Search: “framework”

On the Computational and Statistical Efficiency of the Empirical Maximum Entropy on the Mean Method

arXiv:2608.27705v1 Announce Type: cross Abstract: The Maximum Entropy on the Mean (MEM) method provides a flexible computational framework for solving inverse problems by combining data fidelity with

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Safety

SafeStep: An Interactive Demonstration of Semantic Communication for Pedestrian Safety Monitoring

DGX agent

arXiv:2608.27688v1 Announce Type: new Abstract: In this paper, we develop SafeStep, an interactive browser-based semantic communication platform for live pedestrian safety monitoring. SafeStep extract

safetyarxiv-cs-lg

31 Aug 2026

Securing Multi-Agent GIS Systems: Risk Evaluation and Prompt Hardening Optimization

arXiv:2606.17092v2 Announce Type: replace-cross Abstract: Agentic systems are increasingly integrated with geographic information systems (GIS), where multi-agent coordination enables complex conversa

agentsarxiv-cs-cl

Spatial-Semantic Reasoning using Large Language Models for Efficient UAV Search Operations

arXiv:2608.28270v1 Announce Type: new Abstract: We present a real-time semantic navigation framework for Unmanned Aerial Vehicles (UAVs) focused on improving time efficiency in the Object Goal Navigat

applicationsarxiv-cs-ro

Unsupervised Continual Learning with Growing Self-Organizing Maps and Synthetic Replay

arXiv:2608.27662v1 Announce Type: new Abstract: This work presents a generative continual learning framework based on growing self-organizing maps (GSOMs) that are augmented with learned distributiona

Agentic AI for operating scientific instruments for nanoscale characterization

arXiv:2608.26198v1 Announce Type: new Abstract: Operating a scientific instrument such as an atomic force microscope (AFM) requires continuous expert decision-making. A trained user defines the experi

Beyond Discrete Samples: High Information Density Replay for Efficient Lifelong Person Re-Identification

arXiv:2508.01587v4 Announce Type: replace Abstract: Lifelong Person Re-Identification (LReID) typically resists catastrophic forgetting by replaying historical samples, rehearsing domain distributions

CARE: Causally-Aligned Reasoning Exploration for Medical Large Language Models

arXiv:2608.26147v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong potential for medical reasoning, yet the scarcity and cost of expert-annotated data constrain their progr

safetyarxiv-cs-cl

Guided Data Generation for Understanding Model Behavior

arXiv:2502.06658v4 Announce Type: replace Abstract: We propose a method for generating distributions over the input space as an inspection tool for understanding trained models. Our framework poses qu

Hallucinations in LLMs: A Lifecycle-Based Survey of Causes, Detection, Mitigation, and Prevention

model-releasesarxiv-cs-ai

arXiv:2608.26168v1 Announce Type: cross Abstract: The lifecycle of hallucination in LLMs is a concept that enables building solid frameworks on the control and reliability of LLMs in high-stakes envir

LLMs in Digital EDA: A perspective on shifting roles from Generation to Orchestration

arXiv:2608.27184v1 Announce Type: cross Abstract: Electronic design automation (EDA) has advanced engineering productivity through successive generations of tooling that progressively automate synthes

ProofEvolve: Neuro-Symbolic Evolution for Formal Automated Theorem Proving

arXiv:2608.26334v1 Announce Type: new Abstract: Automated theorem proving offers a natural foundation for recursive self-improvement in scientific discovery. However, existing neural provers do not fu

Quantitative mapping from conventional MRI using self-supervised physics-guided deep learning: applications to a large-scale, clinically heterogeneous dataset

arXiv:2601.05063v2 Announce Type: replace-cross Abstract: Magnetic resonance imaging (MRI) is a cornerstone of clinical neuroimaging, yet conventional MRIs provide qualitative information heavily depe

applicationsarxiv-cs-cv

Refine-POI: Reinforcement Fine-Tuned Large Language Models for Next Point-of-Interest Recommendation

arXiv:2506.21599v5 Announce Type: replace-cross Abstract: Advancing large language models (LLMs) for the next point-of-interest (POI) recommendation task faces two fundamental challenges: (i) although

SymbolLKG: Towards Verifiable Logical Reasoning via Logical Knowledge Graph and Symbolic Solvers

arXiv:2608.26836v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable proficiency in natural language understanding, yet they struggle with strict multi-step reason

Diffusion Transformers for Roof Graph Synthesis and Reconstruction

arXiv:2608.25652v1 Announce Type: new Abstract: We present RoofDiT, a generative framework for 2D roof graph synthesis and reconstruction. Roofs are compactly described as planar graphs of junctions a

safetyarxiv-cs-cv

Formal, Executable and Explainable Runtime Monitoring of Spoken Air Traffic Control Operational Procedures

arXiv:2608.25926v1 Announce Type: cross Abstract: Air traffic control procedures are executed through spoken exchanges between controllers and pilots. These interactions are essential to the safety of

safetyarxiv-cs-cl

Learning Continuous Regional Temperature Fields with Lead-Time and Resolution Queries

arXiv:2608.25823v1 Announce Type: new Abstract: Accurate regional near-surface temperature forecasting is fundamental to short-range weather services and downstream risk assessment. Existing deep lear

Less Contouring, More Accuracy: Lesion-Guided ROI Deep Learning for Ovarian Ultrasound Classification

arXiv:2608.25965v1 Announce Type: new Abstract: Ovarian lesion classification using transvaginal ultrasound remains challenging due to overlapping imaging characteristics and the dependence on expert

NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates

arXiv:2608.25080v1 Announce Type: new Abstract: Time series forecasting models are widely used in high-stakes settings, yet their predictions remain difficult to interpret because existing post-hoc me

ROS2 Connect: A new ROS2 over WAN Solution

arXiv:2608.25102v1 Announce Type: new Abstract: The Robot Operating System 2 (ROS2) has become a widely adopted framework for the development of distributed robotic systems. However, its communication

researcharxiv-cs-ro

Think-Probe-Respond: Improving Large Language Models as Judges of Research Idea Novelty

arXiv:2608.25660v1 Announce Type: new Abstract: Automated novelty judgment can accelerate scientific discovery by enabling efficient evaluation, refinement, and comparison of research ideas. While lar

safetyarxiv-cs-cl

Token-Oriented Semantic Communication with Pretrained Vision Transformers

arXiv:2608.25410v1 Announce Type: cross Abstract: Token communications realize the semantic communication principle at the granularity of transformer tokens, providing a promising direction for client

safetyarxiv-cs-cv

Absorbing Gradient Conflicts: Modeling Semantic Variance via Kent Distributions for Cross-Modal Hashing

model-releasesarxiv-cs-cv

arXiv:2608.24010v1 Announce Type: new Abstract: Supervised proxy-based deep cross-modal hashing has become the dominant paradigm for large-scale retrieval. However, prevalent methods model class proxi

Adaptive prediction theory combining offline and online learning

arXiv:2512.00342v2 Announce Type: replace Abstract: Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system

CoMMa: Contribution-Aware Medical Multi-Agents for Decentralized Oncology Decision Support

arXiv:2602.09159v2 Announce Type: replace Abstract: Recent multi-agent frameworks have shown promise for oncology decision support, yet most assume centralized data access and rely on prompt-based ass

Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering

model-releasesarxiv-cs-ai

arXiv:2608.23666v1 Announce Type: new Abstract: Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential

Markerless Pose Estimation for Resistance Training Technique Assessment

arXiv:2608.24384v1 Announce Type: cross Abstract: Resistance training can be a high risk activity, and safe form is essential to avoiding injury. Laboratory-based movement analysis provides quantitive

applicationsarxiv-cs-ai

Real-World Knowledge-Guided Change Data Synthesis for Remote Sensing

arXiv:2608.24263v1 Announce Type: new Abstract: Change data synthesis provides a cost-effective solution for expanding training data and improving the performance of change detection models. However,

applicationsarxiv-cs-ai

The RAT: A Unified Bayesian Model for RAG Evaluation

arXiv:2608.24753v1 Announce Type: cross Abstract: Evaluating Retrieval-Augmented Generation (RAG) systems requires assessing not only end-to-end correctness but also how individual components interact

Towards Reliable AI-Based Histological Staining: A Systematic Study of Scaling and Uncertainty in Unpaired Generative Models

model-releasesarxiv-cs-cv

arXiv:2608.24626v1 Announce Type: new Abstract: Liver fibrosis, the principal predictor of long-term outcome in chronic liver disease, is staged from histological estimates of collagen content. Sirius

VGGT-DP: Generalizable Robot Control via Vision Foundation Models

arXiv:2509.18778v2 Announce Type: replace-cross Abstract: Visual imitation learning frameworks allow robots to learn manipulation skills from expert demonstrations. While existing approaches mainly fo

Weakly Supervised Seafloor Segmentation for Seagrass Habitat Mapping in Side-Scan Sonar Imagery

arXiv:2608.24756v1 Announce Type: new Abstract: Seagrass meadows are crucial blue-carbon habitats, and mapping their extent is a prerequisite for coastal management and carbon inventory. Optical satel

AI University: An LLM-Powered Learning Assistant for Engineering---A Finite Element Method Case Study

arXiv:2504.08846v2 Announce Type: replace-cross Abstract: We introduce AI University (AI-U), a flexible framework for AI-driven course content delivery that adapts to a course's instructional style. A

BioMed-Agent-RL: A Meta Learning, All You Need for Biomedical Applications

model-releasesarxiv-cs-ai

arXiv:2608.21864v1 Announce Type: cross Abstract: The current progress of Clinical Vision Large Language Models (C-VLLMs) has substantially improved digital diagnostics, still these frameworks often e

Guided Riemannian Optimization (GuRO): Bridging Model Predictive Control and Decision Transformers

model-releasesarxiv-cs-ro

arXiv:2608.23204v1 Announce Type: new Abstract: Decision-making in high-dimensional, nonlinear systems remains a central challenge in robotics. While model-based methods like Model Predictive Control

Interpretable statistical feature engineering for early disruption prediction in the short pulse ADITYA tokamak

arXiv:2608.22515v1 Announce Type: cross Abstract: Reliable early disruption prediction is critical for the safe operation and real-time control of tokamaks. However, machine learning based prediction

Learning Implicit Constitutive Laws for Dynamic 3D Gaussian Splatting from Monocular Videos

arXiv:2608.22102v1 Announce Type: cross Abstract: We present GCA (Gaussian Constitutive Alignment), a framework for learning implicit constitutive laws from monocular dynamic video of deformable objec

MADR: MPC-guided Adversarial DeepReach

arXiv:2510.18845v2 Announce Type: replace Abstract: Hamilton-Jacobi (HJ) Reachability offers a framework for generating safe value functions and policies in the face of adversarial disturbance, but is

researcharxiv-cs-ro

MLLM-Assisted Audio VOS: A 3rd Place Report for the MeViS-Audio Track, 8th LSVOS Challenge

arXiv:2608.23234v1 Announce Type: new Abstract: In this technical report, we present a training-free framework for audio-guided video object segmentation, which integrates Multimodal Large Language Mo

Molecular LLM Agents: From Architectural Design to Scientific Autonomy

arXiv:2608.23104v1 Announce Type: cross Abstract: Molecular science represents an important frontier for LLM-based agents. Unlike general agents that mainly operate over natural language, code, or web

Physical Agentic AI: An Architecture for Orchestrating a Robot Crew with LLMs

arXiv:2608.22657v1 Announce Type: cross Abstract: Agentic AI frameworks interpret open-ended task goals and decompose them into multi-step plans. Richer information about embodiment-specific capabilit

A Temporal Planning Approach for Intelligent Flood Response

arXiv:2608.20510v1 Announce Type: new Abstract: Effective response to multiple, simultaneously flooded areas requires coordinating appropriate actions in the correct temporal order, under severe resou

CAS: Conformalized Agentic Search via Adaptive Retrieval and Policy Weighting

arXiv:2608.20771v1 Announce Type: new Abstract: Search Agents face a severe reliability crisis during reinforcement learning (RL) fine-tuning. Heuristic Top-K retrieval often causes critical evidence

Tutorials

CDRL: Certification-Driven Reinforcement Learning for Neutrino Flavor Model Discovery

arXiv:2608.20686v1 Announce Type: new Abstract: Many scientific discovery problems require searching combinatorial hypothesis spaces under complex domain constraints. Reinforcement learning (RL) offer

tutorialsarxiv-cs-ai

From Regulation to Implementation: A Critical Evaluation of LLM-Assisted Regulatory Compliance in Industry

arXiv:2608.21317v1 Announce Type: new Abstract: The European Union (EU) has emerged as a leading regulatory body in the development of sustainability and privacy regulations. While new regulation requ

Interpretable Information-Decomposed Brain Graph Learning for fMRI-based Disease Diagnosis

arXiv:2608.20380v1 Announce Type: cross Abstract: Resting-state functional magnetic resonance imaging (rs-fMRI) has enabled non-invasive mapping of functional brain interactions for computer-aided dia

Interpretable Multimodal Classification with Linear Discriminant Tree Ensembles

arXiv:2608.20384v1 Announce Type: new Abstract: Multimodal affect and behaviour classifiers that fuse heterogeneous text, audio, and visual streams must simultaneously achieve competitive accuracy and