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CLNO: Conservative Local Neural Operator for Compressible Flow Prediction

arXiv:2610.16040v1 Announce Type: cross Abstract: We propose a conservative local neural operator (CLNO) for accurate and generalizable autoregressive prediction of compressible flows. Building upon t

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Tutorials

CloneOT: predicting clone-specific perturbation responses with lineage-supervised neural inverse optimal transport

DGX agent

arXiv:2610.16093v1 Announce Type: cross Abstract: Predicting single-cell perturbation responses requires mapping between two unpaired populations of cells measured before and after the perturbation. O

tutorialsarxiv-cs-lg

14 Oct 2026

Closing the Estimation Gap: Training-Free Transductive Inference for Cross-Domain Few-Shot Action Recognition

arXiv:2610.18209v1 Announce Type: new Abstract: Cross-domain few-shot action recognition (CD-FSAR) aims to recognise unseen action classes in a target domain from a handful of labelled videos. Despite

ClothAtlas: Joint Garment Identification and State Estimation under Self-Occlusion

arXiv:2610.16293v1 Announce Type: new Abstract: Garment manipulation requires inferring both garment identity and complete configuration from partial, self-occluded observations. This creates a chicke

Applications

ClothCode: Generative Modeling for Garment State Estimation and Dynamics Prediction

arXiv:2610.14200v1 Announce Type: cross Abstract: We introduce ClothCode, a unified generative framework for garment state estimation and action-conditioned dynamics prediction in a shared discrete co

applicationsarxiv-cs-cv

Cloud CISO Perspectives: New Gemini Notebook can help CISOs and policymakers prepare for PQC

model-releasesgoogle-cloud-ai

Welcome to the first Cloud CISO Perspectives for October 2026. Today, Stephanie Kiel explains the latest on our approach to post-quantum cryptography, and shares a new tool to help CISOs and executive

Co-Creative Learning via Metropolis-Hastings Interaction between Humans and AI

arXiv:2506.15468v2 Announce Type: replace-cross Abstract: We propose co-creative learning as a novel paradigm where humans and AI, i.e., biological and artificial agents, mutually integrate their part

Co-DSL: Human-LLM Co-design of Reusable Spatial Concepts for Layout Generation

arXiv:2610.15290v1 Announce Type: cross Abstract: We present Co-DSL, a framework in which users and LLMs co-design reusable spatial concepts for layout generation. In the first stage, our system allow

Coarse-Graining Recursive Expert Computation: Continuation-Relative Interfaces and Failure Modes

arXiv:2610.14413v1 Announce Type: new Abstract: Computational coarse-graining aims to replace a sequence of updates with a cheaper module while preserving task performance. We present a continuation-r

CoCA: Criterion-Aware Credit Assignment for Rubric-Based Reinforcement Learning

arXiv:2610.17733v1 Announce Type: new Abstract: Rubric-based reinforcement learning (RL) evaluates responses against explicit criteria to construct rewards, offering a viable way to train large langua

Code-Interactive Visual Reasoning for Financial Candlestick Understanding

model-releasesarxiv-cs-cv

arXiv:2610.16587v1 Announce Type: new Abstract: Financial candlestick understanding requires locating visual elements, aligning them across trading dates and panels, and combining observations through

Code-Switching Detection via Language-Selective Dimensions in Speech Foundation Models

researchapple-ml-research

Code-switching (CS), the alternation between languages within an utterance, is common in multilingual speech but underrepresented in pretraining corpora. Increasing CS coverage requires finding releva

Code2Worlds-2: Physically Plausible Agent Harness for Embodied World Simulation

model-releasesarxiv-cs-cv

arXiv:2610.17651v1 Announce Type: cross Abstract: Recent coding large language models (LLMs) can synthesize dynamic 4D worlds from natural language, but the resulting content remains a visual artifact

CodeLift: Your Test Suite Is Secretly a Dense SWE Curriculum

arXiv:2610.17224v1 Announce Type: new Abstract: The pass-all-test binary reward has become a standard recipe for training software engineering agents, but its sparsity eliminates difference of partial

CodeWalk: Generating Coding Benchmarks by Walking a Problem Graph

arXiv:2610.15345v1 Announce Type: new Abstract: High-quality coding problems are expensive to collect. Benchmarks such as SWE-bench rely on substantial human curation, while synthetic alternatives typ

Tutorials

Coding LLMs Can Be Harnessed to Learn Interpretable Models from Data

arXiv:2610.14006v1 Announce Type: new Abstract: Since compact, interpretable classifiers correspond to simple programs, it is natural to ask if LLM-based coding agents can be used to learn interpretab

tutorialsarxiv-cs-lg

Agents

CoEvoke: Evoking Multi-Agent Collaboration for Trajectory Collection

arXiv:2610.14021v1 Announce Type: new Abstract: Training multi-agent collaboration requires trajectories of checking, feedback, and repair, yet task-solving rollouts may end in immediate approval or r

agentsarxiv-cs-lg

Agents

CoLA: Multi-VLA Coordination via Learned Adapters

arXiv:2610.15337v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are typically deployed as isolated single-agent policies. When several such agents share a workspace, they can coo

agentsarxiv-cs-lg

Collaborative Planning for UAV-UGV Teams under Operational Constraints via Masked Error-bounded Neuro-Symbolic Diffusion

arXiv:2610.18850v1 Announce Type: new Abstract: Collaborative planning under operational constraints is essential for heterogeneous robot teams in large-scale missions. Unmanned Aerial Vehicles (UAVs)

safetyarxiv-cs-ro

Colored Graph Signal Diffusion Models

arXiv:2610.17282v1 Announce Type: cross Abstract: Standard diffusion processes with isotropic noise corruption are not spectrally neutral. They inherit a coarse-to-fine generation hierarchy from the n

Comparative Study of Canvas- and Coordinate-Based Geometry-Conditioned Neural Networks for Real-Time Prediction of Indoor Environments with Varying Room Dimensions

arXiv:2610.15885v1 Announce Type: cross Abstract: Computational fluid dynamics (CFD) is computationally expensive for iterative building design. Deep learning surrogates offer faster predictions, but

Applications

Comparing GenAI to Machine Learning and Manual Review for eDiscovery

arXiv:2610.16925v1 Announce Type: new Abstract: Keeling et al. [Keeling2026Generative] report on a case study recently conducted by Redgrave LLP in which they assert that Relativity's Generative AI Re

applicationsarxiv-cs-lg

COMPASS: Contextual Moment Prior Alignment for Generalizable AIGI Detection

arXiv:2610.18034v1 Announce Type: new Abstract: Generalizable AI-generated image (AIGI) and deepfake detection remain challenging due to the asymmetry phenomenon, where adaptation to limited training

safetyarxiv-cs-cv

COMPASS: Membership Inference Attack Against Vision Large Language Models via Adaptive Noise Calibration

arXiv:2610.17332v1 Announce Type: new Abstract: Vision large language models (VLLMs) are deployed in privacy-sensitive domains, raising training-data exposure concerns. Existing gray-box membership in

Hardware

Competition Domains Matter: Selective Head Globalization for Training-Free Sparse Attention in Video Diffusion Transformers

arXiv:2610.14672v1 Announce Type: new Abstract: Training-free sparse attention is a practical route to efficient video diffusion transformer inference, yet existing methods typically fix the competiti

hardwarearxiv-cs-cv

Competitive Task Allocation with Temporal Proposal Windows and Improved Artificial Potential Fields for Dual-Arm Industrial Manipulation

arXiv:2610.15763v1 Announce Type: new Abstract: Modern industrial automation demands autonomous collaborative systems capable of coordinated manipulation in workspaces with heterogeneous object arrang

safetyarxiv-cs-ro

Complexity Dependent Error Rates for Physics-informed Statistical Learning via the Small-ball Method

arXiv:2510.23149v2 Announce Type: replace-cross Abstract: Physics-informed statistical learning (PISL) integrates empirical data with physical knowledge to enhance the statistical performance of estim

Composable Dynamics for Cooperative Humanoids: A RoboCompiler Extension

arXiv:2610.14237v1 Announce Type: new Abstract: Physically connected humanoids need consistent dynamics for internal actuator loops, inter-robot forces, and changing ground supports. We extend RoboCom

researcharxiv-cs-ro

Compositional Average Velocity Modeling for Efficient Diffusion Offline Reinforcement Learning

arXiv:2610.14941v1 Announce Type: new Abstract: Diffusion-based policies have recently emerged as a powerful paradigm for offline reinforcement learning, but their reliance on multi-step denoising int

Compositional Concepts Erasing: Disentangling Object-Style via Domain Manifold Unlearning

arXiv:2610.14514v1 Announce Type: new Abstract: Diffusion models pose significant risks regarding the generation of illicit content and copyright violations. This has catalyzed the development of mach

Compositional RL: Evaluating and Training LLMs for Collaborative Reasoning

arXiv:2610.17456v1 Announce Type: cross Abstract: Language models are often evaluated alone but increasingly deployed together, routed between, made to debate, ensembled, or collaboratively trained. F

Tutorials

Comprehensive Workflow for Uncertainty-Aware Ionic Liquid Solvent Discovery

arXiv:2610.17171v1 Announce Type: cross Abstract: Designing synthesizable materials with targeted properties remains one of the central objectives in materials sciences. Ionic liquids (ILs) are well s

tutorialsarxiv-cs-lg

Applications

Compression Through Time: An Interplay of Separability, Stationarity and Capacity

arXiv:2610.16660v1 Announce Type: new Abstract: Information-theoretic and geometric compression have been widely studied as possible explanations for generalization. Yet their temporal dynamics in rec

applicationsarxiv-cs-lg

Compute-optimal data scaling for neural surrogates via multi-fidelity training

arXiv:2610.17221v1 Announce Type: new Abstract: Neural surrogates for Partial Differential Equations (PDEs) are usually trained on synthetic data from numerical simulators. As models grow and scaling

Compute-Optimal Scaling Laws for Spiking Language Models

arXiv:2610.15146v1 Announce Type: new Abstract: Spiking neural networks target energy-efficient language modeling through sparse, binary activations, but the efficiency-accuracy tradeoff of spiking la

Concealed Handgun Detection using WiFi Signals

arXiv:2610.18736v1 Announce Type: new Abstract: While conventional camera-based surveillance systems and metal detectors can provide a sufficient level of security when used appropriately, they have f

Concentration inequalities for leave-one-out cross validation

arXiv:2211.02478v4 Announce Type: replace-cross Abstract: In this article we prove that estimator stability, together with a gradient-growth condition on the expected fitted loss, is enough to provide

Agents

ConDenseDrive: Knowledge-Dense, Token-Sparse Visual Encoder for End-to-End Autonomous Driving

arXiv:2610.16908v1 Announce Type: new Abstract: End-to-end driving requires rich spatiotemporal representations to support scene understanding and trajectory planning under strict latency constraints.

agentsarxiv-cs-cv

Conditional Multi-Event Temporal Grounding in Long-Form Video

model-releasesarxiv-cs-cv

arXiv:2606.15320v2 Announce Type: replace Abstract: Multimodal large language models have made rapid progress in video temporal grounding, yet real-world applications routinely require localizing ever

Confine to the Task, Anchor the Rest: Concept-Guided Retention Regularizer for Parameter-Efficient Fine-Tuning

arXiv:2610.17713v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) has been widely used, yet the adapted model suffers catastrophic forgetting of pre-trained knowledge. While most

Conformal Sequential Decision Making With Cost and Sublinear Policy Regret Guarantees

arXiv:2610.15011v1 Announce Type: new Abstract: Automated decision makers, such as AI agents that control robots or network devices, must often satisfy hard cost constraints while maintaining competit

ConformalGuard: False-Positive-Controlled Action Gating for LM Classifiers

arXiv:2610.14365v1 Announce Type: new Abstract: Language model classifiers are increasingly deployed for high-stakes decisions such as phishing screening, content moderation, and fraud triage, yet val

Congrats to @lightseekorg on the impressive TokenSpeed results! 🚀 Great to see Qwen3.8-Flash-Next reaching 685 output tokens/s per user on …

Congrats to @lightseekorg on the impressive TokenSpeed results! 🚀 Great to see Qwen3.8-Flash-Next reaching 685 output tokens/s per user on Nvida GPUs. Excited to see the community unlock more of Qwen’

model-releasesqwen--x

Local Ai

ConicFlow: constrained Inference-time optimal control for flow matching models

arXiv:2610.14307v1 Announce Type: cross Abstract: We propose ConicFlow, which frames constrained sampling from a flow matching model at inference time as an optimal control problem that balances devia

local-aiarxiv-cs-cv

Connect your ChatGPT and Claude subscriptions to Grok @bot with the prompt below (@elonmusk approved): Connect my Claude and ChatGPT subscri…

model-releaseselon-musk--x

Connect your ChatGPT and Claude subscriptions to Grok @bot with the prompt below (@elonmusk approved): Connect my Claude and ChatGPT subscriptions so all of my bots can use them. 1. On your computer,

Constant-Depth Rational-Weight GNNs and their Connection to Schanuel's Conjecture

arXiv:2610.16993v1 Announce Type: new Abstract: A landmark result states that the expressive power of graph neural networks (GNNs) is bounded from above by the 1-dimensional Weisfeiler-Leman (1-WL) te

Constrained Contextual Bandits with Adversarial Contexts

arXiv:2605.06190v2 Announce Type: replace Abstract: We study constrained contextual bandits with adversarial contexts, where each action yields a random reward and incurs a random cost. The conditiona

Constrained Differentiable Policy Learning for Safe Quadrotor Navigation

arXiv:2610.16119v1 Announce Type: new Abstract: Differentiable simulation enables efficient policy optimization through analytic gradients, yet safety is commonly incorporated as a weighted penalty, r

safetyarxiv-cs-ro