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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

safetyarxiv-cs-lg

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

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DGX agent

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'

safetyarxiv-cs-ro

14 Oct 2026

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

Agents

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

researcharxiv-cs-cv

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

researcharxiv-cs-cv

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

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

CoPlanVLM: Coordinated Path Planning for a Robot Team using Vision Language Models

arXiv:2610.14341v1 Announce Type: new Abstract: We present CoPlanVLM, which uses a Vision Language Model (VLM) to translate a single natural-language instruction and image into coordinated paths for a

researcharxiv-cs-ro

CopyQuad: Quadrupedal Skill Transfer from a Single Side-View Video Without a Depth Model

arXiv:2610.16737v1 Announce Type: cross Abstract: Video-to-robot pipelines for quadrupedal imitation insert a learned lifting stage, either a monocular depth model or a per-clip 3D reconstruction, to

corporate espionage they say

openai staff are out there turning the office into a stealth game, while my biggest security threat is letting codex, claude code and sumus loose on a test branch without read only permissions enabled

model-releasesr-chatgpt

Correcting or Continuing? What On-Policy Distillation Learns from Student Errors

arXiv:2610.18011v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on its own rollouts under a frozen teacher, mitigating the distribution mismatch of off-policy supervision

Correlation-Aware Reconstruction for Multivariate Time Series Anomaly Detection

arXiv:2610.15250v1 Announce Type: new Abstract: Reconstruction-based detectors for multivariate time series anomaly detection typically learn a single entangled representation of normal behavior and f

CoSMO: Conformal Semantic Mapping for Open-World Safe Robot Navigation

arXiv:2610.18321v1 Announce Type: new Abstract: Safe autonomous navigation requires not only geometric obstacle avoidance but also semantic awareness. Different object categories demand different safe

safetyarxiv-cs-ro

CoTL: Compact Token Learning for 3D Scene Representation

arXiv:2610.18446v1 Announce Type: new Abstract: We present CoTL, a framework that learns a compact set of tokens that preserves scene geometry and appearance from unposed multi-view images. Our encode

researcharxiv-cs-cv

Counterfactual Certification for Sequential Unlearning with Long-Run Performance Guarantees

arXiv:2610.17993v1 Announce Type: new Abstract: Certified machine unlearning ensures the proximity between the unlearned model and a model retrained without the data to be forgotten. Extending this fr

Counterfactual Rollouts for Offline Contrastive Goal-Conditioned Reinforcement Learning

arXiv:2610.14953v1 Announce Type: new Abstract: Contrastive reinforcement learning (CRL) learns goal-conditioned values by associating state--action pairs with the states subsequently reached, assumin

Counting with Attention and LayerNorm: Norm Scaling and Representation Geometry

arXiv:2610.16653v1 Announce Type: new Abstract: Counting is a simple task on which transformers can nevertheless fail at long sequence lengths. We study the cost of counting in a single attention laye

Applications

CowCare: A Unified Visual Framework for Viewpoint-Robust Cattle Tracking and Spatiotemporal Heat-Stress Analysis

arXiv:2610.15012v1 Announce Type: new Abstract: Reliable individual monitoring is essential for dairy cattle welfare and early heat stress detection in Precision Livestock Farming (PLF). However, tran

applicationsarxiv-cs-cv

Tutorials

Cross-Embodiment Affordance Transfer for Robotic Manipulation

arXiv:2610.18194v1 Announce Type: new Abstract: Robotic manipulation systems commonly learn object affordances from human-annotated datasets, which reflect interaction possibilities for a human hand r

tutorialsarxiv-cs-ro

Cross-Market Meta-Learning for Electricity Price Forecasting

arXiv:2610.17387v1 Announce Type: new Abstract: Day-ahead (DA) electricity price forecasting is usually posed per market, with a separate model fitted to each grid's own history. This caps accuracy: s

Cross-Material Magnetic Core Loss Prediction via Operating-Condition Matching and Partial Optimal Transport

arXiv:2610.14964v1 Announce Type: new Abstract: Cross-material magnetic core loss prediction requires adapting to new material responses with limited measurements. Global feature alignment overlooks d

safetyarxiv-cs-lg

Cross-Subject and Cross-Montage EEG Transfer Learning via Individual Tangent Space Alignment and Spatial-Riemannian Feature Fusion

arXiv:2508.08216v2 Announce Type: replace Abstract: Personalised music-based interventions offer a powerful means of supporting motor rehabilitation by dynamically tailoring auditory stimuli to provid

safetyarxiv-cs-lg

Tutorials

Cross-View Time-Frequency Diffusion for Extreme-Aware Time-Series Generation

arXiv:2610.17407v1 Announce Type: new Abstract: Generating realistic time-series requires faithfully reproducing rare but high-impact extreme events. Existing approaches often rely on specialized repr

tutorialsarxiv-cs-lg

Crossing the Threshold: How OpenAI and Anthropic Approach Autonomy and Safety in Financial Agents

At AI Engineer New York, OpenAI and Anthropic presented how to give financial agents useful autonomy while keeping consequential decisions under control. The consensus was that safe autonomy depends o

safetylatent-space

CrossMean: Model Merging by Pairing Merged and Expert Activations

arXiv:2610.14762v1 Announce Type: new Abstract: Model merging combines fine-tuned experts into one network without retraining, and closed-form methods compute each merged layer from statistics of its

CrossPortrait: Cross-Species Portrait Animation via Adversarial Motion Alignment

arXiv:2610.17532v1 Announce Type: new Abstract: Cross-species portrait animation, which aims to animate a source portrait of species A using a driving video of species B, is particularly challenging d

Local Ai

CryoTracer: A Synthetic-to-Real System for Filament Instance Tracing in Cryo-EM

arXiv:2610.18696v1 Announce Type: new Abstract: Particle picking in cryo-electron microscopy is commonly formulated as an object-detection problem in which individual particles are represented by boun

local-aiarxiv-cs-cv

CryptoFlowBench: Benchmarking Multi-Hop Reasoning on Blockchains for Cryptocurrency Fund Tracing

arXiv:2610.16449v1 Announce Type: cross Abstract: Pseudonymous accounts and complex smart-contract ecosystems substantially hinder the tracing of illicit cryptocurrency fund flows. Existing Graph Neur

cuda, hip: GDN chunked kernel by am17an · Pull Request #29353 · ggml-org/llama.cpp

model-releasesr-localllama

Performance on Model Prompt tokens master tok/s pr tok/s Change RTX PRO 6000 Blackwell Qwen3.5-35B-A3B-Q8_0 2048 13,653.58 16,459.56 +20.6% RTX PRO 6000 Blackwell Qwen3.5-35B-A3B-Q8_0 4096 14,090.26 1

D-World: An Explicit World-Language-Action Model with Recursive Self-Improvement under Dual Control

model-releasesarxiv-cs-ro

arXiv:2610.17114v1 Announce Type: new Abstract: Frontier large language models (LLMs) now reason about space well enough to program robots, yet the world models behind robot policies are implicit, hel

D^{2}-VPR: A Parameter-efficient Visual-foundation-model-based Visual Place Recognition Method via Knowledge Distillation and Deformable Aggregation

model-releasesarxiv-cs-cv

arXiv:2511.12528v5 Announce Type: replace Abstract: Visual Place Recognition (VPR) aims to determine the geographic location of a query image by retrieving its most visually similar counterpart from a

DASS: A Solver-Adaptable Dynamic Auxiliary Search Strategy for Symbolic Regression

arXiv:2610.16812v1 Announce Type: new Abstract: Symbolic regression (SR) aims to discover interpretable mathematical expressions from data and plays a key role in scientific discovery. However, existi

Data-Centric Recursive Self-Improvement for Navigation via Policy-Synchronized Language-Action Dual Bootstrapping

arXiv:2610.15782v1 Announce Type: new Abstract: Vision-language navigation requires agents to follow natural-language instructions to reach target locations, making high-quality language supervision e

Data-Free Continual Learning for World Action Model with Rectified Generative Replay

arXiv:2610.18038v1 Announce Type: cross Abstract: World action models (WAMs) built on pretrained video generation models adapt quickly to new robotic tasks, but they forget previously learned tasks un

Data Free Training of Diffusion Models for Lattice Field Theories

arXiv:2610.18863v1 Announce Type: cross Abstract: Sampling equilibrium field configurations remains a major computational bottleneck in lattice field theory, motivating the development of generative s

Data-Topology Compatibility Enables Personalization in Decentralized Learning

arXiv:2610.15126v1 Announce Type: cross Abstract: Decentralized learning must balance collaboration with personalization across heterogeneous agents. This paper studies when cooperation can support st

Agents

Davinci-Tool: Scaling Agentic Tool-Use Supervision with Verifiable Executable Environments

arXiv:2610.16867v1 Announce Type: new Abstract: Reliable agentic tool use requires training data that pair diverse multi-step workflows with executable evidence that the requested outcomes were achiev

agentsarxiv-cs-lg

DC-Flow: Target-Conditioned Cyclic Peptide Design via Delayed-Coupling Flow Matching

arXiv:2610.15391v1 Announce Type: new Abstract: Target-conditioned cyclic peptide design requires coordinating interfacial side chains with macrocyclic closure. Existing end-to-end generators concurre

DDVR-Net: Degradation-Aware Decoupling and Visibility-Guided Restoration for Historical Document Recognition

model-releasesarxiv-cs-cv

arXiv:2610.16956v1 Announce Type: new Abstract: Historical document analysis is crucial for cultural heritage preservation and low-resource language digitization. However, real historical documents of

Decentralized Bandit Learning of Markov Perfect Equilibria

arXiv:2610.14333v1 Announce Type: new Abstract: We study decentralized bandit learning in discounted infinite-horizon, general-sum Markov games with continuous actions. Agents observe the public state