Search: “framework”

arXiv:2504.01882v2 Announce Type: replace Abstract: The use of DNS over HTTPS (DoH) tunneling by an attacker to hide malicious activity within encrypted DNS traffic poses a serious threat to network s

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Agents

COOPA: A Modular LLM Agent Architecture for Operations Research Problems

DGX agent

arXiv:2606.27611v1 Announce Type: new Abstract: Operations Research (OR) provides a rigorous framework for high-stakes decision-making, but effective OR modeling requires substantial domain knowledge,

agentsarxiv-cs-lg

29 Jun 2026

Curriculum-guided Change Detection Training: Toward Accurate Serac Fall Monitoring

model-releasesarxiv-cs-cv

arXiv:2606.28012v1 Announce Type: new Abstract: Change Detection (CD) aims to identify semantic or structural changes from nearly registered multi-temporal images. While recent advances in training me

Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs

model-releasesarxiv-cs-cl

arXiv:2606.27378v1 Announce Type: new Abstract: We introduce an axiomatic evaluation framework for latent thought representations in LLMs, comprising metrics that are independent of downstream benchma

HunyuanImage 3.0 Technical Report

arXiv:2509.23951v3 Announce Type: replace Abstract: We present HunyuanImage 3.0, a native multimodal model that unifies multimodal understanding and generation within an autoregressive framework, with

safetyarxiv-cs-cv

LieSolver: PDE-Constrained Learning for IBVPs via Lie Symmetries

arXiv:2510.25731v2 Announce Type: replace-cross Abstract: Initial-boundary value problems (IBVPs) provide the essential framework for modelling a wide range of phenomena in physics and engineering. We

researcharxiv-cs-ai

LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior

model-releasesarxiv-cs-ai

arXiv:2606.28182v1 Announce Type: cross Abstract: Embodied agents operating in decentralized and partially observable environments have attracted growing attention in recent years. However, existing l

Local Ai

Odyssey: Constructing Verifiable Local Truth-Preserving Foundation Models

arXiv:2606.27593v1 Announce Type: new Abstract: We introduce a categorical framework called ODYSSEY for constructing verifiable, local truth-preserving foundation models as compositions of foundries:

local-aiarxiv-cs-ai

OverFlowLight: Real-Time Gridlock Prevention and Traffic Signal Optimization for Urban Intersections

arXiv:2606.27381v1 Announce Type: cross Abstract: Queue overflow, a severe consequence of urban traffic congestion, occurs when vehicle queues exceed intersection capacity, obstructing upstream traffi

safetyarxiv-cs-ai

PerceptionRubrics: Calibrating Multimodal Evaluation to Human Perception

model-releasesarxiv-cs-cv

arXiv:2606.28322v1 Announce Type: new Abstract: We introduce PerceptionRubrics, a rubric-based evaluation framework that addresses the gap between saturated benchmark scores and real-world brittleness

Regularized Reward-Punishment Reinforcement Learning

arXiv:2606.28152v1 Announce Type: new Abstract: We propose KL-Coupled Policy Regularization (KCPR), a policy coordination framework for Reward-Punishment Reinforcement Learning (RPRL). Based on KCPR,

safetyarxiv-cs-lg

Scene Generation at Absolute Scale: Utilizing Semantic and Geometric Guidance From Text for Accurate and Interpretable 3D Indoor Scene Generation

arXiv:2603.13910v2 Announce Type: replace Abstract: We present GuidedSceneGen, a text-to-3D generation framework that produces metrically accurate, globally consistent, and semantically interpretable

safetyarxiv-cs-cv

StableMotion: One-Step Motion Estimation with Diffusion Prior

arXiv:2505.06668v2 Announce Type: replace Abstract: We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion

StructSplat: Generalizable 3D Gaussian Splatting from Uncalibrated Sparse Views

arXiv:2606.28321v1 Announce Type: new Abstract: We present StructSplat, a feed-forward and generalizable 3D Gaussian reconstruction framework that operates directly on uncalibrated images without requ

safetyarxiv-cs-cv

Structured-Li-GS: Structured 3D Gaussians Splatting with LiDAR Incorporation and Spatial Constraints

model-releasesarxiv-cs-cv

arXiv:2606.27509v1 Announce Type: new Abstract: In this study, we develop a Structured framework for Gaussian Splatting (3DGS) with LiDAR integration (Structured-Li-GS). It is a lightweight Gaussian S

Adaptive Utility driven Resource Orchestration for Resilient AI (AURORA-AI)

arXiv:2606.27005v1 Announce Type: new Abstract: Modern AI systems are increasingly deployed under non-stationary computational, demographic, and operational conditions in which static resource allocat

safetyarxiv-cs-ai

Anatomy-Guided Residual Motion Diffusion for Controllable 4D Cardiac MRI Synthesis

arXiv:2606.26764v1 Announce Type: cross Abstract: Developing robust artificial intelligence models for 4D (3D + time) medical imaging is constrained by limited annotated data, inter-device domain shif

researcharxiv-cs-ai

Bayesian Optimization for General Reaction Conditions

model-releasesarxiv-cs-lg

arXiv:2502.18966v2 Announce Type: replace Abstract: General chemical reaction conditions that achieve consistently high performance across multiple substrates are important for practical applications

Applications

Circular Quasiconformal Deturbulence: Geometry-Based Restoration from Multiple Turbulent Frames

arXiv:2504.13432v3 Announce Type: replace Abstract: Imaging through inhomogeneous media often results in severe distortions, posing significant challenges to downstream image-processing tasks. The lac

applicationsarxiv-cs-cv

Compositionality and the lexicon in evolutionary semantics

arXiv:2606.27228v1 Announce Type: new Abstract: Formal semantics has shown that sentence meanings arise by recursively composing lexical meanings, yet much of the literature on semantic universals mod

researcharxiv-cs-cl

HyperDFlash: MHC-Aligned Block Speculative Decoding with Gated Residual Reduction

model-releasesarxiv-cs-cl

arXiv:2606.26744v1 Announce Type: cross Abstract: We present HyperDFlash, a block-parallel speculative decoding framework tailored to the novel multi-hyper-connection (MHC) architecture proposed by De

Applications

Kalman Prototypical Networks for Few-shot Fault Detection in Combined Cycle Gas Turbines

arXiv:2606.26710v1 Announce Type: new Abstract: Combined-cycle gas turbines (CCGTs) play a key role in modern power generation, offering both high efficiency and reduced environmental impact. However,

applicationsarxiv-cs-ai

Latent Diffusion Posterior Sampling with Surrogate Likelihood Guidance for PDE Inverse Problems

model-releasesarxiv-cs-lg

arXiv:2606.26592v1 Announce Type: cross Abstract: We propose latent-space diffusion posterior sampling (L-DPS), an approximate Bayesian framework for high-dimensional inverse problems governed by part

Morphology-Specific Closed-Loop Control of Logarithmic-Spiral Continuum Arms via Online Jacobian Error Compensation

arXiv:2606.26188v1 Announce Type: new Abstract: Logarithmic spirals are ubiquitous in biological appendages and provide an attractive morphology for continuum manipulators capable of reaching, wrappin

researcharxiv-cs-ro

Tutorials

Neural Voxel Dynamics: Learning Implicit 3D Physics via Volumetric Feature Advection

arXiv:2606.26410v1 Announce Type: new Abstract: We present a self-supervised framework for learning implicit 3D physical dynamics directly from video-derived supervisory signals. While current generat

tutorialsarxiv-cs-cv

Radical AI Interpretability

arXiv:2606.26523v1 Announce Type: new Abstract: We develop a framework for interpreting AI systems as agents, drawing on the philosophical tradition of radical interpretation and the tools of mechanis

safetyarxiv-cs-ai

Scalable AI-assisted Workflow Management for Detector Design Optimization Using Distributed Computing

model-releasesarxiv-cs-ai

arXiv:2603.30014v2 Announce Type: replace-cross Abstract: The Production and Distributed Analysis (PanDA) system, originally developed for the ATLAS experiment at the CERN Large Hadron Collider (LHC),

Tailor Made Embeddings for Quantum Machine Learning

arXiv:2606.26312v1 Announce Type: cross Abstract: Autoencoders transformed classical machine learning by solving the curse of dimensionality, enabling principled weight initialization and learning com

A Bregman Perspective on Classification and Regression Trees

arXiv:2606.13984v2 Announce Type: replace-cross Abstract: Classification and Regression Trees (CART) constitute one of the most influential paradigms in statistical learning. Although a variety of imp

Agent-as-a-Router: Agentic Model Routing for Coding Tasks

model-releasesarxiv-cs-ai

arXiv:2606.22902v2 Announce Type: replace Abstract: Real-world users typically have access to multiple Large Language Models (LLMs) from different providers, and these LLMs often excel at distinct dom

Certified Robust Invariant Polytope Training in Neural Controlled ODEs

arXiv:2408.01273v3 Announce Type: replace Abstract: We propose a framework for training neural network controllers with certified robust forward invariant polytopes. First, we parameterize a family of

CoGeoAD: Hierarchical Color-Geometric Fusion with Multi-View Attention for Zero-Shot 3D Anomaly Detection

arXiv:2606.25273v1 Announce Type: new Abstract: Zero-shot 3D anomaly detection is essential for industrial quality inspection, where labeled anomaly samples are scarce. Meanwhile, existing methods lac

Tutorials

Compositional Behavioral Semantics for State Abstraction in Reinforcement Learning

arXiv:2606.25357v1 Announce Type: new Abstract: State abstraction plays a key role in scaling reinforcement learning to complex but structured systems. In studying such systems, a wide range of behavi

tutorialsarxiv-cs-lg

Cross-Attention Multimodal Learning for Predicting Response to Neoadjuvant Imatinib in Gastrointestinal Stromal Tumors: A Multicenter Retrospective Study

arXiv:2606.25579v1 Announce Type: cross Abstract: Background: Response to neoadjuvant imatinib in gastrointestinal stromal tumors (GISTs) is highly variable and cannot be reliably predicted using curr

Efficient Analytic Uncertainty Quantification for Multi-Modal Regression

arXiv:2606.25188v1 Announce Type: new Abstract: Efficient uncertainty quantification (UQ) is essential for trustworthy large-scale learning. Existing UQ methods for regression tasks mainly operate und

Error-Aware TF-IDF Retrieval-Augmented Generation for ASR Error Correction

arXiv:2606.24915v1 Announce Type: new Abstract: End-to-end automatic speech recognition systems frequently hallucinate rare entities and domain-specific terms, especially in low-resource languages. Wh

researcharxiv-cs-cl

Expresso-AI: Explainable Video-Based Deep Learning Models for Depression Diagnosis

arXiv:2606.25606v1 Announce Type: new Abstract: Given the widespread prevalence of depression and its consequential impact on individuals and society, it is crucial to obtain objective measures for ea

Fuzzy Quantification over OWL Ontologies and Knowledge Graphs

arXiv:2606.25778v1 Announce Type: new Abstract: This paper presents a versatile framework for evaluating fuzzy quantification queries over both standard and fuzzy ontologies as well as knowledge graph

researcharxiv-cs-ai

GCT-MARL: Graph-Based Contrastive Transfer for Sample-Efficient Cooperative Multi-Agent Reinforcement Learning

arXiv:2606.25073v1 Announce Type: new Abstract: In cooperative multi-agent reinforcement learning (MARL), from a deployment perspective, it is challenging and expensive to train agents from scratch fo

safetyarxiv-cs-lg

Gradient-based inverse lithography for EUV masks via the waveguide method and a physics-informed neural operator

arXiv:2606.25753v1 Announce Type: new Abstract: Gradient-based inverse lithography technology~(ILT) for extreme ultraviolet~(EUV) masks is presented. A novel framework treats the differentiable wavegu

InvestPhilBench: A Multi-Layer Dynamic Benchmark for Evaluating Large Language Model Procedural Reasoning in Expert Investment Philosophy

model-releasesarxiv-cs-lg

arXiv:2606.25984v1 Announce Type: cross Abstract: Large language models are increasingly deployed as investment research assistants, yet no benchmark tests whether they can accurately reconstruct and

Agents

Is GraphRAG Needed? From Basic RAG to Graph-/Agentic Solutions with Context Optimization

arXiv:2606.25656v1 Announce Type: new Abstract: As advanced RAG variants like GraphRAG and Agentic RAG emerge, one leading question is when and how to use them. Here, we introduce a framework for diff

agentsarxiv-cs-cl

Limitations of SGD for Multi-Index Models Beyond Statistical Queries

arXiv:2602.05704v2 Announce Type: replace Abstract: Understanding the limitations of gradient methods, and stochastic gradient descent (SGD) in particular, is a central challenge in learning theory. T

Neural operator-based digital twins for modeling amyloid-eta and tau propagation and treatment optimization in Alzheimer's disease

arXiv:2606.25185v1 Announce Type: new Abstract: Accurately predicting the spatiotemporal evolution of amyloid-eta and tau proteins at the individual level is critical for improving the diagnosis and t

Scalable Peptide Design via Memory-Efficient Equivariant Transformer

arXiv:2606.25006v1 Announce Type: new Abstract: Target-specific peptide design requires sequence and structure co-design under full atom geometric constraints. Latent generative frameworks offer an ef

Space-Efficient Language Generation in the Limit

arXiv:2606.25777v1 Announce Type: cross Abstract: We initiate a resource-aware theory of extit{language generation in the limit} under the minimal constraint of space efficiency. In our framework, a l

researcharxiv-cs-cl

Supervised Reinforcement Learning for the Coordination of Distributed Energy Resources

arXiv:2606.24947v1 Announce Type: new Abstract: The increasing integration of distributed energy resources (DERs) is crucial for power system decarbonization, yet unlocking DERs' flexibility is challe

safetyarxiv-cs-lg

Agents

UniTeD: Unified Temporal Diffusion for Joint Perception and Planning in Autonomous Driving

arXiv:2606.25736v1 Announce Type: new Abstract: Diffusion models have shown strong potential for multi-modal planning in end-to-end autonomous driving. However, most existing methods confine diffusion

agentsarxiv-cs-cv