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Syntactic Simplification of OWL Class Expressions

arXiv:2608.18899v1 Announce Type: new Abstract: Class expression learning often produces complex OWL class expressions that are difficult to interpret and reason over. However, by following theoretica

Tangut Word Segmentation under Extreme Resource Scarcity: Integrating Traditional Lexicons and Unlabeled Text

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DGX agent

arXiv:2608.18437v1 Announce Type: new Abstract: Tangut is an extinct language whose script does not explicitly mark word boundaries. We present the first systematic study of Tangut word segmentation u

researcharxiv-cs-cl

20 Aug 2026

Task-Conditioned Least-Privilege Learning for Executable Terminal and MCP Agents

arXiv:2608.18351v1 Announce Type: cross Abstract: Tool-using large language-model agents can complete a task while exercising authority that the user did not grant or the task does not need, causing e

Tatarstan Toponyms: A Bilingual Dataset and Hybrid RAG System for Geospatial Question Answering

model-releasesarxiv-cs-cl

arXiv:2605.05962v2 Announce Type: replace Abstract: This paper addresses end-to-end geospatial question answering over multilingual toponymic data. We introduce a bilingual (Russian-Tatar) dataset of

Tutorials

Teach a Molmo2Fish: Towards interactive fish tracking with natural language guidance

arXiv:2608.18602v1 Announce Type: new Abstract: Computer vision is increasingly used to automate recognition tasks in large ecological datasets, but more complex tasks such as multi-object tracking co

tutorialsarxiv-cs-cv

Local Ai

Teeth2Point: A Two-Stage Dental CBCT ROI-to-Point Segmentation Framework

arXiv:2608.18667v1 Announce Type: new Abstract: Modern deep learning architectures have demonstrated strong performance in dental CBCT segmentation. One remaining crucial challenge is accurate tooth l

local-aiarxiv-cs-cv

Temporal Multi-Signal Fusion for Token-Level Hallucination Detection

arXiv:2608.18115v1 Announce Type: cross Abstract: Token-level hallucination detectors score each token independently from a single signal, and fail exactly when the generating model is confidently wro

Tensor Field Models

arXiv:2608.18808v1 Announce Type: new Abstract: This paper introduces Tensor Field Models (TFMs), realization-level Mathematical Structures in which a learned Operator maps a product of admissible com

Applications

Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck

arXiv:2608.18931v1 Announce Type: cross Abstract: Test-time scaling (TTS) improves language model outputs by spending additional inference compute - generating multiple candidates, searching over part

applicationsarxiv-cs-ai

The Deontic Gap: Large Language Models and the Modal Language of Obligation

arXiv:2608.18144v1 Announce Type: cross Abstract: Modal auxiliaries such as must, should, and have to mark necessity and obligation within the contexts of speaker authority and interpersonal stance. W

The Embodiment Gap in Robot Foundation Models

arXiv:2608.18433v1 Announce Type: new Abstract: Robot foundation models (RFMs), including vision-language-action (VLA) policies, are often discussed through a scaling view: more data, larger models, a

researcharxiv-cs-ro

The Impact of CutMix on Reliability and Robustness in Semantic Segmentation

arXiv:2608.18715v1 Announce Type: cross Abstract: Ensuring not only high accuracy but also reliable and robust predictions is critical for the deployment of semantic segmentation models in safety-crit

safetyarxiv-cs-ai

The Lifecycle of LLM-as-a-Judge for Large-Scale Recommendation Explanations

arXiv:2608.18300v1 Announce Type: new Abstract: LLM-as-a-Judge, which leverages a large language model to evaluate natural language generated by another AI application or model, has become a standard,

The Road Taken: The Role of Optimizers at the Edge of Stability

arXiv:2608.18415v1 Announce Type: new Abstract: The edge of stability refers to a phenomenon in deep learning with gradient-based optimizers where the Hessian eigenvalues of the loss remain stable abo

safetyarxiv-cs-lg

The Role of Grid Cells in Reducing Spatial Aliasing in Hippocampal Place Representations

arXiv:2608.18569v1 Announce Type: cross Abstract: Spatial aliasing occurs when two or more distinct locations produce highly similar place-cell representations, primarily due to environmental symmetry

Think Shallow, Solve Deep: Controlling Recurrent Dynamics for Reliable Test-Time Depth

arXiv:2608.18222v1 Announce Type: cross Abstract: Recurrent-depth reasoners aim to solve harder problems by iterating their update longer at test time, but additional iterations can improve, preserve,

safetyarxiv-cs-cl

Tianmu-TC: Physics-constraints Generative Artificial Intelligence for Global Tropical Cyclone Forecasting

arXiv:2608.18500v1 Announce Type: new Abstract: Tropical cyclones (TCs) pose severe risks from strong winds and heavy rainfall. However, forecasting their track and intensity remains challenging due t

To Go Far, Go Together: Diverse Preferences Induce a Curriculum for Reward Optimization

arXiv:2608.18770v1 Announce Type: cross Abstract: Learning a reward model from human feedback and optimizing a policy against it is one approach to aligning AI systems with individual users. From a fa

safetyarxiv-cs-ro

Hardware

TokenPowerSandbox: Evidence-Gated CPU-First Screening for Energy-Aware LLM Serving

arXiv:2608.18149v1 Announce Type: cross Abstract: Energy-aware LLM serving requires comparing configurations under realistic request shapes, yet exhaustive target-GPU profiling is costly and a cheap p

hardwarearxiv-cs-ai

Topology-Aware Differential Privacy in Hierarchical Federated Learning

arXiv:2506.19260v3 Announce Type: replace-cross Abstract: Hierarchical federated learning places regional aggregators between clients and the cloud, so a participant's update is observed only alongsid

Towards Reversible Forgetting: Managing Obsolete Knowledge in Continual Enterprise AI Agents

arXiv:2608.18177v1 Announce Type: new Abstract: Continual learning has traditionally treated forgetting as a failure, emphasizing preservation of previously acquired knowledge as environments evolve.

safetyarxiv-cs-lg

TractoGraphVLM: A Unified Vision-Language Framework for White Matter Tractography

arXiv:2608.18166v1 Announce Type: cross Abstract: Vision language models have transformed 2D medical imaging, yet extending them to 3D white matter tractography remains challenging due to the complex

researcharxiv-cs-cv

Training Chemical Plausibility-Aware Large Language Models for Single-Step Retrosynthesis

arXiv:2608.18940v1 Announce Type: cross Abstract: Single-step retrosynthesis is a central component of computer-aided synthesis planning, yet its intrinsically one-to-many nature is poorly captured by

Agents

Training-Free Inference-Time Self-Reflection and Cost-Bounded Early Stopping for Large Language Models

arXiv:2608.18884v1 Announce Type: new Abstract: Reinforcement-learning training of reasoning LLMs (e.g., GRPO) is expensive and requires a controllable environment, committing every contribution to a

agentsarxiv-cs-ai

Local Ai

Transferable Tool-Tissue Contact Detection from Stereo Depth in Robot-Assisted Surgery

arXiv:2608.18270v1 Announce Type: new Abstract: Reliable tool--tissue contact detection can support interaction-aware control and downstream force estimation in robot-assisted surgery. Most existing m

local-aiarxiv-cs-ro

Transforming Heart Disease Prediction with Advanced Machine Learning Techniques

arXiv:2608.18687v1 Announce Type: new Abstract: Heart disease remains the leading cause of mortality globally, necessitating early and accurate detection to improve patient outcomes. This research foc

TranslatePsy-AfriSLM: High-Quality Data Scaling For Low-Resource Machine Translation

arXiv:2608.18655v1 Announce Type: new Abstract: The rapid progress in Artificial Intelligence has largely bypassed African languages, creating a digital divide that limits AI adoption on the continent

researcharxiv-cs-cl

Applications

Transportable Causal Effect Estimation across Networks under Interference

arXiv:2608.18932v1 Announce Type: new Abstract: Estimating causal effects under network interference typically assumes that the network used for training and the network used for deployment coincide.

applicationsarxiv-cs-lg

TrojanGYM: A Detector-in-the-Loop LLM for Adaptive RTL Hardware Trojan Insertion

arXiv:2601.17178v3 Announce Type: replace-cross Abstract: Hardware Trojans (HTs) remain a critical threat because learning-based detectors often overfit to narrow trigger/payload patterns and small, s

Trust as a Field: A Macroscopic Representation for Vehicular Networks

arXiv:2608.18178v1 Announce Type: new Abstract: Trust assessment is a fundamental component of cooperative and connected vehicle systems. However, existing approaches operate primarily at the level of

researcharxiv-cs-ro

TTSD-FAR: Test-Time Self-Distillation with Fisher-Anchored Restoration for Missing-Modality Emotion Recognition in LVLMs

arXiv:2608.18386v1 Announce Type: cross Abstract: Large video-language models (LVLMs) have shown remarkable performance on multimodal tasks like multimodal emotion recognition (ER) in the wild. ER is

Hardware

Tuning the Stochastic Machine: A Systems Engineer's Operating Model for Human-AI Engineering

arXiv:2608.19125v1 Announce Type: new Abstract: When an expert corrects an LLM assistant's error, the correction usually dies with the session, and the error class returns. I argue this is an operatio

hardwarearxiv-cs-ai

UMER: Unifying Embedding and Ranking via Pair-Aware Discriminative Reasoning for Universal Multimodal Retrieval

arXiv:2608.18504v1 Announce Type: new Abstract: Universal multimodal retrieval aims to support diverse instruction-aware retrieval tasks, demanding both efficient corpus-scale matching and fine-graine

Applications

Uncertainty-Aware Art-Historical Dating with Vision-Language Models

arXiv:2608.18984v1 Announce Type: new Abstract: Museum and archival datasets do not mirror historical artistic production, but materialize the contingent histories of collecting, preservation, catalog

applicationsarxiv-cs-cv

Understanding Multilingual Medical ASR Adaptation Through Layer-Wise Analysis

arXiv:2608.18825v1 Announce Type: cross Abstract: Medical automatic speech recognition (MedASR) requires adaptation to specialised terminology, limited annotated clinical data, and multilingual use ca

Agents

USR-Drive: Unified Driving Scene Representation via Joint Denoising of 3D Gaussians and Boxes

arXiv:2608.19036v1 Announce Type: new Abstract: Spatial representation learning for autonomous driving aims to map raw visual signals into structured 3D scene representations, where object-centric bou

agentsarxiv-cs-cv

VA-Judger: Reward Modeling from Human Preference Feedback for Joint Video-Audio Generation

model-releasesarxiv-cs-cv

arXiv:2608.18607v1 Announce Type: new Abstract: Using reinforcement learning to post-train joint video-audio generation models requires a reward signal. Existing methods construct this reward by combi

Vector Symbolic Policy Gradient

arXiv:2608.18404v1 Announce Type: cross Abstract: We answer this question with Vector-Symbolic Policy Gradient (VSPG), a discrete-action actor that represents each action by a unit-norm hypervector an

safetyarxiv-cs-ai

VERAGMIL: Virtual Environment for Scooping Granular Foods with Imitation Learning Models

arXiv:2608.18258v1 Announce Type: new Abstract: Robot-Assisted Feeding (RAF) systems are essential for assisting individuals with disabilities or motor impairments in eating tasks. Manipulating granul

researcharxiv-cs-ro

Verifiable abstention makes AI leak diagnosis accountable in water distribution networks

arXiv:2608.18836v1 Announce Type: new Abstract: Utilities lose a substantial share of treated water to leakage, yet rarely trust artificial-intelligence localizers to dispatch crews: guessing everywhe

Vision-Language Models for Egocentric Video: From Hand-Object Interaction to Embodied AI

arXiv:2608.18671v1 Announce Type: new Abstract: Egocentric video captures activities from the wearer's perspective, providing a direct view of human attention, hand--object interaction, and goal-direc

safetyarxiv-cs-cv

Visual-Aware Representation of Web Pages for Machine Learning Applications

arXiv:2608.18727v1 Announce Type: new Abstract: Applying machine learning to web pages is challenging due to the need to interpret HTML together with associated resources and perform rendering to obta

Visual-Prompt Guided Wildlife Instance-Level Recognition

arXiv:2608.18246v1 Announce Type: cross Abstract: Fine-grained wildlife re-identification remains a challenging area in research. Current state-of-the-art approaches apply a detection and re-identific

VTONQA: A Multi-Dimensional Quality Assessment Dataset for Virtual Try-on

model-releasesarxiv-cs-cv

arXiv:2601.02945v2 Announce Type: replace Abstract: With the rapid development of e-commerce and digital fashion, image-based virtual try-on (VTON) has attracted increasing attention. However, existin

Weak-to-Strong Generalization via Bregman Bias-Variance Decomposition

arXiv:2505.24313v3 Announce Type: replace Abstract: Weak-to-strong generalization (W2SG) is the phenomenon in which a powerful student model, trained on labels produced by a weaker teacher, ultimately

safetyarxiv-cs-lg

Local Ai

WESPR: Wind-adaptive Energy-Efficient Safe Perception & Planning for Robust Flight with Quadrotors

arXiv:2603.09194v2 Announce Type: replace Abstract: Local wind conditions strongly influence drone performance: headwinds increase flight time, crosswinds and wind shear hinder agility in cluttered sp

local-aiarxiv-cs-ro

Tutorials

What Can Artificial Intelligence Learn from Medicine? Generative Analogies and Reliable Machine Learning Systems

arXiv:2608.18186v1 Announce Type: cross Abstract: In the past few years, machine learning (ML) has been widely (and to an extent, successfully) implemented in medicine. However, uncertainties surround

tutorialsarxiv-cs-ai

What Does Attention Transfer Transfer? Attention Structure and Robustness in Vision Transformers

arXiv:2608.18399v1 Announce Type: new Abstract: Vision transformers (ViTs) trained to copy a pretrained teacher's attention maps recover most of fine-tuning's in-distribution accuracy yet fall measura

researcharxiv-cs-cv