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arXiv:2608.18573v1 Announce Type: new Abstract: Existing explainable deepfake forensic methods typically rely on task-adapted MLLM to jointly address detection, localization, and explanation. Inspired

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Research

Payload Swing Estimation and Damping Without Payload Parameters for Multirotor UAVs

DGX agent

arXiv:2608.18625v1 Announce Type: cross Abstract: Cable-suspended payload transport by multirotor UAVs is flexible but generates periodic swing disturbance that degrades tracking and risks instability

researcharxiv-cs-ro

20 Aug 2026

PCQA-R1: Advancing Generalized 3D Point Cloud Quality Assessment with Reinforcement Learning

arXiv:2608.18627v1 Announce Type: new Abstract: No-reference point cloud quality assessment (PCQA) has been an active topic in recent years and is used to measure and optimize the visual experience of

safetyarxiv-cs-cv

Pedagogical AI in Mental Health: A Tri-Stream Fine-Tuned LLM Framework for Automated Clinical Supervision and Risk Triage

arXiv:2608.18438v1 Announce Type: cross Abstract: Modern mental healthcare faces a critical shortage of senior supervisory oversight, leading to a 'supervision gap' where novice therapists manage high

Performance Drift Detection in Machine Learning as a Service (MLaaS) for IoT Environments

arXiv:2608.18555v1 Announce Type: cross Abstract: Machine Learning as a Service (MLaaS) is a powerful cloud paradigm enabling data-driven intelligent applications in Internet of Things (IoT) environme

applicationsarxiv-cs-ai

Persona-Guided LLM Agents for Task-Oriented Dialogue

model-releasesarxiv-cs-cl

arXiv:2608.18085v1 Announce Type: new Abstract: Prior work has shown that large language models (LLMs) can express diverse personality traits in open-ended text generation. However, it remains unclear

Personalized Autonomous Driving via Optimal Control with Clearance Constraints from Questionnaires

arXiv:2602.08326v2 Announce Type: replace Abstract: Driving without considering the preferred separation distance from surrounding vehicles may cause discomfort for users. To address this limitation,

safetyarxiv-cs-ro

PGFS++: Molecular Property Improvement under Synthesis and Diversity Constraints

arXiv:2608.19121v1 Announce Type: cross Abstract: Improving molecular properties, such as drug-likeness or binding affinity, is a recurring task in early-stage drug discovery. However, molecules optim

Local Ai

Physics-Unrolled Neural Operator for Wireless Field Modeling

arXiv:2608.18495v1 Announce Type: cross Abstract: Radio maps are essential for wireless decision-making tasks such as access-point placement, coverage planning, and localization, but their fine spatia

local-aiarxiv-cs-ai

PLASMA: A Layout-Aware Benchmark Reveals Memory Layout Matters for Graph-based ANNS on GPU

model-releasesarxiv-cs-cv

arXiv:2508.15436v2 Announce Type: replace-cross Abstract: We propose a extbf{P}latform for extbf{L}ayout-extbf{A}ware extbf{S}earch and extbf{M}emory extbf{A}rrangement (extbf{PLASMA}), a unified eval

Position: AI Leaderboards Are Underserving the Global South: A Case Study from India

arXiv:2608.18117v1 Announce Type: new Abstract: This position paper argues that AI leaderboards are structurally ill-suited to serving the Global South because they lack independent governance, confli

applicationsarxiv-cs-ai

Position: Behavioral Systems Require Behavioral Tests

arXiv:2608.18081v1 Announce Type: new Abstract: Artificial agentic systems increasingly operate as behavioral systems by interacting with dynamic environments, pursuing goals, and adapting over time.

Position: Collusion Risks Among AI Reasoning Agents Justify Certification Requirements for Making Market Decisions

arXiv:2608.18078v1 Announce Type: new Abstract: This position paper argues that AI agents with chain-of-thought reasoning capabilities are predisposed to exhibit collusive behavior and should be requi

Position: Current Model Cards Are Insufficient for Downstream Governance of Open-Weight Foundation Models

arXiv:2608.18086v1 Announce Type: new Abstract: The growth of open-weight foundation models (OWFMs) has prompted the AI community to re-evaluate strategies for effective downstream governance. Althoug

Position: Multi-Agent Systems Should Prioritize Concurrency Control

arXiv:2608.18092v1 Announce Type: new Abstract: LLM-based multi-agent systems (MAS) promise scalable collaboration, yet adding agents often reduces reliability. This position paper argues that many MA

Position: Profiling Game Worlds by Transition Complexity

arXiv:2608.18079v1 Announce Type: new Abstract: Game world modeling (GWM) and reinforcement learning (RL) are often confounded because research papers rarely quantify how difficult the underlying tran

Pre-Compiled Pipeline Shards for Distributed LLM Inference on Intel AI PC Fleets

arXiv:2608.19147v1 Announce Type: cross Abstract: Modern Intel AI PCs ship capable integrated GPUs and NPUs with 16+ GB of unified memory, and they spend considerable time idle. That is not enough mem

Pre-Training for Simulation-Based Science: A Study on Jet Foundation Model Training Objectives

arXiv:2606.14870v2 Announce Type: replace-cross Abstract: Foundation models (FMs) trained on large datasets and fine-tuned on downstream tasks have emerged as a powerful paradigm in AI for science. In

researcharxiv-cs-lg

Preference Reasoning under Indeterminacy in Large Language Models

arXiv:2608.18631v1 Announce Type: new Abstract: As large language models evolve into decision-making agents, the ability to reason over preferences becomes fundamental to alignment, coordination, and

Pretraining Reusable Inference Across Views with Synthetic Task Priors

arXiv:2608.19115v1 Announce Type: new Abstract: Modern pretrained encoders make representations from heterogeneous views increasingly reusable, but the procedure that determines view utility and combi

safetyarxiv-cs-lg

Prior-Conditioned Gaussian Discriminants for Generalizable AI-generated Image Detection

arXiv:2608.18523v1 Announce Type: cross Abstract: Diffusion-based generators have made synthetic images ubiquitous, but detectors often fail under simultaneous shifts in generator, prompt/style, and s

Process Optimization Under Uncertainty for Improving the Bond Quality of Polymer Filaments in Fused Filament Fabrication

model-releasesarxiv-cs-lg

arXiv:2608.18431v1 Announce Type: cross Abstract: This paper develops a computational framework to optimize the process parameters such that the bond quality between extruded polymer filaments is maxi

Professional Software Developers Don't Vibe, They Control: AI Agent Use for Coding in 2025

arXiv:2512.14012v2 Announce Type: replace-cross Abstract: The rise of AI agents is transforming how software can be built. The promise of agents is that developers might write code quicker, delegate m

Progressive Experience Fusion for Multi-Task World Model Control in Endovascular Navigation

arXiv:2608.18647v1 Announce Type: new Abstract: Autonomous endovascular navigation could support the delivery of mechanical thrombectomy to underserved areas, but controllers must navigate long, multi

agentsarxiv-cs-ro

ProxyGuard: Direct Reliability Inference for Randomized Data Release Mechanisms with Shared Targets

arXiv:2608.18643v1 Announce Type: new Abstract: Researchers often choose a proxy dataset from many releases, transformations, or seeds. Search can make an invalid release appear adequate, while one ad

researcharxiv-cs-lg

Tutorials

Quantum-Logic Tsetlin Machines: Interpretable Quantum Machine Learning with Commuting Projector Clauses

arXiv:2608.18659v1 Announce Type: cross Abstract: Tsetlin Machines (TMs) learn interpretable Boolean clauses using finite-state automata. We introduce the Quantum-Logic Tsetlin Machine (QL-TM), which

tutorialsarxiv-cs-lg

Quantum Tensor Network Learning with DMRG

arXiv:2608.18901v1 Announce Type: cross Abstract: Tensor Networks are a relatively new machine learning approach. The architectures proposed initially are inspired by approaches from quantum many-body

researcharxiv-cs-lg

QuARC-GS: Quantized Anchored Residual Coding for Compact Dynamic Scene Streaming with Gaussian Splatting

arXiv:2608.18285v1 Announce Type: cross Abstract: 3D scene representation techniques such as neural radiance fields (NeRFs) and Gaussian splatting have made substantial progress in novel view synthesi

researcharxiv-cs-cv

RDFdL: Integrating RDF with Differential Dynamic Logic

arXiv:2608.18165v1 Announce Type: new Abstract: Knowledge graphs modeled in RDF are powerful for describing static knowledge, but they cannot capture or reason about the dynamic behavior of physical s

Readable, Faithful, Used: Three Dissociable Properties of Demographic Identity in a Language Model

model-releasesarxiv-cs-cl

arXiv:2608.18768v1 Announce Type: new Abstract: Large language models are widely used to simulate survey respondents, yet their answers are homogeneous and unfaithful to real inter-group differences.

Real-Time Control-Constrained DDP for Underactuated Balancing of Legged Robots

arXiv:2608.18552v1 Announce Type: new Abstract: This paper presents a real-time control-constrained Differential Dynamic Programming (DDP) framework for underactuated legged robots. To address the lim

researcharxiv-cs-ro

Reconstruction of continuum robots by marker-free shape registration of image data using a kinematic model

arXiv:2405.15336v2 Announce Type: replace Abstract: Continuum robots are slender, flexible manipulators that navigate confined, curved workspaces and are gaining traction in aerospace, inspection, aut

researcharxiv-cs-ro

Local Ai

Redakto - The Incognito Tab for LLMs

arXiv:2608.18260v1 Announce Type: new Abstract: Large Language Models (LLMs) are being increasingly used in everyday applications. A major challenge in the context of LLMs or Artificial Intelligence (

local-aiarxiv-cs-ai

rEDMRec: Distilling Large Language Model Reasoning into an Editable Experience Memory for Recommendation

arXiv:2608.18952v1 Announce Type: cross Abstract: Large language models can improve recommendation quality by reasoning explicitly over user history and candidate items - for example, extracting a use

Regularised Iterative Generalised Least Squares with Optimal Selection of the Hyper-Parameter for Identifying Nonlinear Phenomenological Models

model-releasesarxiv-cs-lg

arXiv:2608.18742v1 Announce Type: cross Abstract: In some fields currently dominated by empirical approaches, such as state of health (SoH) prediction for lithium-ion batteries, phenomenological model

Reinforced Planning with Latent World Models

arXiv:2608.18669v1 Announce Type: new Abstract: Humans solve complex problems by constructing plans and mentally simulating their outcomes with an internal model of the world. Machine learning has pro

safetyarxiv-cs-lg

Repeatability is not recovery: Quantifying algorithmic stability and topic recovery in Latent Dirichlet Allocation

arXiv:2511.12850v2 Announce Type: replace Abstract: Topic models are often judged by the consistency of their outputs across repeated runs, implicitly assuming that repeatable topic output is a succes

applicationsarxiv-cs-cl

Reproducible Multimodal Affordance Prediction

arXiv:2608.18317v1 Announce Type: new Abstract: Affordance prediction is the identification of potential actions an agent can perform on a target object from multimodal inputs. Affordance prediction m

safetyarxiv-cs-cv

Rethinking Privileged Information in On-Policy Self-Distillation

arXiv:2608.18271v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a student on its own responses using token-level supervision from the same model conditioned on privileged ref

safetyarxiv-cs-lg

Revisiting the 'Push-T' Robot Manipulation Task with Agentic Robotics

model-releasesarxiv-cs-ro

arXiv:2608.18227v1 Announce Type: new Abstract: Push-T is an iconic benchmark for learning manipulation policies from human demonstrations. The robot must use a single point of contact to push a T-sha

ReWEIGH the Evidence: Calibrating Token-Level Ordinal Visual Evidence to Mitigate Hallucinations in Large Vision-Language Models

arXiv:2608.19075v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) often hallucinate, generating content that the input image does not support. Preventing such content during decod

researcharxiv-cs-ai

ReX-Shot: Single-Image Rephotography via Geometry- and Camera-Grounded Generation

arXiv:2608.18593v1 Announce Type: new Abstract: Single-image rephotography aims to synthesize new shots of a scene from a single reference image with specified viewpoints, focal lengths, and photograp

safetyarxiv-cs-cv

RoboEdit: Turning Human Manipulation Videos into Scalable Robot Experience

arXiv:2608.18948v1 Announce Type: new Abstract: Collecting robot hand-object interaction data is costly and embodiment-specific, yet abundant human-object videos remain unusable for robot training. We

applicationsarxiv-cs-ro

Robust Risk Under Evolving Uncertainty: A Wasserstein Counterpart of the Entropic Value-at-Risk

arXiv:2608.19073v1 Announce Type: new Abstract: An agent still learning its environment should be cautious while ignorant and bold once confident. The entropic value-at-risk captures this through a ro

RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping

arXiv:2607.15048v2 Announce Type: replace Abstract: Road surface mapping plays a crucial role in autonomous driving, supporting high-definition map generation, lane-level perception, and automatic roa

agentsarxiv-cs-cv

Tutorials

Role-Conditioned Sub-Token Routing for Efficient Vision-Language-Action Policies

arXiv:2608.18410v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models process long multimodal token sequences, making inference expensive in both memory and computation. Existing efficie

tutorialsarxiv-cs-lg

RouteCost: A Production-Inspired Multi-Stage Framework for Pre-Order Shipping Cost Estimation in E-Commerce

arXiv:2607.16230v2 Announce Type: replace-cross Abstract: Accurate pre-order shipping cost estimation is important in e-commerce because it affects price presentation, margin planning, and conversion.

applicationsarxiv-cs-ai

RTPO: Reverse-Turn Policy Optimization for Stabilizing Agentic RL Training

arXiv:2608.18682v1 Announce Type: new Abstract: Training multi-turn agentic workflows with reinforcement learning (RL) enables large language models to perform complex reasoning, use external tools, a