Search: “framework”

BAT: Balancing Agility and Stability via Online Policy Switching for Long-Horizon Whole-Body Humanoid Control

arXiv:2604.01064v2 Announce Type: replace Abstract: Despite advances in reinforcement and imitation learning, achieving both precise control and dynamic whole-body behaviors in long-horizon tasks rema

safetyarxiv-cs-ro

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Safety

Behavioral Safety Assessment towards Large-scale Deployment of Autonomous Vehicles, Part I: Methodology

DGX agent

arXiv:2610.08450v1 Announce Type: new Abstract: Autonomous vehicles (AVs) have significantly advanced in real-world deployment in recent years, yet safety continues to be a critical barrier to widespr

safetyarxiv-cs-ro

7 Oct 2026

Beyond Refusal Patterns: Safe-Role Internalization for Robust and Generalizable LLM Safety Alignment

arXiv:2610.07023v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to jailbreak attacks that elicit harmful or unsafe outputs. Exi

Beyond the Embedding Bottleneck: Adaptive Retrieval-Augmented 3D CT Report Generation

model-releasesarxiv-cs-cv

arXiv:2603.15822v2 Announce Type: replace Abstract: Automated radiology report generation from 3D CT volumes often suffers from incomplete pathology coverage. We provide empirical evidence that this l

Beyond Training from Scratch: Foundation Models for Data-Efficient and Generalizable Cardiac MRI Reconstruction

model-releasesarxiv-cs-cv

arXiv:2610.08109v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging reconstruction aims to recover high-quality images from undersampled acquisitions, enabling faster scans while preser

Beyond Waypoint Regression: Query-Based Cost Learning over Reachable Ego Futures for End-to-End Driving

arXiv:2610.08123v1 Announce Type: cross Abstract: End-to-end planners based on waypoint regression achieve strong open-loop accuracy, but they primarily learn to mimic expert geometry and remain diffi

Calibrated Answers About Randomized Trials From a 4-Billion-Parameter Open Model: A Registered Test and a License-Clean Release

model-releasesarxiv-cs-cl

arXiv:2610.07019v1 Announce Type: new Abstract: Fiorillo v0.5 is an open model that answers typed questions with a probability for each answer. Its main specialist reads a randomized trial's article,

Catastrophic Forgetting in Sequential Thermal Anti-UAV Detection: The Role of Scale-Conditioned Gradient Imbalance

arXiv:2610.08315v1 Announce Type: new Abstract: Counter-UAV systems based on thermal infrared detection must stay accurate as operational datasets evolve, yet sequential fine-tuning causes catastrophi

CheckerBench: Can Long-Horizon Agents Synthesize Static-Analysis Checkers?

arXiv:2610.07557v1 Announce Type: cross Abstract: Static-analysis checker synthesis requires agents to interpret a defect specification, inspect a repository, implement analyzer-specific logic, and re

Cite What You Explore: Budget-Aware LLM Reasoning over Medical KGs with Verifiable Evidence

arXiv:2610.07739v1 Announce Type: new Abstract: Post-discharge risk prediction from electronic health records (EHRs) is difficult because many dependencies that link discharge-time observations to dow

Commit While Futures Agree: Consequence-Aware Adaptive Action Chunking for Robot Manipulation

arXiv:2610.07949v1 Announce Type: new Abstract: Action-chunking policies predict multi-step control sequences, but a fundamental question remains: how much of a predicted action chunk should be commit

safetyarxiv-cs-ro

Common-Mode Errors Limit Low-Timestep Deep Spiking Q-Networks

arXiv:2610.07808v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) offer sparse and event-driven computation, making them attractive for energy-constrained reinforcement learning (RL) on

Complementary Supervised and Self-Supervised Representations for Out-of-Distribution Graph Learning

arXiv:2610.07628v1 Announce Type: new Abstract: Out-of-distribution (OOD) generalization remains challenging for graph neural networks (GNNs), as graph distributions can vary substantially across time

Comprehensive Evaluation and Fine-Tuning of Foundational Cell Nuclei Segmentation Models in Renal Pathology

arXiv:2610.07711v1 Announce Type: new Abstract: Accurate nuclei instance segmentation is essential for quantitative renal pathology, yet general-purpose models often struggle with low contrast, dense

Local Ai

Computationally efficient goodness-of-fit tests through kernelized Stein discrepancy

arXiv:2512.20007v3 Announce Type: replace-cross Abstract: Models with intractable normalizing constants are widely used in statistics and machine learning. Assessing the adequacy of such models poses

local-aiarxiv-cs-lg

Constant-Curvature Sliced Gromov-Wasserstein for Heterogeneous Cross-Curvature Alignment

arXiv:2610.07218v1 Announce Type: new Abstract: Recent advances in representation learning have highlighted the utility of constant-curvature models, such as hyperbolic and spherical spaces, for model

Contrastive Learning for Aspect Representation towards Explainable Recommendation

arXiv:2610.07761v1 Announce Type: cross Abstract: In this work, we propose a novel recommendation model, CLARER (Contrastive Learning for Aspect Representation towards Explainable Recommendation) that

CroissantMiner: Automated Extraction and Validation of Croissant Metadata for ML Datasets

arXiv:2610.07132v1 Announce Type: cross Abstract: Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful read

Crop Yield Prediction for Punjab, Pakistan: A Tree-Ensemble and Leaf-Health Prototype, and What Random Validation Hides

arXiv:2610.07059v1 Announce Type: new Abstract: Yield forecasts help planners and farmers decide on inputs, storage and imports, but small agricultural tables can make reported accuracy fail on a new

CtrlCache: Accelerating Interactive Video World Models with Control-Aware Caching

arXiv:2610.08777v1 Announce Type: new Abstract: Interactive video world models need to generate each video chunk efficiently while responding faithfully to user controls. Many systems use chunk-wise a

safetyarxiv-cs-cv

Decide Before You Look: Learning Which Retrieved Memories Deserve Pixels

arXiv:2610.07984v1 Announce Type: cross Abstract: Multimodal assistants answer questions from long-term memories that contain images. After retrieval, each retrieved image reaches the answering model

Decomposition-Guided Curvelet Thresholding for Sharp-to-Soft CT Kernel Conversion

arXiv:2610.07067v1 Announce Type: new Abstract: Image denoising is a crucial task in image processing, focused on improving image quality by minimizing noise while maintaining essential structural ele

Deep Defence on Wheels: A Dual Intrusion Detection System Architecture for Comprehensive In-Vehicle Network Security

arXiv:2610.07489v1 Announce Type: cross Abstract: Increasing connectivity to the outside world and the lack of inbuilt security mechanisms have made legacy intra-vehicular networks vulnerable to cyber

DeepAJM: Deep Association Joint Model for Irregularly Sampled data

arXiv:2610.07388v1 Announce Type: cross Abstract: Joint Models simultaneously model longitudinal and survival outcomes, leveraging patterns in patients' longitudinal trajectory to improve the predicti

Defense-in-Depth for LLMs: Evaluating Memory Gates Against Activation-Induced and Memory-Induced Sycophancy

arXiv:2610.07403v1 Announce Type: new Abstract: Long-term memory allows Large Language Models (LLMs) to maintain personalized context across interactions, but retrieved user history can induce memory-

Deformable CT-US Registration via Anatomy-Aware Implicit Neural Representations

arXiv:2610.08419v1 Announce Type: new Abstract: Slice-to-volume registration between ultrasound (US) and preoperative computed tomography (CT) imaging would enhance many minimally invasive interventio

safetyarxiv-cs-cv

Agents

DHCG: Dynamic Construction of Hierarchical Collaboration Graphs for LLM-Based Multi-Agent Reasoning

arXiv:2610.07835v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orch

agentsarxiv-cs-ai

DIPrune: Task-Aware Token Pruning with Dual Importance for Efficient Multimodal Language Models

model-releasesarxiv-cs-cv

arXiv:2610.08341v1 Announce Type: new Abstract: Recent training-free pruning approaches for Multimodal Large Language Models (MLLMs) effectively cut computational overhead by exploiting visual redunda

Direct Regret Optimization in Bayesian Optimization

arXiv:2507.06529v2 Announce Type: replace Abstract: Bayesian optimization (BO) is a powerful paradigm for optimizing expensive black-box functions. Traditional BO methods typically rely on separate ha

Diverse Motion Customization via Control-based Dynamic Optimization

arXiv:2610.07911v1 Announce Type: cross Abstract: Despite recent advances in video generation, motion customization remains challenging due to content leakage, where appearance attributes from the ref

Do Higher-Order Models Win for Higher-Order Reasons? Rethinking Performance Gains in Hypergraph Learning

arXiv:2610.07981v1 Announce Type: new Abstract: Higher-order models (e.g., hypergraph neural networks) often outperform lower-order baselines on hypergraph learning benchmarks, and their advantages ar

Local Ai

Do I Need the Cloud? Uncertainty-Aware Step-Level Handoff for Small Language Model Agents

arXiv:2610.07816v1 Announce Type: new Abstract: Small language models (SLMs) are attractive as local agent controllers because they reduce remote inference, latency, and deployment footprint, yet stru

local-aiarxiv-cs-ai

Does Muon Need Fine-Grained Spectral Shaping?

arXiv:2610.07497v1 Announce Type: new Abstract: Muon combines current and past gradients into matrix momentum. For M=USigma V^op, the idealized polar update Q=UV^op gives every singular direction the

Dual-Modality Multi-Stage Adversarial Safety Training: Robustifying Multimodal Web Agents Against Cross-Modal Attacks

arXiv:2603.04364v2 Announce Type: replace-cross Abstract: Multimodal web agents that process both screenshots and accessibility trees are increasingly deployed to interact with web interfaces, yet the

Dynamic Alignment and Calibration for Multimodal Learning

arXiv:2610.07928v1 Announce Type: cross Abstract: Dynamic multimodal learning aims to learn robust representations by adaptively modeling information discrepancies across modalities. However, existing

Applications

EgoLAP: Learning from Egocentric Human Data through Language-Action Reasoning

arXiv:2610.08726v1 Announce Type: cross Abstract: Egocentric human data offer a path to scaling robot learning beyond costly robot demonstrations, yet the embodiment gap makes raw human trajectories a

applicationsarxiv-cs-ai

Agents

EIO-Agents: The Missing Semantic Layer for AI Agent Evaluation

arXiv:2610.07675v1 Announce Type: new Abstract: AI agents are entering production in increasingly consequential environments without a shared semantic standard for what their evaluations actually mean

agentsarxiv-cs-ai

Tutorials

ElasticFit: Fit-Aware 3D Object Insertion via VLM Reasoning and Generative Adaptation

arXiv:2610.07460v1 Announce Type: cross Abstract: Inserting objects into existing 3D scenes requires more than selecting a plausible location: the inserted object must also fit local geometry while pr

tutorialsarxiv-cs-ai

EMHO: EMbodied Agent Harness Optimization via Experience Traces

arXiv:2610.08432v1 Announce Type: new Abstract: Improving embodied agents often focuses on optimizing the underlying model through training, while the surrounding agent harness that controls planning,

EnGRICH: Enhancing Generative Reward Modeling with Critiques from Humans

arXiv:2610.05370v2 Announce Type: replace Abstract: Generative reward models (GRMs) are important for LLM optimization. Unlike scalar reward models, GRMs generate natural-language critiques alongside

Enhancing Diffusion Language Models with Autoregressive Post-Training Weights

model-releasesarxiv-cs-lg

arXiv:2610.08108v1 Announce Type: new Abstract: Diffusion language models (dLLMs) have emerged as a promising alternative to autoregressive (AR) language models, offering flexible token-update orders

Agents

Evaluate the Stack, Not the Layer: Do Deterministic and LLM Gates for Agent Actions Fail Independently?

arXiv:2610.07359v1 Announce Type: new Abstract: Runtime gates for agent tool calls are stacked on the assumption that their errors multiply. We test it on 1,119 labelled agent actions from three corpo

agentsarxiv-cs-ai

Event-Driven ML Pipeline Orchestration for Manufacturing: An AWS Industry Experience

arXiv:2610.06890v1 Announce Type: new Abstract: We present an industry experience report on three years of operating an event-driven cloud infrastructure for continuous machine learning training in au

Applications

EVFormer: An Egocentric Vision-EMG Bidirectional Attention Model for Bimanual Hand Pose Estimation

arXiv:2610.06970v1 Announce Type: new Abstract: Egocentric bimanual hand pose estimation is important for virtual interaction, wearable control, and rehabilitation, but visual observations are often d

applicationsarxiv-cs-lg

Evidence-Bound Reasoning: Neuro-Semantic Verification of Biomedical AI in Glioblastoma Radiogenomics

model-releasesarxiv-cs-cl

arXiv:2610.08660v1 Announce Type: new Abstract: Background: Biomedical AI can generate plausible explanations without reliably verifying whether each statement is supported by patient-specific evidenc

Evolutionary One-Step Generators: Fast and Diverse Sampling for Discrete Design

arXiv:2610.08367v1 Announce Type: new Abstract: Several discrete design tasks, such as molecular discovery, require diverse collections of useful candidates at low computational cost. High validity al

Tutorials

ExoBridge: Learning a Bare Hand to Hand-Worn Exoskeleton Mapping through Human Limb Coupling

arXiv:2610.07692v1 Announce Type: new Abstract: Human video offers a scalable source of experience for dexterous robot learning, but obtaining motion and tactile supervision while preserving bare hand

tutorialsarxiv-cs-ro

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