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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

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

DGX agent

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

researcharxiv-cs-cv

18 Aug 2026

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

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

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

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

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

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

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

Demystifying Oversmoothing in Sheaf Neural Networks: An Index-Theoretic Criterion

arXiv:2608.16180v1 Announce Type: new Abstract: To combat oversmoothing in Graph Convolutional Networks, Sheaf Neural Networks (SNNs) were proposed as a generalization by equipping the graph with a sh

Depth-Dominant Skeleton Detection for Natural Scenes

arXiv:2608.16367v1 Announce Type: new Abstract: To date, all natural scene skeleton detection follows the paradigm of taking RGB images as the sole input; despite notable progress, methods under this

Design Optimization for Large High-Force Soft Robot Manipulators Under Gravitational Loads

arXiv:2608.16728v1 Announce Type: new Abstract: Designing large soft robots capable of generating high forces for physical human-robot interaction remains a significant challenge in soft robotics. Pri

researcharxiv-cs-ro

Detachable Wire Drive : Reconfigurable Robot Architecture with Shared Actuators

arXiv:2608.15461v1 Announce Type: new Abstract: Reconfigurable robots offer significant potential for adapting to diverse tasks; however, conventional centralized architectures often require dedicated

researcharxiv-cs-ro

Detector-Augmented SAMURAI for Long-Duration Drone Tracking

arXiv:2601.04798v2 Announce Type: replace Abstract: Robust long-term tracking of drone is a critical requirement for modern surveillance systems, given their increasing threat potential. While detecto

Developing an Offshore Machine Learning Surface Layer Scheme

arXiv:2608.14935v1 Announce Type: cross Abstract: Turbulent fluxes between the surface and the atmosphere are typically parameterized using empirically fit relationships. Here we test machine learning

Differentiable Thermodynamic Phase-Equilibria for Machine Learning

arXiv:2603.11249v4 Announce Type: replace Abstract: Accurate prediction of phase equilibria remains a central challenge in chemical engineering. Physics-consistent machine learning methods that incorp

DiffSoup: Direct Differentiable Rasterization of Triangle Soup for Extreme Radiance Field Simplification

arXiv:2603.27151v2 Announce Type: replace-cross Abstract: Radiance field reconstruction aims to recover high-quality 3D representations from multi-view RGB images. Recent advances, such as 3D Gaussian

Digital Twin Degradation: Detecting Cyber Physical Attacks via Temporal Inconsistencies

arXiv:2608.16159v1 Announce Type: cross Abstract: Digital Twins (DTs) are increasingly used to monitor and analyze Cyber Physical Systems (CPS). However, in adversarial environments, the fidelity of a

Discrete Diffusion Language Models Are Training-Free Multi-Label Classifiers

arXiv:2608.14649v1 Announce Type: new Abstract: We present dLLM-SetScore, a training-free method that uses discrete masked-diffusion language models for multi-label text classification. For each candi

Disentangling Homophily and Rarity: Explaining Failure in Graph Neural Networks

arXiv:2608.14823v1 Announce Type: new Abstract: Are heterophilic nodes in a graph harder to classify because they are heterophilic or because they are rare? Some existing work frames classification of

Distribution-free false-alarm calibration and chance-corrected spatial evaluation for industrial anomaly detection

arXiv:2608.15090v1 Announce Type: new Abstract: Studies of industrial visual inspection commonly report the area under the receiver operating characteristic curve (AUROC) and the overlap between anoma

Do CNNs Internally Represent Real and Fake Images Differently? A Hidden-Layer Analysis

arXiv:2608.14729v1 Announce Type: new Abstract: Fake/synthetic images are increasingly prevalent, but it remains unclear whether Convolutional Neural Networks (CNNs) process real and fake images in th

Do Language Models Consistently Encode the Current Year?

arXiv:2608.15507v1 Announce Type: new Abstract: A consistent concept of the current time is important for temporal reasoning, yet how language models represent the current time is not well understood.

researcharxiv-cs-cl

Do LLMs Know What to Ask and When? Evaluating Multi-Turn Information Seeking

arXiv:2608.14808v1 Announce Type: new Abstract: When a user question is underspecified, a capable model should recognize that its context is insufficient, identify the missing information, ask for it,

Do Uncertainty Signals Help? A Systematic Study of Uncertainty-Aware Decoding with Rollback Mechanisms

arXiv:2608.14653v1 Announce Type: cross Abstract: Prediction uncertainty is a widely adopted metric for quantifying model confidence, with downstream applications spanning model explanation, data sele

Does 1/2-Tsallis-INF Also Work Well for Best-Arm Identification?

arXiv:2608.15365v1 Announce Type: new Abstract: Regret minimization (RM) and best-arm identification (BAI) are two fundamental objectives in multi-armed bandits. Among regret-minimizing algorithms, 1/

Does the Heart Show Your Pain? Tackling the X-ITE Pain Challenge with Self-Supervised ECG Representation Learning

arXiv:2608.14662v1 Announce Type: cross Abstract: Accurate recognition of pain using physiological signals remains a challenging problem due to pain's subjective nature and high inter-individual varia

Doubly robust nearest neighbors in factor models

arXiv:2211.14297v4 Announce Type: replace-cross Abstract: We introduce and analyze an improved variant of nearest neighbors (NN) for estimation with missing data in latent factor models. We consider a

DSPrompt: Dynamic Soft Prompt Defense Against M-RAG Corruption

arXiv:2608.16536v1 Announce Type: cross Abstract: Multimodal Retrieval Augmented Generation (M-RAG) is increasingly vulnerable to adversarial attacks where malicious data are crafted to produce embedd

researcharxiv-cs-cl

Dual-Branch State-Displacement Network for Sea Surface Temperature Super-Resolution

arXiv:2608.15423v1 Announce Type: cross Abstract: Sea surface temperature (SST) is a critical indicator of global climate change, yet satellite-derived SST imagery often suffers from coarse spatial re

DuplexGen: Decoupling Content, Timing, and Acoustics for Synthetic Dialogue Speech

arXiv:2608.16053v1 Announce Type: new Abstract: Synthetic conversational speech has become an important resource for developing and evaluating conversational speech systems. However, existing dialogue

researcharxiv-cs-cl

Dynamic Evidence Collection Ecosystem for Assessment Integrity and Authentic Competence

arXiv:2608.16016v1 Announce Type: cross Abstract: Generative Artificial Intelligence (GenAI) can produce high-quality essays, code, and design artefacts, challenging the validity of conventional asses

Dynamic Multi-Byte Prediction With Hierarchical Language Models

arXiv:2608.15454v1 Announce Type: new Abstract: Byte-level hierarchical language models (LMs) have recently emerged as a robust alternative to their popular counterparts that use subword tokenization.

EA-LiteUNet: An Edge-Adaptive and Resource-Efficient U-Net for Boundary-Sensitive Dermoscopic Image Segmentation

arXiv:2608.15537v1 Announce Type: cross Abstract: Accurate boundary delineation remains a persistent challenge in dermoscopic image segmentation because of blurred lesion margins, heterogeneous textur

Early Cycle Charge Trajectory Generative Prediction and Full Life Cycle Health Management of Iron-Chromium Flow Batteries Based on FlowBD-E1

arXiv:2608.14637v1 Announce Type: new Abstract: Long-duration stationary energy storage requires batteries whose degradation can be detected before substantial capacity loss has accumulated. Iron-chro

EdgeCrafter: Compact ViTs for Edge Dense Prediction via Task-Specialized Distillation

arXiv:2603.18739v4 Announce Type: replace Abstract: Deploying high-performance dense prediction models on resource-constrained edge devices remains challenging due to strict computation and memory bud

Efficient Audio-Visual Generation via Synchrony-Aware Cross-Modal Sparse Attention

arXiv:2608.15522v1 Announce Type: new Abstract: Recent audio-visual generation models can synthesize synchronized video and sound in a unified diffusion process, but their inference cost remains high

Efficient Code Embeddings from Code Generation Models

arXiv:2508.21290v2 Announce Type: replace-cross Abstract: jina-code-embeddings is a novel code embedding model suite designed to retrieve code from natural language queries, perform technical question

Efficient Neural-Network-Based High-Resolution Radiative Transfer for CO___ Retrieval, and Application to Interferometric Sensing

arXiv:2608.14645v1 Announce Type: new Abstract: Studying climate change requires reducing uncertainties in CO2 and CH4 emission estimates to better distinguish anthropogenic from natural sources, whic

EMASAM: a Computationally Efficient Sharpness-Aware Minimization via EMA-Guided Perturbations

arXiv:2608.15105v1 Announce Type: cross Abstract: Recent progress in optimization research has highlighted the sharpness of the loss landscape as a key factor in narrowing the generalization gap. Moti

Emergent 3D Instance Segmentation from Self-Supervised Point Transformers

arXiv:2608.15796v1 Announce Type: new Abstract: Unsupervised 3D instance segmentation of outdoor LiDAR scans has traditionally relied on handcrafted geometric priors such as density-based clustering,

ENAF: A Multi-Exit Network with an Adaptive Patch Fusion for Large Image Super Resolution

arXiv:2608.15349v1 Announce Type: cross Abstract: To accelerate single image super-resolution (SISR) networks on large images (2K-8K), many recent approaches decompose an image into small patches and

Equilibrium Forcing: Adaptive Video Generation Without Noise Conditioning

arXiv:2608.14706v1 Announce Type: cross Abstract: Standard autoregressive video generation algorithms based on Diffusion and Flow Matching rely on rigid training objectives and static sampling schedul

Euclid-Omni : A Unified Neuro-Symbolic Framework for Plane Geometry

arXiv:2608.14585v1 Announce Type: new Abstract: Euclidean geometry is a compelling testbed for AI reasoning, as it demands the combination of intuitive diagram understanding, axiomatic deduction, and

Evaluating Multimodal LLMs across Text and Audio Modalities for Accessible Disaster Assistance

arXiv:2608.14651v1 Announce Type: new Abstract: Effective disaster risk communication is a foundational humanitarian challenge, yet current emergency infrastructure fails to meet the needs of individu