All entries

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

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

CoEvoke: Evoking Multi-Agent Collaboration for Trajectory Collection

DGX agent

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

14 Oct 2026

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)

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

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

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

Constrained Diffusion Models with Primal-Dual Inference

arXiv:2606.17192v2 Announce Type: replace Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimi

Constraint-Decomposed Impedance Control from Generative Policy for Articulated Object Manipulation

arXiv:2610.16316v1 Announce Type: new Abstract: Articulated object manipulation tasks such as opening doors, tightening bolts, and pulling drawers impose kinematic constraints on a robot end-effector'

Contact Trajectory Prompting: In-Context Transfer of Contact-Rich Behaviors from a Single Demonstration

model-releasesarxiv-cs-ro

arXiv:2610.18848v1 Announce Type: new Abstract: In-context robot learning enables robots to acquire new behaviors from demonstrations without test-time parameter updates. However, visual and kinematic

Context-aware Bayesian Fusion for Multimodal Object Detection

arXiv:2610.18741v1 Announce Type: new Abstract: Reliable detection of pedestrians and road users is essential for the safe operation of autonomous vehicles. However, this task becomes increasingly cha

agentsarxiv-cs-cv

Context-Aware Precision Scheduling for Small Language Models

arXiv:2610.15640v1 Announce Type: new Abstract: Small language models (SLMs) used as on-device agents must balance accuracy and latency as their context grows. Mixed precision helps manage this tradeo

Contextual Representation Flow Across Depth in State-Space and Transformer Architectures

arXiv:2510.06640v3 Announce Type: replace-cross Abstract: State Space Models (SSMs) have emerged as efficient, linear-time alternatives to Transformer-Based Models (TBMs) for long-context processing.

Continuous-Time Cloth Dynamics with Physics-Informed Neural ODEs

arXiv:2610.14342v1 Announce Type: new Abstract: We present ContinuousCloth, a continuous-time, physics-informed neural solver for deformable cloth dynamics that enforces a spring--mass ODE within a ne

Local Ai

Contractor Filters

arXiv:2610.18040v1 Announce Type: new Abstract: We introduce Contractor Filters (CFs), a set-membership architecture for nonlinear continuous-time state estimation with bounded uncertainties and spora

local-aiarxiv-cs-ro

Contrastive Covariance Subspaces for Activation Steering

arXiv:2610.14025v1 Announce Type: new Abstract: Activation steering controls large language model behavior by adding a direction to hidden activations during inference. For steering to work well, that

Contrastive learning for video reuse detection

arXiv:2610.17098v1 Announce Type: new Abstract: The incorporation of footage from other sources has long been a concern from a copyright perspective, as such usage can harm the interests of rights hol

Tutorials

Contrastive Linearized Laplace: Loss Geometry, Valid Repairs, and Reliable Cores

arXiv:2610.14875v1 Announce Type: new Abstract: While contrastive learning is widely used to learn deterministic representations, it does not inherently provide estimates of uncertainty. Post-hoc unce

tutorialsarxiv-cs-lg

Contrastive Metric Learning for Point Cloud Segmentation in Highly Granular Detectors

arXiv:2603.23356v2 Announce Type: replace-cross Abstract: We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predict

Controllable Diverse Sampling through Pullback Directions

arXiv:2610.14294v1 Announce Type: cross Abstract: Conditional diffusion models can generate high-quality images that align closely with a given prompt. However, samples generated from different random

safetyarxiv-cs-cv

Convergence-Rate-Guided Algorithm Design of Expected Improvement for Continuous Simulation Optimization

arXiv:2610.18434v1 Announce Type: cross Abstract: Expected improvement (EI) based on stochastic kriging (SK) surrogate is widely used in continuous simulation optimization, but unknown heteroscedastic

Convex Chance-Constrained Stochastic Control under Uncertain Specifications with Application to Learning-Based Hybrid Powertrain Control

arXiv:2601.18313v2 Announce Type: replace-cross Abstract: This paper proposes a strictly convex chance-constrained stochastic control framework that accounts for uncertainty in control specifications