Search: “framework”

Lattice-to-Total Thermal Conductivity Ratio: A Phonon-Glass Electron-Crystal Descriptor for Data-Driven Thermoelectric Design

arXiv:2511.21213v2 Announce Type: replace-cross Abstract: Thermoelectrics (TEs) are promising candidates for energy harvesting with performance quantified by figure of merit, ZT. To accelerate the dis

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Learning from Demonstration with Failure Awareness for Safe Robot Navigation

DGX agent

arXiv:2604.23360v1 Announce Type: new Abstract: Learning from demonstration is widely used for robot navigation, yet it suffers from a fundamental limitation: demonstrations consist predominantly of s

safetyarxiv-cs-ro

28 Apr 2026

LLM-Augmented Traffic Signal Control with LSTM-Based Traffic State Prediction and Safety-Constrained Decision Support

arXiv:2604.23902v1 Announce Type: new Abstract: Traffic signal control is a critical task in intelligent transportation systems, yet conventional fixed-time and rule-based methods often struggle to ad

MuSc-V2: Zero-Shot Multimodal Industrial Anomaly Classification and Segmentation with Mutual Scoring of Unlabeled Samples

arXiv:2511.10047v2 Announce Type: replace Abstract: Zero-shot anomaly classification (AC) and segmentation (AS) methods aim to identify and outline defects without using any labeled samples. In this p

No Test Cases, No Problem: Distillation-Driven Code Generation for Scientific Workflows

model-releasesarxiv-cs-ai

arXiv:2604.23106v1 Announce Type: cross Abstract: Existing multi-agent Large Language Model (LLM) frameworks for code generation typically use execution feedback and improve iteratively using Input/Ou

Safe Navigation in Unknown and Cluttered Environments via Direction-Aware Convex Free-Region Generation

arXiv:2604.23648v1 Announce Type: new Abstract: Convex free regions provide a structured and optimization-friendly representation of collision-free space for robot navigation in unknown and cluttered

Sliding Mode Control for Safe Trajectory Tracking with Moving Obstacles Avoidance: Experimental Validation on Planar Robots

arXiv:2604.24518v1 Announce Type: cross Abstract: This paper presents a unified control framework for robust trajectory tracking and moving obstacle avoidance applicable to a broad class of mobile rob

Solving Nonlinear PDEs with Sparse Radial Basis Function Networks

arXiv:2505.07765v3 Announce Type: replace-cross Abstract: We propose a novel framework for solving nonlinear PDEs using sparse radial basis function (RBF) networks. Sparsity-promoting regularization i

researcharxiv-cs-lg

When PINNs Go Wrong: Pseudo-Time Stepping Against Spurious Solutions

arXiv:2604.23528v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) provide a promising machine learning framework for solving partial differential equations, but their training o

researcharxiv-cs-lg

// Agentic World Modeling // Massive 40-author survey just dropped. Cleanest taxonomy of world models in agent research I've seen. (bookmark…

// Agentic World Modeling // Massive 40-author survey just dropped. Cleanest taxonomy of world models in agent research I've seen. (bookmark it) The paper proposes a 'levels × laws' framework. Three c

agentsdair-ai--x

Controllable Spoken Dialogue Generation: An LLM-Driven Grading System for K-12 Non-Native English Learners

arXiv:2604.22542v1 Announce Type: cross Abstract: Large language models (LLMs) often fail to meet the pedagogical needs of K-12 English learners in non-native contexts due to a proficiency mismatch. T

FlowAnchor: Stabilizing the Editing Signal for Inversion-Free Video Editing

arXiv:2604.22586v1 Announce Type: new Abstract: We propose FlowAnchor, a training-free framework for stable and efficient inversion-free, flow-based video editing. Inversion-free editing methods have

safetyarxiv-cs-cv

V-STC: A Time-Efficient Multi-Vehicle Coordinated Trajectory Planning Approach

arXiv:2604.22196v1 Announce Type: new Abstract: Coordinating the motions of multiple autonomous vehicles (AVs) requires planning frameworks that ensure safety while making efficient use of space and t

260 things we announced at Google Cloud Next '26 – a recap

model-releasesgoogle-cloud-ai

Google Cloud Next ‘26 took place this week in Las Vegas, and the energy was incredible as we welcomed over 32,000 leaders, developers, and partners to explore the Agentic Era with us. Across three key

ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming

model-releasesarxiv-cs-lg

arXiv:2505.05261v3 Announce Type: replace-cross Abstract: Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability remains a cha

Inferring High-Level Events from Timestamped Data: Complexity and Medical Applications

arXiv:2604.21793v1 Announce Type: new Abstract: In this paper, we develop a novel logic-based approach to detecting high-level temporally extended events from timestamped data and background knowledge

VFM^{4}SDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection

arXiv:2604.21502v1 Announce Type: new Abstract: In real-world scenarios, continual changes in weather, illumination, and imaging conditions cause significant domain shifts, leading detectors trained o

safetyarxiv-cs-cv

Vista4D: Video Reshooting with 4D Point Clouds

arXiv:2604.21915v1 Announce Type: new Abstract: We present Vista4D, a robust and flexible video reshooting framework that grounds the input video and target cameras in a 4D point cloud. Specifically,

applicationsarxiv-cs-cv

A Hough transform approach to safety-aware scalar field mapping using Gaussian Processes

arXiv:2604.20799v1 Announce Type: new Abstract: This paper presents a framework for mapping unknown scalar fields using a sensor-equipped autonomous robot operating in unsafe environments. The unsafe

Breaking the Assistant Mold: Modeling Behavioral Variation in LLM Based Procedural Character Generation

arXiv:2601.03396v2 Announce Type: replace Abstract: Procedural content generation has enabled vast virtual worlds through levels, maps, and quests, but large-scale character generation remains underex

Efficient Reinforcement Learning using Linear Koopman Dynamics for Nonlinear Robotic Systems

arXiv:2604.19980v1 Announce Type: new Abstract: This paper presents a model-based reinforcement learning (RL) framework for optimal closed-loop control of nonlinear robotic systems. The proposed appro

Federated Learning over Blockchain-Enabled Cloud Infrastructure

arXiv:2604.20062v1 Announce Type: new Abstract: The rise of IoT devices and the uptake of cloud computing have informed a new era of data-driven intelligence. Traditional centralized machine learning

From Actions to Understanding: Conformal Interpretability of Temporal Concepts in LLM Agents

arXiv:2604.19775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments.

agentsarxiv-cs-ai

What Makes a Good AI Review? Concern-Level Diagnostics for AI Peer Review

arXiv:2604.19998v1 Announce Type: new Abstract: Evaluating AI-generated reviews by verdict agreement is widely recognized as insufficient, yet current alternatives rarely audit which concerns a system

BEAT: Tokenizing and Generating Symbolic Music by Uniform Temporal Steps

arXiv:2604.19532v1 Announce Type: cross Abstract: Tokenizing music to fit the general framework of language models is a compelling challenge, especially considering the diverse symbolic structures in

researcharxiv-cs-ai

Budgeted Online Influence Maximization

arXiv:2604.19672v1 Announce Type: new Abstract: We introduce a new budgeted framework for online influence maximization, considering the total cost of an advertising campaign instead of the common car

Multi-Gait Learning for Humanoid Robots Using Reinforcement Learning with Selective Adversarial Motion Prior

arXiv:2604.19102v1 Announce Type: cross Abstract: Learning diverse locomotion skills for humanoid robots in a unified reinforcement learning framework remains challenging due to the conflicting requir

Pay attention to this one, AI devs. This is particularly interesting if you work with long-horizon terminal agents that often drown in their…

Pay attention to this one, AI devs. This is particularly interesting if you work with long-horizon terminal agents that often drown in their own observations. TACO is a self-evolving framework that au

agentsdair-ai--x

RL-ABC: Reinforcement Learning for Accelerator Beamline Control

arXiv:2604.19146v1 Announce Type: new Abstract: Particle accelerator beamline optimization is a high-dimensional control problem traditionally requiring significant expert intervention. We present RLA

safetyarxiv-cs-lg

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring

arXiv:2604.18835v1 Announce Type: cross Abstract: We propose a scalable, multifactorial experimental framework that systematically probes LLM sensitivity to subtle semantic changes in pairwise documen

STAR-Teaming: A Strategy-Response Multiplex Network Approach to Automated LLM Red Teaming

arXiv:2604.18976v1 Announce Type: new Abstract: While Large Language Models (LLMs) are widely used, they remain susceptible to jailbreak prompts that can elicit harmful or inappropriate responses. Thi

The signal is the ceiling: Measurement limits of LLM-predicted experience ratings from open-ended survey text

arXiv:2604.19645v1 Announce Type: new Abstract: An earlier paper (Hong, Potteiger, and Zapata 2026) established that an unoptimized GPT 4.1 prompt predicts fan-reported experience ratings within one p

A unified convergence theory for adaptive first-order methods in the nonconvex case, including AdaNorm, full and diagonal AdaGrad, Shampoo and Muo

arXiv:2604.17423v1 Announce Type: new Abstract: A unified framework for first-order optimization algorithms fornonconvex unconstrained optimization is proposed that uses adaptivelypreconditioned gradi

researcharxiv-cs-lg

Agentic Risk-Aware Set-Based Engineering Design

model-releasesarxiv-cs-lg

arXiv:2604.16687v1 Announce Type: cross Abstract: This paper introduces a multi-agent framework guided by Large Language Models (LLMs) to assist in the early stages of engineering design, a phase ofte

Contrastive Analysis of Linguistic Representations in Large Language Model Outputs through Structured Synthetic Data Generation and Abstracted N-gram Associations

arXiv:2604.17398v1 Announce Type: new Abstract: We present a methodological framework to discover linguistic and discursive patterns associated to different social groups through contrastive synthetic

Tutorials

Evaluating Adaptive Personalization of Educational Readings with Simulated Learners

arXiv:2604.16744v1 Announce Type: new Abstract: We present a framework for evaluating adaptive personalization of educational reading materials with theory-grounded simulated learners. The system buil

tutorialsarxiv-cs-cl

Inference-Time Temporal Probability Smoothing for Stable Video Segmentation with SAM2 under Weak Prompts

arXiv:2604.17115v1 Announce Type: new Abstract: Interactive video segmentation models such as SAM2 have demonstrated strong generalization across diverse visual domains. However, under weak user super

MHSafeEval: Role-Aware Interaction-Level Evaluation of Mental Health Safety in Large Language Models

arXiv:2604.17730v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly explored as scalable tools for mental health counseling, yet evaluating their safety remains challenging d

RA-RRG: Multimodal Retrieval-Augmented Radiology Report Generation with Key Phrase Extraction

arXiv:2504.07415v2 Announce Type: replace-cross Abstract: Automated radiology report generation (RRG) holds potential to reduce the workload of radiologists, and recent advances in multimodal large la

applicationsarxiv-cs-cl

Real-Time Visual Attribution Streaming in Thinking Model

arXiv:2604.16587v1 Announce Type: new Abstract: We present an amortized framework for real-time visual attribution streaming in multimodal thinking models. When these models generate code from a scree

SegTTA: Training-Free Test-Time Augmentation for Zero-Shot Medical Imaging Segmentation

arXiv:2604.17451v1 Announce Type: new Abstract: Increasingly advanced data augmentation techniques have greatly aided clinical medical research, increasing data diversity and improving model generaliz

What Makes AI Research Replicable? Executable Knowledge Graphs as Scientific Knowledge Representations

arXiv:2510.17795v3 Announce Type: replace Abstract: Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate exec

agentsarxiv-cs-cl

AscendKernelGen: A Systematic Study of LLM-Based Kernel Generation for Neural Processing Units

model-releasesarxiv-cs-ai

arXiv:2601.07160v2 Announce Type: replace Abstract: To meet the ever-increasing demand for computational efficiency, Neural Processing Units (NPUs) have become critical in modern AI infrastructure. Ho

Designing Synthetic Discussion Generation Systems: A Case Study for Online Facilitation

arXiv:2503.16505v4 Announce Type: replace-cross Abstract: A critical challenge in social science research is the high cost associated with experiments involving human participants. We identify Synthet

applicationsarxiv-cs-cl

Local Ai

From Limited Labels to Open Domains:An Efficient Learning Method for Drone-view Geo-Localization

arXiv:2503.07520v5 Announce Type: replace Abstract: Traditional supervised drone-view geo-localization (DVGL) methods heavily depend on paired training data and encounter difficulties in learning cros

local-aiarxiv-cs-cv

Joint Score-Threshold Optimization for Interpretable Risk Assessment

arXiv:2510.21934v3 Announce Type: replace Abstract: Risk assessment tools in healthcare commonly employ point-based scoring systems that map patients to ordinal risk categories via thresholds. While e

Saturation-Aware Space-Variant Blind Image Deblurring

arXiv:2604.16200v1 Announce Type: new Abstract: This paper presents a novel saturation aware space variant blind image deblurring framework designed to address challenges posed by saturated pixels in

applicationsarxiv-cs-cv

Heat and Matern Kernels on Matchings