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Coverage Is Not Containment: A Fundamental Limit of Admission-Time Defenses Against Coordinated Poisoning of Vector Retrieval

arXiv:2608.16044v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) answers a question by retrieving passages from a vector store and trusting them as context, so anyone who can add

researcharxiv-cs-cl

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Coverage-Maximizing Multinomial Subset Routing under Operational Constraints

DGX agent

arXiv:2608.16375v1 Announce Type: cross Abstract: We introduce Multinomial Subset Routing (MSR), a new online routing framework over K experts in which the learner keeps a multinomial routing policy i

safetyarxiv-cs-ai

18 Aug 2026

Credit Fairness: Online Fairness In Shared Resource Pools

arXiv:2601.17944v2 Announce Type: replace-cross Abstract: We study repeated allocation of shared resources among agents with time-varying demands and capped linear utilities. In this setting, independ

CrevasseSeg: A Label-Efficient UAV Crevasse Segmentation Framework

arXiv:2608.15790v1 Announce Type: new Abstract: Crevasse mapping from uncrewed aerial vehicle (UAV) imagery matters for glaciological research and for field safety in glaciated terrain. Yet, pixel-lev

Cross-Domain Industrial Fault Detection by Causal Mechanism Monitoring

arXiv:2608.14666v1 Announce Type: new Abstract: Unsupervised fault detection in industrial systems is dominated by reconstruction based methods that monitor individual sensor marginal distributions. T

Cross-Entropy Risk Estimation for Language Models: Inconsistency Must Be Dense, and the Holdout Method Is No Exception

arXiv:2608.15798v1 Announce Type: new Abstract: Language models are compared by their held-out per-token cross-entropy risk---the quantity scaling laws are fitted to. We show that it cannot be consist

Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening

arXiv:2608.14763v1 Announce Type: cross Abstract: Assessment of ventriculomegaly (VM) on fetal brain ultrasound relies primarily on measuring lateral ventricular atrial width on standard planes, which

Cross-Sign Language Transfer Learning Using Domain Adaptation with Multi-scale Temporal Alignment

arXiv:2608.16804v1 Announce Type: new Abstract: Sign language serves as a vital means of communication for individuals with hearing impairments, yet recognition resources for the over 100 distinct sig

Cross-View Urban Sensing: Mapping Subjective Streetscape Perception via AlphaEarth Embeddings and Urban Context

arXiv:2608.16310v1 Announce Type: new Abstract: Residents' perception of the urban streetscape is an important factor in public health, active mobility, and social wellbeing. Street view imagery (SVI)

CrossView: Can Vision-Language Models Reason Across Cameras?

model-releasesarxiv-cs-cv

arXiv:2608.15539v1 Announce Type: new Abstract: Video understanding benchmarks have long centered on single-camera settings, where modern multi-modal language models achieve strong performance across

Crystal-structure design by agentic AI in a language of motifs

arXiv:2608.15900v1 Announce Type: cross Abstract: Data-driven materials discovery interpolates more reliably than it extrapolates and seldom reaches new structure types. We present MatEvolve, an agent

CSMoE: An Efficient Remote Sensing Foundation Model with Soft Mixture-of-Experts

arXiv:2509.14104v2 Announce Type: replace Abstract: Self-supervised learning (SSL) through masked autoencoders (MAEs) has recently attracted great attention for remote sensing (RS) foundation model (F

CUBICS: Situation-aware performance estimation for safety-relevant ML components

arXiv:2608.16564v1 Announce Type: new Abstract: Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A

CulTrace: Tracing Internal Cultural Reasoning in Large Language Models

arXiv:2508.08879v3 Announce Type: replace-cross Abstract: The growing deployment of large language models (LLMs) across diverse cultural contexts necessitates a deeper understanding of models' hidden

researcharxiv-cs-ai

Cyclops: LiDAR as a Camera That Dreams in Color

arXiv:2608.16264v1 Announce Type: new Abstract: Conventionally, robotic perception relies heavily on cameras due to the rich semantic texture they provide. However, their performance degrades signific

safetyarxiv-cs-ro

CytoFormer: A Molecularly Supervised Cell Foundation Model for Histopathology Cell Classification

arXiv:2608.16718v1 Announce Type: new Abstract: Identifying cell types directly from routine haematoxylin and eosin (H&E) histology would enable single-cell analysis at scale, but training such models

Agents

D2-ScaleAgent: Dual-Dimensional Scaling for Long Document Understanding

arXiv:2608.16417v1 Announce Type: new Abstract: Multi-modal retrieval-augmented generation (RAG) is a key technique for visually rich long document understanding. Existing multi-modal RAG methods are

agentsarxiv-cs-cl

D^{2}R^{2}: Discrete Diffusion with Regulation Reinforcement for Single-Cell Perturbation Prediction

arXiv:2608.15288v1 Announce Type: new Abstract: Predicting single-cell transcriptomic responses to genetic perturbations is central to functional genomics and virtual-cell modeling. Existing approache

DA-RAC: Distance-Aware Calibration of LLM Judges for Trustworthy AI Auditing

arXiv:2608.14950v1 Announce Type: new Abstract: Generative AI systems are increasingly producing real-world artifacts, however their efficacy and validity are often evaluated via context-free LLM-scor

applicationsarxiv-cs-cl

Tutorials

Data-Driven Reconstruction of Spatially Resolved Electron and Ion Energy Distributions from Macroscopic Plasma Quantities with Deep Neural Networks

arXiv:2608.16519v1 Announce Type: cross Abstract: Spatially resolved EEDFs/IEDFs provide essential kinetic information about low-temperature plasmas (LTPs) and play a central role in determining trans

tutorialsarxiv-cs-lg

Data-Efficient and Interpretable Classification of Circulating Tumor Cell Phenotypes in Microfluidic Devices via Deep Learning

arXiv:2608.16870v1 Announce Type: new Abstract: Accurate classification of circulating tumor cell (CTC) phenotypes can provide valuable information for assessing metastatic potential. Label free micro

local-aiarxiv-cs-lg

Data-knowledge dual-driven intelligent framework for full-chain, experiment-efficient synthesis of 2D dendrites

arXiv:2603.16959v2 Announce Type: replace-cross Abstract: Exemplified by the chemical vapor deposition growth of two-dimensional dendrites, which has potential applications in catalysis and presents a

DCA-MoE: Spatially Adaptive Cross-Layer Fusion and Density-Routed Experts for Crowd Counting

arXiv:2608.15213v1 Announce Type: new Abstract: Crowd counting must recover reliable local density under severe variations in perspective, head scale, occlusion, and background clutter. Although moder

local-aiarxiv-cs-cv

Agents

Dear Algo: A Precision-First Agentic Intent Layer for Unified Search and Recommendation

arXiv:2608.15877v1 Announce Type: new Abstract: Search and recommendation serve a shared discovery objective but encode intent differently. We study this boundary through Dear Algo on Threads, a deplo

agentsarxiv-cs-ai

Decentralized Federated Learning for Heterogeneous Multi-Task Semantic Communication

arXiv:2608.15256v1 Announce Type: new Abstract: Collaborative training in distributed semantic communication (DSC) networks typically relies on decentralized federated learning (DFL). However, pushing

Decision-Driven Regularization: A Blended Model for Learning and Optimization

arXiv:2608.15124v1 Announce Type: new Abstract: In contextual optimization, the decision-maker seeks optimal decisions to minimize a cost function, that varies based on observed features. This context

Tutorials

DeCo-MIL: Debiased Counterfactual Reasoning for Long-Tailed Whole Slide Image Analysis

arXiv:2608.14719v1 Announce Type: cross Abstract: Multiple instance learning (MIL) is widely used for weakly supervised whole slide image (WSI) analysis. However, under long-tailed distributions, MIL-

tutorialsarxiv-cs-ai

Decomposing Staleness in Recommender Systems: A Dual-Filter Framework for Supersession and Decay

arXiv:2608.15780v1 Announce Type: cross Abstract: Stale recommendations are a pervasive challenge and a leading source of user complaints on large-scale content platforms. Items lose relevance through

applicationsarxiv-cs-ai

Decomposing Whole Slide Image Report Generation with Graph-Constrained Multiple Instance Learning Workflows

arXiv:2608.15353v1 Announce Type: new Abstract: Whole-slide image (WSI) report generation requires recognizing spatially distributed pathological features and organizing them into a coherent diagnosti

Decorrelation Is Not Complementarity: Skill, Not Lineage, Governs Trusted-Monitor Ensembles

arXiv:2608.16190v1 Announce Type: cross Abstract: Trusted monitoring has a cheap, trusted model score a stronger untrusted model's actions, and a diverse ensemble of them beats a single stronger monit

Decoupled Temporal Encoding for Generative Recommendation

arXiv:2608.16274v1 Announce Type: cross Abstract: Positional encoding is a fundamental component of Transformer-based generative recommendation models, where user histories are modeled as autoregressi

Decoupling Parcellation from Classification: Systematic Benchmark of Fast Brain Segmentation Methods for Alzheimer's Disease Detection

arXiv:2608.16039v1 Announce Type: cross Abstract: Brain parcellation and classification are typically evaluated in isolation, yet downstream AD detection performance depends on their interaction. We d

Deep Analog: Open-Set Film Emulation with Reference-Conditioned 3D LUTs

arXiv:2608.14702v1 Announce Type: new Abstract: Film emulation reproduces the look of an analog film stock on a new digital photograph. We target its open-set form -- matching any reference film frame

Deep learning-based computed tomography (CT) derived body composition classifier for colorectal cancer patients

arXiv:2608.15712v1 Announce Type: cross Abstract: Background: Accurate body composition analysis using Computed Tomography (CT) scans is essential for assessing skeletal muscle area (SMA) and skeletal

Deep Learning for BioImaging: What Are We Really Learning?

model-releasesarxiv-cs-cv

arXiv:2603.13377v2 Announce Type: replace Abstract: Representation learning has driven major advances in natural image analysis by enabling models to acquire high-level semantic features. In microscop

Deep Probabilistic Indoor Gas Source Localization via Physical Dependency-Guided Sequential Inference

arXiv:2608.16221v1 Announce Type: new Abstract: Reliable gas source localization (GSL) is critical to safety in industrial and urban environments, yet remains challenging indoors because walls and obs

local-aiarxiv-cs-ro

Deep Thought Alignment: Trajectory-Level Latent Distillation for Video Reasoning

arXiv:2608.16316v1 Announce Type: cross Abstract: Large Multimodal Models (LMMs) for video reasoning have long been hindered by the high computational cost of processing vast amounts of visual informa

DeepInsight II: One Trace from Benchmark to Robot

arXiv:2608.16556v1 Announce Type: new Abstract: Across a Physical AI stack, evaluation maturity is inversely aligned with deployment risk: foundation models enjoy mature, standardized harnesses, while

DeepOHeat-v2: Self-Improving Operator Learning for Fast and Trustworthy Thermal Optimization in 3D-IC Design

arXiv:2608.16080v1 Announce Type: new Abstract: Thermal-aware optimization of multi-die 3D integrated circuits evaluates many designs, each a costly heat-equation solve. Operator-learning surrogates r

Defake-o3: From Speculative Rationales to Verifiable Evidence for Explainable AIGI Detection

arXiv:2608.16259v1 Announce Type: cross Abstract: The rapid progress of image generation models calls for AI-generated image (AIGI) detectors that are not only accurate but also explainable and reliab

Degeneracy Counting Quantum Algorithm using Decoherence

arXiv:2608.14941v1 Announce Type: new Abstract: Counting the global optima of a classical optimization problem is a #P-hard task. We develop the canonical thermal pure quantum (CTPQ) state-based degen

Degenerate in Whose Frame? An Equivariance Condition for Degeneracy Detection in LiDAR Registration

arXiv:2608.15532v1 Announce Type: new Abstract: Degeneracy detectors for LiDAR registration commonly return six per-axis binary labels. We ask whether these labels are properties of the scene. Under a

researcharxiv-cs-ro

Degradation-Aligned Self-Supervised Learning for State of Health Estimation of Lithium-Ion Batteries under Label Sparsity

arXiv:2608.16612v1 Announce Type: cross Abstract: An accurate estimation of the state of health (SOH) underpins a safe and optimized use of the battery system. Although compelling, data-driven SOH est

applicationsarxiv-cs-ai

DeltaLog: Deferred Materialization of Recurrent States for Linear Attention Decoding

arXiv:2608.15533v1 Announce Type: cross Abstract: Linear attention models eliminate the quadratic prefix computation and context-growing KV cache of softmax attention by replacing pairwise token inter

Demand-Driven Vertiport Siting and Discrete-Event Fleet Simulation for On-Demand Urban Air Mobility Network Design

arXiv:2608.14974v1 Announce Type: new Abstract: This paper presents a demand-driven framework for on-demand Urban Air Mobility (UAM) network design that links vertiport siting, fleet simulation, and d

applicationsarxiv-cs-ai

Demo: Real-time Generative Multicasting with On-Device Intent-aware Semantic Decomposition

arXiv:2608.14600v1 Announce Type: cross Abstract: We present a demonstration for generative multicasting with on-device, intent-aware semantic decomposition. At the transmitter, DNN-based segmentation

local-aiarxiv-cs-lg

Demographic Injection in Medical Language Models under Diversity, Equity, and Inclusion Prompts

arXiv:2608.15254v1 Announce Type: new Abstract: Clinical-AI guidance increasingly recommends prompting language models to reason with attention to diversity, equity, and inclusion (DEI). We measure a

researcharxiv-cs-ai

DeMTS: Denoising Trajectories as Multivariate Time Series for Hallucination Detection in Diffusion Language Models

arXiv:2608.14632v1 Announce Type: cross Abstract: Diffusion large language models (D-LLMs) have emerged as a promising paradigm for text generation. However, similar to autoregressive LLMs, D-LLMs rem

researcharxiv-cs-ai