primal-dual methods for decentralized non-smooth convex optimization often require each node to maintain O(d) auxiliary variables

Fast, Interpretable, and Deterministic Time Series Classification With a Bag-of-Receptive-Fields

arXiv:2311.18029v2 Announce Type: replace-cross Abstract: The current trend in the literature on Time Series Classification is to develop increasingly accurate algorithms by combining multiple models

Fast Non-Parametric Heteroscedastic Imitation Learning With Geometric Priors

arXiv:2610.08650v1 Announce Type: new Abstract: When learning probabilistic policies from human demonstrations, data-efficient learning and fast adaptations to new scenarios are key requirements. One

agentsarxiv-cs-ro

Hardware

Faster Scientific Image Analysis with NVIDIA cuPhoton

NVIDIA cuPhoton is an open‑source CUDA‑X toolkit that keeps scientific image data on the GPU from ingestion through classification, providing modules such as xDataReader (direct FITS loading), xRep (a

hardwarenvidia-developer

FastH3 V2/V3: Project Status

model-releasesr-stablediffusion

https://preview.redd.it/pr5bl6rcezth1.png?width=834&format=png&auto=webp&s=dca7440c56e169b53a586182368829f848805c9a They released FastH3 V2 three weeks ago: https://www.reddit.com/r/StableDiffusion/co

FastVideo’s FastH3 now runs on a single consumer machine

local-air-stablediffusion

https://x.com/haoailab/status/2107591980591227227 https://github.com/hao-ai-lab/FastVideo https://haoailab.com/FastVideo/cookbook/minimax-h3/ https://huggingface.co/FastVideo/FastVideo-FastH3-Trim-Com

FC-SWE: Failure-Conditioned RL for Long-Horizon Software Engineering Agents

arXiv:2610.07898v1 Announce Type: new Abstract: Repository-level software engineering (SWE) is a challenging long-horizon setting: agents must reason over extended interactions, use tools, and adapt t

safetyarxiv-cs-lg

Feature Encoding in VAE-based Audio Decoders: Effects of Input, Depth and Distribution

arXiv:2610.07966v1 Announce Type: cross Abstract: Neural audio synthesis models like the Realtime Audio Variational autoEncoder (RAVE) achieve impressive genera tion quality, yet how their internal re

Feature Information Dynamics in Diffusion

arXiv:2610.08626v1 Announce Type: cross Abstract: Diffusion models generate data through a continuum of denoising problems, and are widely observed to reveal coarse structure before fine detail. Yet,

Hardware

Feature Space Analysis by Guided Diffusion Model

arXiv:2509.07936v3 Announce Type: replace Abstract: This paper aims to analyse the feature space of a vision-related Deep Neural Network (DNN) by proposing a decoder that can generate an image whose f

hardwarearxiv-cs-cv

Fed-BRDECS: Privacy-Preserving and Heterogeneity-Aware Federated Deep Embedded Clustering

arXiv:2610.07399v1 Announce Type: new Abstract: Federated deep clustering seeks to learn clustering-friendly representations from decentralized unlabeled data while preserving client privacy. However,

local-aiarxiv-cs-lg

FedCoT: Communication-Efficient Federated Reasoning Enhancement for Large Language Models

arXiv:2508.10020v2 Announce Type: replace-cross Abstract: Enhancing LLM reasoning in federated settings is nontrivial due to stringent computational, communication, and privacy constraints, especially

FedDermaSeg: Federated Learning for Dermatological Image Segmentation

arXiv:2610.08574v1 Announce Type: cross Abstract: Skin cancer is a major global health concern, and early detection and accurate lesion delineation are important for effective diagnosis and treatment

Federated Bayesian Surveillance of Mechanical Thrombectomy Adverse Events: A Population Risk Layer for Surgical Digital Twins

model-releasesarxiv-cs-ro

arXiv:2610.08464v1 Announce Type: cross Abstract: Learned surgical simulators and world models can roll out plausible procedural futures, but they carry no grounded estimate of how often interventiona

Federated Mixture-of-Experts Alignment on Mobile Edge Networks under Data Heterogeneity

arXiv:2603.21276v2 Announce Type: replace-cross Abstract: The growing demand for on-device large language model (LLM) services on mobile edge devices has driven the adoption of Mixture-of-Experts (MoE

Feeling Through the Load: Compliant Quadruped Locomotion under Payload Interactions

arXiv:2610.08637v1 Announce Type: new Abstract: Quadruped robots are increasingly expected to carry objects while moving through human environments. But what happens when a person interacts directly w

safetyarxiv-cs-ro

Few-Shot Bioactivity Prediction with Meta-Learning under Assay Heterogeneity

arXiv:2610.07079v1 Announce Type: new Abstract: Accurate bioactivity prediction is a central challenge in early-stage drug discovery, as individual assays often contain too few measurements to train r

Finding the Heads and the Neurons Responsible for Network Information Retrieval in Language Models

arXiv:2610.08200v1 Announce Type: new Abstract: We ask whether specific attention heads, and more finely specific neurons inside those heads, are responsible for recognizing that a language model's co

Fine-Tuning VLM for Enhancing AI's Spatial Intelligence: Understanding 3D and 2D Rotations

arXiv:2610.04206v2 Announce Type: replace Abstract: Spatial intelligence is a fundamental skill in multiple domains, such as Science, Technology, Engineering, and Mathematics (STEM), Medicine, Archite

Applications

FlexiFlow: Bandit-based Model Switching in ML Workflows

arXiv:2610.07286v1 Announce Type: cross Abstract: Model optimizations help improve inference performance and accuracy of ML workflows. However, relying on a single model to perform inference across al

applicationsarxiv-cs-ai

FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

arXiv:2610.08537v1 Announce Type: cross Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would

Applications

FluidPD: In-Place Elasticity for SLO-Aware Prefill-Decode Disaggregated LLM Serving

arXiv:2610.06917v1 Announce Type: new Abstract: Prefill-decode disaggregation is becoming a common architecture for LLM serving because it separates two phases with distinct execution patterns and SLO

applicationsarxiv-cs-ai

Fluorescence-enhanced Whisker Array with Vision-based Deformation Analysis for Underwater Source Localization

arXiv:2610.07275v1 Announce Type: new Abstract: Deep-water biological observation is essential for understanding marine organisms and their interactions with the environment. However, conventional opt

safetyarxiv-cs-ro

Hardware

Forecast Accuracy Is Not Trading Profit: Evolving Small Recurrent Networks for Stock Return Prediction

arXiv:2610.07825v1 Announce Type: cross Abstract: Time series forecasting models are typically compared on pointwise error, which scores a prediction in isolation from the decision it is produced for,

hardwarearxiv-cs-lg

Forecasting the Growth of Social Media Information Cascades: Towards Human-in-the-Loop Misinformation Triage

arXiv:2610.07209v1 Announce Type: cross Abstract: Limited review teams must identify which emerging claims are likely to keep growing before their eventual reach is known. We center early misinformati

researcharxiv-cs-cl

Forensic Reserve: Eliciting Latent Knowledge for Image Forgery Detection

model-releasesarxiv-cs-cv

arXiv:2610.08639v1 Announce Type: new Abstract: As generated images become increasingly realistic, reliable forgery detection is essential for maintaining trust in visual information. However, existin

Foresight-over-Graph: Reasoning Beyond Local Horizons for Knowledge Base Question Answering

arXiv:2610.08388v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in question answering, yet they still frequently suffer from hallucinations on know

local-aiarxiv-cs-ai

Fork-and-Flush: Escaping Idea Basins in Autoresearch Agents

arXiv:2610.07447v1 Announce Type: new Abstract: Autoresearch agents tackle open-ended problems by repeatedly proposing candidate solutions, evaluating them, and using feedback to guide subsequent expe

agentsarxiv-cs-lg

FOSLS-deRhaNN: native de Rham neural classes for H(div) and H(curl) with applications to first-order system least-squares neural network methods for partial differential equations

arXiv:2610.08016v1 Announce Type: cross Abstract: We construct neural approximation classes native to the graph spaces H(div) and H(curl), in two and three dimensions and, for H(div), in any dimension

Foundation Model-Aided Multi-Agent Reinforcement Learning for Wireless Random Access Network Optimization

arXiv:2610.07550v1 Announce Type: cross Abstract: Random access (RA) is one of the most foundational medium access control (MAC) layer scheduling schemes for handling unpredictable data traffic from m

local-aiarxiv-cs-ai

Foveated Compression: Selective High-Resolution Preservation for Token-Efficient VLMs

arXiv:2610.07729v1 Announce Type: new Abstract: Visual tokens are a major source of inference cost in vision-language models, yet simple image downsampling remains a surprisingly strong compression ba

local-aiarxiv-cs-cv

FRAGMENTA: Efficient End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimization in Small Data Regime

arXiv:2511.20510v3 Announce Type: replace Abstract: Molecule generation from extremely limited training data is a key challenge in drug discovery. Existing fragment-based methods are more suitable tha

agentsarxiv-cs-ai

FreDF: Learning to Forecast in the Frequency Domain

arXiv:2402.02399v3 Announce Type: replace-cross Abstract: Time series modeling presents unique challenges due to autocorrelation in both historical data and future sequences. While current research pr

From Evidence to Action: How Tool-Using Agents Fail

arXiv:2610.07753v1 Announce Type: cross Abstract: Tool-using agents make consequential changes to external state, yet correct outcomes do not guarantee that their actions were supported by evidence es

From Laboratory to Road: Evaluating Wearable Gaze Accuracy for Driving

arXiv:2610.07783v1 Announce Type: new Abstract: Bird's-eye-view (BEV) representations have become a widely used interface between perception and planning in autonomous driving, but they encode what is

safetyarxiv-cs-cv

From Legs to Wheels: Embodiment-Aware Human Motion Retargeting for Mobile-Base Humanoids

arXiv:2610.08381v1 Announce Type: new Abstract: Human video offers a scalable source of robot demonstrations, yet most human-to-humanoid retargeting methods assume a legged robot with human-like kinem

safetyarxiv-cs-ro

From Local Evidence to Safety Verdicts: Causal Tracing in Vision-Language Models

arXiv:2610.07514v1 Announce Type: new Abstract: A vision-language model may need to combine an image with a prompt to recognize a safety risk that neither reveals alone. Where does this joint safety j