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From Generation to Simulation: How Far Are World Models from Being True Simulators?

arXiv:2608.23070v1 Announce Type: new Abstract: With the rapid progress of diffusion models and large-scale video generation, generative world models are increasingly expected to replace traditional s

researcharxiv-cs-ai

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From Inertia to Objectivity: Improving Deep Research Agents with Noise Isolation

DGX agent

arXiv:2608.23045v1 Announce Type: new Abstract: Web search agents powered by Large Language Models (LLMs) show strong promise, but deep research tasks expose a recurring failure mode: once an agent ha

model-releasesarxiv-cs-ai

25 Aug 2026

From Isolation to Alignment: Unified LoRA for Efficient Multi-Task Learning

arXiv:2508.05078v2 Announce Type: replace-cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is essential for adapting Large Language Models (LLMs) to multi-task scenarios. A prevailing trend in t

From Mastery Profile to Simulated Response: Stochastic Student Knowledge Graphs (SSKG) for Faithful LLM Student Simulation

arXiv:2608.21668v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate students at different mastery levels. These simulations can generate synthetic training d

From Multimodal Observation to Interpretable Suggestions: Counterfactual Time-Expanded Relational Modeling of Surgical Teams

arXiv:2608.23254v1 Announce Type: new Abstract: In surgery, patient safety is threatened not only by technical issues but also by poor teamwork. However, existing surgical AI-based solutions focus mai

safetyarxiv-cs-lg

From Recognition to Reasoning: Advancing Multimodal Harmful Meme Detection via Chain-of-Thought Alignment

arXiv:2506.18919v5 Announce Type: replace-cross Abstract: As a multimodal communication medium that integrates images and text, memes often convey implicit harmful content through metaphors, satire, a

safetyarxiv-cs-ai

From Solver Feedback to Faithful Plans: Multi-Role Reinforcement Learning for Symbolic Planning

arXiv:2608.21897v1 Announce Type: new Abstract: Reliable planning requires converting natural-language instructions into executable symbolic specifications, yet large language models remain brittle wi

tutorialsarxiv-cs-ai

From SQL Generation to Tool Selection: A Domain-Oriented Pattern for MCP Servers

arXiv:2608.22063v1 Announce Type: new Abstract: Agents built on Large Language Models (LLMs) increasingly reach enterprise data through the Model Context Protocol (MCP), and many MCP database servers

From Subjective Judgments to Auditable Standards:Protocol-Guided AI Auditing of Website Redundancy

model-releasesarxiv-cs-cv

arXiv:2608.21476v1 Announce Type: cross Abstract: Website redundancy does not have a single fixed meaning. The same repeated element may distract during one task and provide backup during another. We

From Symmetry to Invariance: Learning Galois Equivalent Representations in Finite Fields

arXiv:2608.22513v1 Announce Type: new Abstract: Neural networks can learn algebraic operations from finite examples, but it remains unclear whether this ability transfers across mathematically equival

tutorialsarxiv-cs-lg

FrugalSOT - Frugal Search Over the Models

arXiv:2608.21621v1 Announce Type: new Abstract: In on-device NLP tasks, limited resources of embedded hardware, such as the Raspberry Pi 5, require efficient inference strategies. This paper introduce

local-aiarxiv-cs-lg

Functional compatibility as a determinant of persistent neural learning

arXiv:2608.22462v1 Announce Type: cross Abstract: Artificial neural networks can acquire new capabilities but often damage existing ones when they continue to learn. This stability-plasticity problem

tutorialsarxiv-cs-ai

Future Querying: Can LLMs Serve as Implicit Medical World Models?

arXiv:2608.23248v1 Announce Type: cross Abstract: Traditional clinical prediction models rely on task-specific pipelines and curated, structured data, which scale poorly and underutilize unstructured

researcharxiv-cs-ai

GameXpert-Bench: How Far Are Coding Agents from Expert Game Development?

arXiv:2608.21833v1 Announce Type: new Abstract: Recent large language models (LLMs) can operate as coding agents that build complete games from natural language requests. Game development is especiall

GAN-Diff : Coupling Pretrained WGAN-GP Features with Conditional Diffusion U-Nets

arXiv:2608.22272v1 Announce Type: cross Abstract: Generative adversarial networks (GANs) can provide efficient image generation, while diffusion models offer high-quality image restoration but require

Gate Voltage Effect on Pulse Detection Efficiency of Perimeter-Gated SPADs

arXiv:2608.21371v1 Announce Type: cross Abstract: Perimeter-gated single-photon avalanche diodes (pg-SPADs) are known for their dynamic dark noise modulation capabilities. They are reported to trade n

Gated Decoupled Compositional Bandits: A Unified Theory of Contextual Bandits with Supervised-Calibrated Action Scaling and Pre-Execution Gating

model-releasesarxiv-cs-lg

arXiv:2608.21993v1 Announce Type: new Abstract: We introduce Gated Decoupled Compositional Bandits (GDCB), a family of contextual bandit algorithms with three structural innovations that jointly fall

Gauss--Hermite Quadrature for Gaussian-Mixture Entropy with an Action-Space Hermite Surrogate

model-releasesarxiv-cs-lg

arXiv:2608.21467v1 Announce Type: cross Abstract: Gaussian distributions are used to model uncertainty in signals and states, and Gaussian mixtures are often used when the underlying distribution is m

Gaussian process learning with flow map refinement for parameter estimation in dynamical systems

model-releasesarxiv-cs-lg

arXiv:2608.22324v1 Announce Type: new Abstract: Parameter estimation is a central task in data-driven learning of dynamical systems. It aims to recover the underlying physical parameters from observed

GaussVid: Sparse-View Gaussian Splatting with 3D-Aware Video Diffusion Priors

arXiv:2608.21849v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has achieved remarkable success in novel view synthesis; however, reconstructions under sparse views often exhibit noticeab

GCA: Global Centroid Alignment in Federated Learning

arXiv:2608.22593v1 Announce Type: new Abstract: Autoencoder (AE)-based federated learning (FL) is attractive for anomaly detection when clients have limited local data. However, conventional FL exchan

local-aiarxiv-cs-lg

Applications

GCS-Bridging: Restoring Connectivity of Disconnected Convex Sets for Graph-of-Convex-Sets Motion Planning

arXiv:2608.22326v1 Announce Type: new Abstract: Graph-of-Convex-Sets (GCS)-based trajectory optimization represents collision-free regions in configuration space as a finite collection of convex sets

applicationsarxiv-cs-ro

GenCoord: Skill-Path Commitments under Private Information

arXiv:2608.22055v1 Announce Type: new Abstract: Suppose one embodied agent knows what must be built, while its teammate alone knows which transformation its workcell can perform. Neither local view de

local-aiarxiv-cs-ai

Generate in the Chart, Not on the Boundary: Function-Symbol Grounding for Hard Constraints in LTN-GANs

arXiv:2608.21605v1 Announce Type: new Abstract: Logic Tensor Network-Enhanced Generative Adversarial Networks (LTN-GANs) inject background knowledge by grounding each logical axiom as a predicate and

tutorialsarxiv-cs-ai

Applications

Generated Reality: Human-centric World Simulation using Interactive Video Generation with Hand and Camera Control

arXiv:2602.18422v2 Announce Type: replace Abstract: Extended reality (XR) demands generative models that respond to users' tracked real-world motion, yet current video world models accept only coarse

applicationsarxiv-cs-cv

Generative Gap Filling

arXiv:2608.21401v1 Announce Type: cross Abstract: Most contract litigation turns on contracts that imperfectly record parties' bargains. When the parties' dispute can't be solved by interpreting the t

safetyarxiv-cs-cl

Generative Neural Networks for Sinkhorn Distributionally Robust Hypothesis Testing

arXiv:2608.22746v1 Announce Type: cross Abstract: This paper studies the Sinkhorn distributionally robust hypothesis testing (SDRHT) problem, seeking a robust detector against least-favorable distribu

researcharxiv-cs-lg

Agents

Geo-VLA: Geometry-Aware Vision-Language-Action Planning via Internalization of Map Semantics

arXiv:2608.21440v1 Announce Type: cross Abstract: Vision-language-action (VLA) models have advanced end-to-end autonomous driving by leveraging foundation models for semantic reasoning and long-tail g

agentsarxiv-cs-ai

Geometric Structures on Graphs: a Holonomy-Based Discretization of Curvature

arXiv:2608.22453v1 Announce Type: new Abstract: We propose a holonomy-based framework for discretizing curvature on graphs equipped with local symmetric positive-definite metrics. Each vertex carries

researcharxiv-cs-lg

Geometry-Driven Opti-Acoustic Co-Registration and View-Invariant Reflectivity Mapping for Side-Scan Sonar

arXiv:2608.23479v1 Announce Type: new Abstract: Side-Scan Sonar (SSS) is a primary modality for large-scale underwater mapping, yet automated perception and cross-modal alignment are severely bottlene

safetyarxiv-cs-cv

GeoMix: Descriptor-Free Visual Localization via Global Context and Multi-Detector Training

arXiv:2607.02486v2 Announce Type: replace Abstract: Descriptor-free visual localization eliminates high-dimensional descriptor storage, preserves scene privacy, and simplifies map maintenance, yet its

tutorialsarxiv-cs-cv

GeoQ: Geometry-Aware Conditional Quantile Error Estimation for Scientific Surrogate Models

arXiv:2608.21652v1 Announce Type: new Abstract: Neural-network surrogate models are increasingly used to accelerate scientific simulations, but their deployment in extrapolative and autoregressive set

local-aiarxiv-cs-lg

GeoRisk-RAG: A Hierarchy-Aware Risk Framework for Improving RAG Reliability through Selective Answering

arXiv:2608.22634v1 Announce Type: cross Abstract: Current work on improving reliability in large language model (LLM)- generated answers has primarily leveraged Retrieval-Augmented Generation (RAG), k

safetyarxiv-cs-ai

Agents

GeoWAM: Visual Geometry World Action Models for Autonomous Driving

arXiv:2608.23486v1 Announce Type: new Abstract: World action models (WAMs) have recently gained increasing attention as a framework for jointly modeling scene evolution and ego actions in autonomous d

agentsarxiv-cs-cv

GET: Generative Embedding Translation for Medical Image Segmentation

arXiv:2608.22619v1 Announce Type: cross Abstract: Generative segmentation provides an alternative to direct pixel-wise prediction by operating on learned latent representations, but effective image-to

Gimbal-Based Human Tracking for Companion Robots Using Continual Learning

arXiv:2608.21388v1 Announce Type: new Abstract: Reliable and continuous human tracking is essential for natural human-robot interaction, particularly for companion robots. However, many existing appro

researcharxiv-cs-ro

GOLEM: Modular Humanoid Autonomy Towards Electric Vehicle Battery Disassembly

arXiv:2608.21550v1 Announce Type: new Abstract: Disassembling end-of-life electric vehicle (EV) battery packs is dull and dangerous work, performed almost entirely by humans. We present GOLEM (General

researcharxiv-cs-ro

GRACE: Step-Level Benchmark for Faithful Reasoning over Context

model-releasesarxiv-cs-cl

arXiv:2606.16151v2 Announce Type: replace Abstract: Many reasoning tasks require models to reason over input context, from document-grounded question answering to rule-based deduction. Chain-of-Though

GradAttn: Replacing Fixed Residual Connections with Task-Modulated Attention Pathways

arXiv:2603.26756v2 Announce Type: replace Abstract: Deep ConvNets suffer from gradient signal degradation as network depth increases, limiting effective feature learning in complex architectures. ResN

GRAFT: Graph-Distilled Generative Retrieval for Facet-Aware Scientific Literature Exploration

arXiv:2608.22381v1 Announce Type: cross Abstract: Scientific papers may relate by problem, method, result, or contribution, but document-level retrievers collapse these into a single similarity score

researcharxiv-cs-cl

Graph Representation Learning of Lightweight IoT Ciphers

arXiv:2608.23054v1 Announce Type: new Abstract: SIMON and SIMECK belong to a family of Lightweight Cryptographic Algorithms (LCAs) based on the Feistel block cipher, designed for Internet of Things (I

researcharxiv-cs-lg

Agents

GraphMed-LT: Patient-Specific Graph Memory with Latent Clinical Thought Refinement for Multi-Turn Medical Conversations

arXiv:2510.03536v3 Announce Type: replace-cross Abstract: Multi-turn medical question answering (QA) aims to model realistic clinical diagnosis, where a doctor gathers patient information across multi

agentsarxiv-cs-ai

GRC-ProbNet: Uncertainty-aware Feature Extraction for Cardiovascular Disease Classification

arXiv:2607.10357v2 Announce Type: replace-cross Abstract: The automatic detection and classification of cardiovascular disease (CVD) from computed tomography (CT) images plays an important role in cli

researcharxiv-cs-ai

Grounded Normative Rule Generation with Structured Search

model-releasesarxiv-cs-cl

arXiv:2608.22229v1 Announce Type: new Abstract: Normative rules like institutional charters and workplace policies must be both human-readable and operationally verifiable against actual environment r

Grounding Free-Form Instructions for Fashion Complementary Image Generation

arXiv:2608.23302v1 Announce Type: new Abstract: Fashion complementary image generation (CIG) aims to create garments that stylistically match a seed item based on user intent, making it a natural mult

safetyarxiv-cs-cv

Grounding Isn't Knowing: Do VLMs Need Object Localization for Spatial Reasoning?

arXiv:2608.23074v1 Announce Type: new Abstract: Vision-language models (VLMs) can answer spatial questions, yet the mechanisms connecting object grounding to spatial reasoning remain poorly understood

local-aiarxiv-cs-cv

GSAR: Goal-State-Anchor Rewards for Mobile GUI Agents with Self-Evolving Data Synthesis

arXiv:2608.22847v1 Announce Type: new Abstract: Vision-Language Models (VLMs) based GUI agents stand to benefit significantly from online reinforcement learning (RL). However, their training is bottle

GTA-RAG: Graph-Trajectory-Augmented Reinforcement Learning for Multi-Turn Retrieval-Augmented Reasoning

arXiv:2608.22479v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) enables LLMs to access external knowledge for answering knowledge-intensive questions. For complex multi-hop questi

safetyarxiv-cs-cl