All entries

Constrained-Action AI Remediation for SIEM/XDR via a NeMo-Guardrails Proxy

arXiv:2610.09906v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) for information technology and operational technology share one incident-response problem: a flood of correlated al

safetyarxiv-cs-cl

Source

Human DGX agent

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Constraint Tree Exploration for Learning from Language Feedback

DGX agent

arXiv:2610.09107v1 Announce Type: cross Abstract: Natural-language feedback in interactive learning often explains why an action failed by pointing to violated requirements. Misinterpreting this feedb

agentsarxiv-cs-cl

8 Oct 2026

Contact-Aware Imitation Learning Through Contact Factorization

arXiv:2610.09533v1 Announce Type: new Abstract: Generalizable contact-rich manipulation requires robots to preserve intended task behavior while adapting its physical realization to changing contact c

safetyarxiv-cs-ro

Context-Aware Adaptive Pesticide Spraying for Agricultural Robots under Changing Weather and Terrain Using Vision-Language Models

arXiv:2610.08807v1 Announce Type: new Abstract: Precision pesticide spraying is essential for optimizing application efficiency and ensuring uniform chemical distribution. Spraying performance is infl

researcharxiv-cs-ro

Context-aware Attention-based Gaussian Mixture Models for Vehicular Trajectory Prediction

arXiv:2610.09174v1 Announce Type: new Abstract: Reliable and interpretable trajectory prediction is critical for cooperative and autonomous driving in complex and uncertain environments. This paper in

agentsarxiv-cs-lg

Continual Graph Multi-Agent Reinforcement Learning

arXiv:2610.10302v1 Announce Type: new Abstract: In Continual Multi-Agent Reinforcement Learning (CMARL), agents learn cooperative policies across sequences of tasks, aiming to adapt effectively to new

Continual Learning without Continual Training

arXiv:2610.10379v1 Announce Type: new Abstract: Continual learning requires models to adapt to new domains and new classes while retaining prior knowledge. Many existing methods rely on continued opti

Controllable Crowd Generation through World-Model Planning

arXiv:2610.09438v1 Announce Type: new Abstract: Crowd simulation plays a central role in robot navigation, autonomous driving, and urban planning. For these applications, realistic simulation requires

agentsarxiv-cs-cv

Controlling Dependence in Implicit Generative Models via Spread Mutual Information

arXiv:2610.10021v1 Announce Type: cross Abstract: Mutual information (MI) provides an objective for suppressing or encouraging statistical dependence in implicit generative models. However, direct MI

Convex-Concave Reinforcement Learning

arXiv:2610.09108v1 Announce Type: new Abstract: Policy learning drives many of the most consequential and heavily-invested applications of reinforcement learning today. Yet the core optimization probl

safetyarxiv-cs-lg

COOL: Curiosity-Driven Object Ownership Learning for Personalized Robotic Assistance

arXiv:2610.09358v1 Announce Type: new Abstract: Robots are increasingly expected to provide personalized services in everyday environments. To do so, they must ground natural-language commands such as

agentsarxiv-cs-ro

COPC: Coupled Off-Policy Correction for Asynchronous LLM Reinforcement Learning

arXiv:2610.09597v1 Announce Type: new Abstract: Asynchronous RL accelerates large language model post-training by decoupling rollout generation from optimization, but trains on stale trajectories. Exi

Correspondences as Decisions: JevNexus for Decision-Centric Schema Matching

arXiv:2610.09487v1 Announce Type: cross Abstract: Schema matching increasingly uses generative language models to rerank retrieved column candidates, although the underlying task is a bounded correspo

CoTrace: Data Recipes for Training Terminal Agents with Harness-Model Co-Evolution

arXiv:2610.10426v1 Announce Type: new Abstract: Terminal-agent capability depends jointly on model weights and the runtime harness that formats prompts, binds tools, and handles error recovery. Existi

safetyarxiv-cs-cl

Counterfactual Route Optimization for Gaussian Head Avatar Modeling

arXiv:2610.09791v1 Announce Type: new Abstract: Head avatar modeling requires jointly optimizing multiple objectives with different dominant effects on geometry, appearance, and cross-view consistency

Covariate-dependent Joint Modeling of Multivariate Ordinal Preferences and Its Connections with Comparison Models

arXiv:2610.09070v1 Announce Type: cross Abstract: Multivariate ordinal data along with covariates are commonly collected in problems ranging from alignment of language models with human preferences, a

safetyarxiv-cs-lg

Cross-Domain Pretraining for Steady-State Neural CFD Surrogates

arXiv:2610.10398v1 Announce Type: new Abstract: Neural surrogates for computational fluid dynamics (CFD) have the potential to greatly enhance engineering innovation through accelerating simulation. H

CRT-HMAR: Causal Requirement Tracing-Guided Hierarchical Multi-Agent Regulation for Open-Task-Aware Infrared-Visible Image Fusion

arXiv:2610.09330v1 Announce Type: new Abstract: Infrared and visible (IR-VIS) image fusion integrates complementary multimodal information into a single fused image to support downstream vision tasks.

agentsarxiv-cs-cv

CurveTQ: Rotation-Free Trellis Quantization of LLM Weights via Curvature-Weighted Search

arXiv:2610.09212v1 Announce Type: new Abstract: The best two-bit weight quantizers for large language models, such as QTIP and Proteus, rotate each weight matrix by a random orthogonal transform, whic

Data Reuse in Non-Stationary Learning

arXiv:2610.10340v1 Announce Type: cross Abstract: We consider online learning in non-stationary environments, where the goal is to track an unknown parameter that switches abruptly between a finite se

Dataset Pruning from First Principles: A Label-Free Linear Programming Approach

arXiv:2610.10347v1 Announce Type: cross Abstract: Dataset pruning reduces a large training set to a representative subset while preserving model performance. Existing geometry-based methods typically

Decentralized SGD under Heavy-Tailed Noise: Optimal Convergence Rates and the Role of Gradient Clipping

arXiv:2610.10527v1 Announce Type: cross Abstract: Heavy-tailed noise has been widely observed in modern machine learning, motivating the use of methods like gradient clipping and normalization. While

Decoding Neural Population Dynamics through Robotic Analog

arXiv:2610.09977v1 Announce Type: new Abstract: Animal evidence shows that precise voluntary movements arise from rotational neural population dynamics in motor cortex, but their physical effects rema

researcharxiv-cs-ro

Decoupled Optimization for Teacher-Student Semi-Supervised Learning via a Pioneer Student

arXiv:2610.09609v1 Announce Type: new Abstract: Semi-supervised learning (SSL) relies on two core mechanisms: self-training under the Teacher-Student (T-S) framework and joint optimization of labeled

Decoupling Exploration from Optimization in RLVR

arXiv:2610.10536v1 Announce Type: cross Abstract: Modern language models undergo reinforcement learning with verifiable rewards (RLVR) on top of already-trained checkpoints. A key promise of RLVR is t

safetyarxiv-cs-cl

Decoupling Logic from Persona: Structural Immunity of Edge LLM Agents to Context Pollution

model-releasesarxiv-cs-cl

arXiv:2610.09772v1 Announce Type: new Abstract: Small language-model agents on edge devices must hold a persona and reason correctly at once, inside one context window that fills with conversational h

Tutorials

Deep Learning-Based Tri-Hybrid Multi-User MIMO Precoding: The Blessing of EM-Reconfigurable Antennas

arXiv:2609.39167v1 Announce Type: cross Abstract: Electromagnetic (EM)-reconfigurable antennas provide multiple candidate radiation patterns per element, thereby introducing an additional EM-domain de

tutorialsarxiv-cs-lg

Deep Learning for Longitudinal Medical Imaging: A Scoping Review

arXiv:2610.08838v1 Announce Type: cross Abstract: Longitudinal medical imaging analysis is a cornerstone of modern medical practice and patient care. Deep learning applied to longitudinal imaging offe

DeepTopoClustering: Unsupervised Derivation of Surface Process Taxonomy from 4D Point Clouds for Topographic Monitoring

arXiv:2610.09860v1 Announce Type: new Abstract: 4D point clouds acquired by permanent laser scanning (PLS) enable accurate high-frequency monitoring of surface change in dynamic topographic environmen

DeltaRepresentation: Geometry Supervised Representation Learning of Phenotypes via Counterfactual Reasoning for Medical VLMs

arXiv:2610.10286v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have shown increasing potential for radiological image interpretation. Medical VLMs encode radiological images int

safetyarxiv-cs-cv

DeltaSplat: Iterative Gaussian Refinement for Pose-Free Feed-Forward 3D Gaussian Splatting

arXiv:2610.09853v1 Announce Type: new Abstract: Pose-free feed-forward 3D Gaussian Splatting (3DGS) reconstructs a scene from sparse, unposed images in a single network pass, removing the need for cam

Local Ai

{Delta}WAM: Distilling Action Tangent Fields into World Action Models

arXiv:2610.09734v1 Announce Type: new Abstract: World Action Models (WAM) improve robot policies by augmenting sparse action supervision with dense future prediction. However, much of the predictable

local-aiarxiv-cs-ro

Hardware

Democratizing MoE inference on commodity GPUs with CoMoE

arXiv:2610.09424v1 Announce Type: cross Abstract: Deploying Mixture-of-Experts (MoE) models relies heavily on Expert Parallelism, which generates intense inter-GPU communication. Consequently, state-o

hardwarearxiv-cs-lg

DenoFlow: Flow Matching for SSVEP Denoising under Real Physiological Artifacts

arXiv:2610.08817v1 Announce Type: new Abstract: Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly steady-state visual evoked potential (SSVEP) systems, are highly vulne

Hardware

Denoising Blocks, Not Tokens: Efficient Compressed Continuous Diffusion with Branching Token Realization

arXiv:2610.09311v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text through iterative parallel refinement, offering the potential for higher throughput than autoregressive (

hardwarearxiv-cs-lg

Tutorials

Depth-to-RGB: Repurposing a Frozen Depth Estimator for Geometry-Guided Compositing

arXiv:2610.09125v1 Announce Type: new Abstract: Reference-based object compositing inserts or replaces an object using a background image, a reference image, and a 2D compositing mask. These inputs gu

tutorialsarxiv-cs-cv

Derivative Gaussian Processes on a Two-Direction Budget

arXiv:2610.10428v1 Announce Type: cross Abstract: Gradient observations promise more accurate Gaussian process (GP) surrogates, but the cost of incorporating them has long stood in the way of realizin

Design of a Fully Actuated 4-DOF Robotic Finger With Joint-Specific Hybrid Remote Actuation

arXiv:2610.10180v1 Announce Type: new Abstract: This paper presents a fully actuated 4-DOF robotic finger using a joint-specific hybrid remote-actuation architecture. The metacarpophalangeal (MCP) joi

agentsarxiv-cs-ro

Design optimization of tendon-driven robots considering tendon wrapping and shortcut

arXiv:2610.09645v1 Announce Type: new Abstract: This study proposes a multi-objective optimization method for tendon-driven arm design, addressing the inherent trade-off between joint torque and arm t

researcharxiv-cs-ro

Despite Instructions: Frontier Agents Improvise Covert Channels at Test Time

model-releasesarxiv-cs-cl

arXiv:2609.32701v2 Announce Type: replace-cross Abstract: In security-sensitive applications, language-model agents are often required to coordinate without disclosing confidential information. Yet re

Detecting Adversarial Images through Response Profiles of Vision-Language Models

arXiv:2610.10436v1 Announce Type: new Abstract: Adversarial perturbations can alter the predictions of frozen vision-language models (VLMs) while leaving their confidence and image--text similarity pa

Detecting Control and Response Events for AI-Enabled Radio Access Networks

arXiv:2606.06459v2 Announce Type: replace Abstract: Next-generation wireless networks are moving toward the use of concurrent AI-driven control functions to optimize different objectives, particularly

Dialect-Robust Speech Language Models with Synthetic Pseudo-Dialect Augmentation

arXiv:2610.09321v1 Announce Type: new Abstract: Speech Language Model (SLM) performance often degrades on dialects due to data scarcity. Conventional text-to-speech (TTS) augmentation struggles to cov

researcharxiv-cs-cl

Differential Refresh Policies for Models Trained on Lagging Data Snapshots: From a Single-Age Equivalence Limit to an Optimal Per-Segment Allocation

arXiv:2610.09519v1 Announce Type: new Abstract: Production machine-learning models are derived artifacts of time-bounded training snapshots: a deployed model is a materialized view over a training cut

safetyarxiv-cs-lg

Diffusion-Generated Image Watermarking: A Two-Axis Taxonomy and Three Protocol-Bounded Case Studies

model-releasesarxiv-cs-cv

arXiv:2610.09755v1 Announce Type: new Abstract: Watermarking diffusion-generated images requires balancing provenance signals with image quality, robustness, and computational cost. This work organize

Local Ai

Directed Temporal Representations for Offline Visual Control

arXiv:2610.08960v1 Announce Type: new Abstract: Predictive world models provide compact visual representations for control. Control requires a latent geometry aligned with temporal reachability rather

local-aiarxiv-cs-lg

Directional Evidence Guided Search-Space Reduction for Exact DAG Learning

arXiv:2610.09136v1 Announce Type: new Abstract: Learning a directed acyclic graph (DAG) from observational data is a challenging combinatorial problem due to the exponential growth in the number of ca

Tutorials

DisParQ: Self-Supervised Part Concepts for Interpretable Vision Foundation Models

arXiv:2610.09802v1 Announce Type: new Abstract: Concept-based vision models represent images through an intermediate layer of human-inspectable concepts, so what a model relies on can be traced to tho

tutorialsarxiv-cs-cv