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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

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Dense Expands, Sparse Anchors: Channel-Asymmetric Query Expansion for Hybrid Retrieval

DGX agent

arXiv:2608.15851v1 Announce Type: cross Abstract: LLM-based query expansion improves retrieval by generating document-like passages. In hybrid retrieval, however, most evaluations fuse fixed top-L den

safetyarxiv-cs-cl

18 Aug 2026

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Density-Reweighted Entropic Optimal Transport: Decoupling Geometry from Sampling Density

arXiv:2608.16506v1 Announce Type: cross Abstract: Dataset alignment is a central step in data analysis across science and engineering, where the goal is to match observations between datasets. Entropi

safetyarxiv-cs-lg

Deploying Frontier Agentic Technology in MOOSEnger, a Multiphysics-Capable AI Assistant

model-releasesarxiv-cs-lg

arXiv:2608.15881v1 Announce Type: new Abstract: The Multiphysics Object-Oriented Simulation Environment (MOOSE) is an open-source finite-element framework for building multiphysics simulation applicat

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

Depth-guided Multi-view Exposure Bracketing for HDR Robot Vision

arXiv:2608.16014v1 Announce Type: new Abstract: Achieving reliable single-shot high dynamic range (HDR) imaging under extreme illumination conditions remains a long-standing challenge, yet no comprehe

DepthArb: Training-Free Depth-Arbitrated Generation for Occlusion-Robust Image Synthesis

arXiv:2603.23924v2 Announce Type: replace Abstract: Text-to-image models often struggle to synthesize correct occlusion relationships among multiple objects, especially in densely overlapping regions.

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

Detecting Money Laundering in Rwandan Mobile Money: A Machine Learning Framework

model-releasesarxiv-cs-lg

arXiv:2608.15447v1 Announce Type: new Abstract: Mobile money has widened financial access across Sub-Saharan Africa and enlarged the surface for money-laundering and terrorism-financing (ML/TF) activi

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

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Diagnosing and Mitigating Perception-Decision Misalignment in Omni-LLMs via Modality Subspace Activation

arXiv:2608.14655v1 Announce Type: cross Abstract: Omni-Large Language Models (Omni-LLMs) power complex multi-modal reasoning in applications like World Action Models and autonomous agents. However, th

agentsarxiv-cs-cv

Diagnosing Dense Same-Class Attribute Misbinding in Large Vision-Language Models

arXiv:2608.16805v1 Announce Type: cross Abstract: Large vision-language models can recognize the objects and attributes in a crowded scene yet assign an attribute to the wrong same-class instance. Gen

DiagnosisArena: Benchmarking Diagnostic Reasoning for Large Language Models

arXiv:2505.14107v5 Announce Type: replace-cross Abstract: The emergence of groundbreaking large language models capable of performing complex reasoning tasks holds significant promise for addressing v

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

Diffusion-model approach to flavor models: A case study for S_4^prime modular flavor model

model-releasesarxiv-cs-lg

arXiv:2504.00944v2 Announce Type: replace-cross Abstract: We propose a numerical method of searching for parameters with experimental constraints in generic flavor models by utilizing diffusion models

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

DirMixE: Harnessing Test Agnostic Long-tail Recognition with Hierarchical Label Variations

arXiv:2405.07780v3 Announce Type: replace-cross Abstract: This paper explores test-agnostic long-tail recognition, a challenging long-tail task where the test label distributions are unknown and arbit

DiSA-IQL: Offline Reinforcement Learning for Robust Soft Robot Control under Distribution Shifts

arXiv:2510.00358v2 Announce Type: replace-cross Abstract: Soft snake robots offer remarkable flexibility and adaptability in complex environments, yet their control remains challenging due to highly n

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Discovering High-Quality Chess Puzzles with Offline Reinforcement Learning

arXiv:2608.14851v1 Announce Type: new Abstract: Learning and skill mastery require extensive and deliberate practice. In many learning settings, producing high-quality pedagogical materials can requir

safetyarxiv-cs-ai

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

Disentangling Pictorial Cue Understanding from Language Bias in VLMs via Depth Ordering Task

arXiv:2607.01503v2 Announce Type: replace Abstract: In this paper, we study depth perception of vision-language models (VLMs) to isolate the effects of pictorial depth cues and disentangle vision and

Distinguishing AI-Generated Music from Edited Audio as a Hard-Negative Robustness Task

arXiv:2608.14916v1 Announce Type: cross Abstract: AI-generated music detectors are commonly evaluated against original songs, but real-world uploads are often remixed, re-encoded, pitch-shifted, or ot

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

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Divergent-Convergent Reasoning: Scaling Test-Time Compute through Structured Solution Synthesis

arXiv:2608.15303v1 Announce Type: new Abstract: Test-time compute can substantially improve Large Language Model (LLM) reasoning performance, yet how and when additional compute helps remains poorly u

agentsarxiv-cs-ai

Do Assessment Instruments Measure the Same Thing for Humans and LLMs? A Latent Structure Analysis

arXiv:2608.15630v1 Announce Type: cross Abstract: The rapid development and growing deployment of large language models (LLMs) have made it increasingly important to understand their capabilities. A c

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 Geometry-Aware Positional Encodings Help Transformers in Spatial Imperfect-Information Games?

arXiv:2608.14982v1 Announce Type: cross Abstract: Transformers applied to spatial imperfect-information games must represent map geometry while tracking hidden entities through time. We ask whether ge

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 LLM Agents Negotiate Rationally? A Mechanism-Design Framework for Verifiable Multi-Agent Interaction over A2A/MCP

arXiv:2608.14613v1 Announce Type: new Abstract: Modern LLM-agent frameworks increasingly interoperate through standards such as Anthropic's Model Context Protocol (MCP) for agent-to-tool access and Go

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

Do Visual Grounding Decoders Need Feed-Forward Networks? A Controlled Study over Frozen Vision-Language Features

arXiv:2608.15061v1 Announce Type: new Abstract: Do feed-forward networks (FFNs) in visual grounding decoders add essential computation once a pretrained vision-language model has already encoded image

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 a Tool Result Carry More Authority Than Plain Text? Three Prospective Studies of False-Claim Adoption in a Synthetic Assignment Task with Claude Opus 5

arXiv:2608.14992v1 Announce Type: new Abstract: Language-model systems increasingly read from stores they also write to, so a claim that was merely written earlier can return looking retrieved. We tes

Does generative AI supersede supervised XMLC? A Benchmark Study on Automated Subject Indexing with German Scientific Literature

arXiv:2607.14882v2 Announce Type: replace-cross Abstract: With a large controlled vocabulary as the label set, the task of automated subject indexing in a library can be understood as a multi-label cl

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

Does the LM Head Create a Harmful Gradient Bottleneck? A Causal Test

model-releasesarxiv-cs-cl

arXiv:2608.16671v1 Announce Type: new Abstract: The language-model head maps a hidden state of width D to a vocabulary of size V, so its transpose can return at most D independent directions to the Tr

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Does the Proof Prove It That Way? Faithful Formalization of Elements Proofs

arXiv:2608.15432v1 Announce Type: new Abstract: In formal verification, both the autoformalization of statements and automated proof search have been studied extensively. While automated proof search

agentsarxiv-cs-ai

Domain-Agnostic Neural Topic Modeling with Contextual Token-Level Semantic Graph Representation

model-releasesarxiv-cs-cl

arXiv:2608.16269v1 Announce Type: new Abstract: Recent advances in neural topic models with pre-trained language models (PLMs) have achieved strong performance by leveraging general-domain pre-trainin

Tutorials

Domain Agnostic Text Redaction from Natural Language Rules using Instruction Tuning

arXiv:2608.14693v1 Announce Type: cross Abstract: With the increasing digitization of personal and corporate communication, the automatic sanitization of textual data has become a crucial component of

tutorialsarxiv-cs-ai

Domain-Specific Text Embedding Models for Entity Resolution

arXiv:2608.16161v1 Announce Type: cross Abstract: General-purpose text embedding models are designed to capture semantic similarity but are not optimised for distinguishing entity records that represe

Don't Drop the BATON: Long-Horizon Robot Manipulation via Agentic Subtask Exploration and Transition-aware Memory

arXiv:2608.16889v1 Announce Type: cross Abstract: Long-horizon robot manipulation chains many contact-rich skills into one multi-stage task. Vision-language-action (VLA) models increasingly master the

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

DPNet: Efficient Dead-End Prediction and Avoidance for Vision-Based UAV Navigation

arXiv:2608.16640v1 Announce Type: new Abstract: Vision-based Unmanned Aerial Vehicles (UAVs) often suffer from navigation failures in dead ends due to limited sensing accuracy and range. To address th

applicationsarxiv-cs-ro