Search: “framework”

Interpretable and Explainable Surrogate Modeling for Simulations: A State-of-the-Art Survey and Perspectives on Explainable AI for Decision-Making

arXiv:2604.14240v1 Announce Type: cross Abstract: The simulation of complex systems increasingly relies on sophisticated but fundamentally opaque computational black-box simulators. Surrogate models p

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Applications

Large Language Models to Enhance Business Process Modeling: Past, Present, and Future Trends

DGX agent

arXiv:2604.14034v1 Announce Type: cross Abstract: Recent advances in Generative Artificial Intelligence, particularly Large Language Models (LLMs), have stimulated growing interest in automating or as

applicationsarxiv-cs-ai

17 Apr 2026

Listening Alone, Understanding Together: Collaborative Context Recovery for Privacy-Aware AI

arXiv:2604.13348v1 Announce Type: new Abstract: We introduce CONCORD, a privacy-aware asynchronous assistant-to-assistant (A2A) framework that leverages collaboration between proactive speech-based AI

researcharxiv-cs-ai

MambaSL: Exploring Single-Layer Mamba for Time Series Classification

arXiv:2604.15174v1 Announce Type: new Abstract: Despite recent advances in state space models (SSMs) such as Mamba across various sequence domains, research on their standalone capacity for time serie

Meituan Merchant Business Diagnosis via Policy-Guided Dual-Process User Simulation

arXiv:2604.15190v1 Announce Type: cross Abstract: Simulating group-level user behavior enables scalable counterfactual evaluation of merchant strategies without costly online experiments. However, bui

safetyarxiv-cs-cl

MemGround: Long-Term Memory Evaluation Kit for Large Language Models in Gamified Scenarios

arXiv:2604.14158v1 Announce Type: new Abstract: Current evaluations of long-term memory in LLMs are fundamentally static. By fixating on simple retrieval and short-context inference, they neglect the

Tutorials

Non-intrusive Learning of Physics-Informed Spatio-temporal Surrogate for Accelerating Design

arXiv:2604.14424v1 Announce Type: new Abstract: Most practical engineering design problems involve nonlinear spatio-temporal dynamical systems. Multi-physics simulations are often performed to capture

tutorialsarxiv-cs-lg

Applications

On the Use of Evolutionary Optimization for the Dynamic Chance Constrained Open-Pit Mine Scheduling Problem

arXiv:2604.13385v1 Announce Type: cross Abstract: Open-pit mine scheduling is a complex real world optimization problem that involves uncertain economic values and dynamically changing resource capaci

applicationsarxiv-cs-ai

Path-Sampled Integrated Gradients

arXiv:2604.14338v1 Announce Type: new Abstract: We introduce path-sampled integrated gradients (PS-IG), a framework that generalizes feature attribution by computing the expected value over baselines

Hardware

Reference-Free Sampling-Based Model Predictive Control

arXiv:2511.19204v3 Announce Type: replace Abstract: We present a sampling-based model predictive control (MPC) framework that enables emergent locomotion without relying on handcrafted gait patterns o

hardwarearxiv-cs-ro

Tutorials

ReSS: Learning Reasoning Models for Tabular Data Prediction via Symbolic Scaffold

arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy

tutorialsarxiv-cs-ai

SciFi: A Safe, Lightweight, User-Friendly, and Fully Autonomous Agentic AI Workflow for Scientific Applications

arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab

agentsarxiv-cs-ai

Secure and Privacy-Preserving Vertical Federated Learning

model-releasesarxiv-cs-ai

arXiv:2604.13474v1 Announce Type: cross Abstract: We propose a novel end-to-end privacy-preserving framework, instantiated by three efficient protocols for different deployment scenarios, covering bot

SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentation

arXiv:2604.15271v1 Announce Type: new Abstract: Reliable uncertainty estimation is critical for medical image segmentation, where automated contours feed downstream quantification and clinical decisio

Towards AI-assisted Neutrino Flavor Theory Design

arXiv:2506.08080v2 Announce Type: replace-cross Abstract: Particle physics theories, such as those which explain neutrino flavor mixing, arise from a vast landscape of model-building possibilities. A

Towards Verified and Targeted Explanations through Formal Methods

arXiv:2604.14209v1 Announce Type: new Abstract: As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that ar

safetyarxiv-cs-lg

Tug-of-War within A Decade: Conflict Resolution in Vulnerability Analysis via Teacher-Guided Retrieval-Augmented Generations

arXiv:2604.14172v1 Announce Type: new Abstract: Large Language Models (LLMs) are essential for analyzing and addressing vulnerabilities in cybersecurity. However, among over 200,000 vulnerabilities we

researcharxiv-cs-cl

Unsupervised Skeleton-Based Action Segmentation via Hierarchical Spatiotemporal Vector Quantization

arXiv:2604.15196v1 Announce Type: new Abstract: We propose a novel hierarchical spatiotemporal vector quantization framework for unsupervised skeleton-based temporal action segmentation. We first intr

safetyarxiv-cs-cv

Adaptive Memory Crystallization for Autonomous AI Agent Learning in Dynamic Environments

arXiv:2604.13085v1 Announce Type: new Abstract: Autonomous AI agents operating in dynamic environments face a persistent challenge: acquiring new capabilities without erasing prior knowledge. We prese

Alignment as Institutional Design: From Behavioral Correction to Transaction Structure in Intelligent Systems

arXiv:2604.13079v1 Announce Type: cross Abstract: Current AI alignment paradigms rely on behavioral correction: external supervisors (e.g., RLHF) observe outputs, judge against preferences, and adjust

safetyarxiv-cs-lg

Beyond Conservative Automated Driving in Multi-Agent Scenarios via Coupled Model Predictive Control and Deep Reinforcement Learning

arXiv:2604.13891v1 Announce Type: new Abstract: Automated driving at unsignalized intersections is challenging due to complex multi-vehicle interactions and the need to balance safety and efficiency.

safetyarxiv-cs-ro

Binomial Gradient-Based Meta-Learning for Enhanced Meta-Gradient Estimation

arXiv:2604.13263v1 Announce Type: new Abstract: Meta-learning offers a principled framework leveraging task-invariant priors from related tasks, with which task-specific models can be fine-tuned on do

CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation

arXiv:2504.21751v4 Announce Type: replace-cross Abstract: Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components

Deep Spatially-Regularized and Superpixel-Based Diffusion Learning for Unsupervised Hyperspectral Image Clustering

arXiv:2604.13307v1 Announce Type: new Abstract: An unsupervised framework for hyperspectral image (HSI) clustering is proposed that incorporates masked deep representation learning with diffusion-base

Defending Your Enterprise When AI Models Can Find Vulnerabilities Faster Than Ever

model-releasesgoogle-cloud-ai

Introduction Advances in AI model-powered exploitation have demonstrated that general-purpose AI models can excel at vulnerability discovery, even without being purpose-built for the task. Eventually,

Applications

Designing synthetic datasets for the real world: Mechanism design and reasoning from first principles

applicationsgoogle-research

This Google Research work presents guidelines for synthetic data mechanism design and provides insights into generating and evaluating synthetic data at scale. The research introduces a reasoning-driv

DiffMagicFace: Identity Consistent Facial Editing of Real Videos

arXiv:2604.13841v1 Announce Type: new Abstract: Text-conditioned image editing has greatly benefitted from the advancements in Image Diffusion Models. However, extending these techniques to facial vid

Tools

Ecom-RLVE: Adaptive Verifiable Environments for E-Commerce Conversational Agents

Ecom-RLVE is a framework for training e-commerce conversational agents using reinforcement learning with verifiable environments that can adapt to different scenarios. The system enables agents to lea

toolshugging-face

Local Ai

From Anchors to Supervision: Memory-Graph Guided Corpus-Free Unlearning for Large Language Models

arXiv:2604.13777v1 Announce Type: new Abstract: Large language models (LLMs) may memorize sensitive or copyrighted content, raising significant privacy and legal concerns. While machine unlearning has

local-aiarxiv-cs-cl

Frozen Forecasting: A Unified Evaluation

arXiv:2507.13942v2 Announce Type: replace Abstract: Forecasting future events is a fundamental capability for general-purpose systems that plan or act across different levels of abstraction. Yet, eval

Goal2Skill: Long-Horizon Manipulation with Adaptive Planning and Reflection

arXiv:2604.13942v1 Announce Type: new Abstract: Recent vision-language-action (VLA) systems have demonstrated strong capabilities in embodied manipulation. However, most existing VLA policies rely on

agentsarxiv-cs-ro

Heuristic Style Transfer for Real-Time, Efficient Weather Attribute Detection

arXiv:2604.13947v1 Announce Type: new Abstract: We present lightweight and efficient architectures to detect weather conditions from RGB images, predicting the weather type (sunny, rain, snow, fog) an

Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models

arXiv:2510.19268v2 Announce Type: replace-cross Abstract: Long-horizon routing tasks of deformable linear objects (DLOs), such as cables and ropes, are common in industrial assembly lines and everyday

IndicDB -- Benchmarking Multilingual Text-to-SQL Capabilities in Indian Languages

arXiv:2604.13686v1 Announce Type: new Abstract: While Large Language Models (LLMs) have significantly advanced Text-to-SQL performance, existing benchmarks predominantly focus on Western contexts and

Learning Class Difficulty in Imbalanced Histopathology Segmentation via Dynamic Focal Attention

arXiv:2604.13479v1 Announce Type: cross Abstract: Semantic segmentation of histopathology images under class imbalance is typically addressed through frequency-based loss reweighting, which implicitly

safetyarxiv-cs-cv

Industry

LeRobot is the unsung hero of open robotics!

LeRobot is an open-source robotics framework or platform that aims to democratize access to robotics development and research. The post suggests it addresses gaps in the robotics field by providing ac

industryclem-delangue--x

LiveClawBench: Benchmarking LLM Agents on Complex, Real-World Assistant Tasks

arXiv:2604.13072v1 Announce Type: new Abstract: LLM-based agents are increasingly expected to handle real-world assistant tasks, yet existing benchmarks typically evaluate them under isolated sources

Tutorials

Nonparametric Sparse Online Learning of the Koopman Operator

arXiv:2405.07432v4 Announce Type: replace-cross Abstract: The Koopman operator provides a powerful framework for representing the dynamics of general nonlinear dynamical systems. However, existing dat

tutorialsarxiv-cs-lg

Out of Context: Reliability in Multimodal Anomaly Detection Requires Contextual Inference

model-releasesarxiv-cs-lg

arXiv:2604.13252v1 Announce Type: new Abstract: Anomaly detection aims to identify observations that deviate from expected behavior. Because anomalous events are inherently sparse, most frameworks are

pi-Play: Multi-Agent Self-Play via Privileged Self-Distillation without External Data

arXiv:2604.14054v1 Announce Type: cross Abstract: Deep search agents have emerged as a promising paradigm for addressing complex information-seeking tasks, but their training remains challenging due t

agentsarxiv-cs-cl

Rare Event Analysis via Stochastic Optimal Control

model-releasesarxiv-cs-lg

arXiv:2604.13213v1 Announce Type: cross Abstract: Rare events such as conformational changes in biomolecules, phase transitions, and chemical reactions are central to the behavior of many physical sys

Local Ai

Rethinking Image-to-3D Generation with Sparse Queries: Efficiency, Capacity, and Input-View Bias

arXiv:2604.13905v1 Announce Type: new Abstract: We present SparseGen, a novel framework for efficient image-to-3D generation, which exhibits low input-view bias while being significantly faster. Unlik

local-aiarxiv-cs-cv

RobotPan: A 360^irc Surround-View Robotic Vision System for Embodied Perception

arXiv:2604.13476v1 Announce Type: cross Abstract: Surround-view perception is increasingly important for robotic navigation and loco-manipulation, especially in human-in-the-loop settings such as tele

Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate

arXiv:2604.13806v1 Announce Type: new Abstract: Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces

Safe and Nonconservative Contingency Planning for Autonomous Vehicles via Online Learning-Based Reachable Set Barriers

arXiv:2509.07464v2 Announce Type: replace Abstract: Autonomous vehicles must navigate dynamically uncertain environments while balancing safety and efficiency. This challenge is exacerbated by unpredi

safetyarxiv-cs-ro

SEDTalker: Emotion-Aware 3D Facial Animation Using Frame-Level Speech Emotion Diarization

arXiv:2604.13335v1 Announce Type: new Abstract: We introduce SEDTalker, an emotion-aware framework for speech-driven 3D facial animation that leverages frame-level speech emotion diarization to achiev

SSD-GS: Scattering and Shadow Decomposition for Relightable 3D Gaussian Splatting

arXiv:2604.13333v1 Announce Type: new Abstract: We present SSD-GS, a physically-based relighting framework built upon 3D Gaussian Splatting (3DGS) that achieves high-quality reconstruction and photore

Synthetic Tabular Generators Fail to Preserve Behavioral Fraud Patterns: A Benchmark on Temporal, Velocity, and Multi-Account Signals

model-releasesarxiv-cs-lg

arXiv:2604.13125v1 Announce Type: new Abstract: We introduce behavioral fidelity -- a third evaluation dimension for synthetic tabular data that measures whether generated data preserves the temporal,