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Compact Feed-Forward 3D Gaussians via Saliency-Guided Primitive Merging

arXiv:2608.10712v1 Announce Type: new Abstract: 3D scene reconstruction, modeling, and rendering are highly relevant for numerous tasks, and 3D Gaussian splatting has become a standard choice in this

researcharxiv-cs-cv

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Compositional Benchmark Synthesis for Hierarchical Human Action Recognition

DGX agent

arXiv:2608.10765v1 Announce Type: new Abstract: Recognizing human behavior across levels of abstraction, from atomic actions to long-horizon intentions, requires data annotated along a semantic hierar

model-releasesarxiv-cs-ai

12 Aug 2026

Comprendia: AI-Augmented Code Comprehension

arXiv:2608.10290v1 Announce Type: cross Abstract: Comprendia is an Eclipse plugin that integrates structural dependency visualization with LLM-powered code explanation on a shared interactive graph fo

Compute-Optimal Is Not Cluster-Optimal: Systems-Aware Scaling for Sparse Mixture-of-Experts

arXiv:2608.10605v1 Announce Type: cross Abstract: In large-scale pretraining, the algorithm, architecture, and systems decisions are conventionally made in disconnected stages. A scaling law stage sel

Conditional Independence Tests for Constraint-Based Causal Discovery: A Survey

arXiv:2608.11156v1 Announce Type: cross Abstract: Conditional Independence (CI) tests are the statistical engine of constraint-based causal discovery: in algorithms such as PC (Peter-Clark) and FCI (F

Conflict or Strategy? Asymmetric Role Framing of La France insoumise and Rassemblement National in French News Headlines, 2022-2025

arXiv:2608.09936v1 Announce Type: new Abstract: Do French news headlines frame left- and right-populist challengers as symmetric ``extremes,'' or as fundamentally different political adversaries? We e

researcharxiv-cs-cl

ConfTriage: A Calibration-Aware LLM Triage Framework for Pulmonary Nodule Malignancy with Selective Specialist Deferral

arXiv:2608.10885v1 Announce Type: new Abstract: Pulmonary nodule malignancy prediction typically depends on image-trained specialist deep learning (DL) models that require substantial annotated imagin

safetyarxiv-cs-cv

ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering

arXiv:2608.10996v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many

safetyarxiv-cs-cl

Continuous Interaction Diffusion: A Diffusion-Native Runtime for Asynchronous Tool-Augmented Reasoning

arXiv:2608.10438v1 Announce Type: new Abstract: Large language models increasingly rely on external tools to access up-to-date information, perform computation, and interact with the outside world. Fo

agentsarxiv-cs-ai

ConVAWG: A Retrieval-Grounded Framework for Controlled Synthetic Dialogue Generation in Violence Against Women and Girls

arXiv:2608.11200v1 Announce Type: cross Abstract: Synthetic dialogue generation offers a way to study conversational dynamics in sensitive domains where real data are difficult to access, release, or

applicationsarxiv-cs-ai

Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization

arXiv:2310.15976v4 Announce Type: replace Abstract: signSGD is attractive in nonconvex optimization because it communicates sign-valued rather than full-precision gradients. Several standard analyses

safetyarxiv-cs-lg

Local Ai

Conversational Orchestration for Organic 6G

arXiv:2608.10714v1 Announce Type: cross Abstract: The Organic 6G vision of a network of networks spanning an edge-cloud continuum complemented by non-terrestrial resources requires, to realize its pro

local-aiarxiv-cs-ai

Conversational versus Dashboard Explainable AI for UAV Intrusion Detection: An Empirical Study of Operator Trust and Reliance

arXiv:2608.10434v1 Announce Type: new Abstract: Machine learning-based Intrusion Detection Systems (IDS) have demonstrated superior performance in securing Unmanned Aerial Vehicle (UAV) networks. Howe

Coordinating the Unknown Lipschitz Constant in Multiplayer Bandits

arXiv:2608.10526v1 Announce Type: cross Abstract: Motivated by decentralized applications, we study cooperative multi-agent bandits in continuous (Lipschitz) action spaces when the Lipschitz constant

agentsarxiv-cs-ai

Cost-Efficient Estimation of General Abilities Across Benchmarks

model-releasesarxiv-cs-cl

arXiv:2604.01418v2 Announce Type: replace Abstract: Thousands of diverse benchmarks have been developed to measure the quality of large language models (LLMs). Yet prior work has demonstrated that LLM

Covert Visual Prompt Injection against Commercial Multimodal Large Language Models

arXiv:2603.29418v2 Announce Type: replace-cross Abstract: Although multimodal large language models (MLLMs) are increasingly deployed in real-world applications, their instruction-following behavior l

applicationsarxiv-cs-ai

Cracks in the Foundation: Seemingly Minor Architectural Choices Impact Long Context Extension

model-releasesarxiv-cs-cl

arXiv:2608.10296v1 Announce Type: new Abstract: One might imagine that architectural variations within the dense transformer paradigm have a limited effect on accuracy. However, we demonstrate that th

CRHT: A Continuous Regression Hybrid Transformer for Vessel Trajectory Prediction with Online Cluster Sampling

arXiv:2608.10256v1 Announce Type: new Abstract: Accurate vessel trajectory prediction is critical for maritime safety and anomaly detection, yet existing models often struggle with geographic bias and

safetyarxiv-cs-lg

Critic-Free Pretraining for Efficient Online Reinforcement Learning Fine-Tuning

arXiv:2608.10473v1 Announce Type: cross Abstract: Offline-to-online (O2O) reinforcement learning aims to leverage policies pretrained on static datasets while improving them through online interaction

safetyarxiv-cs-ai

Cross-View Feature Matching: Survey, Benchmarking, and Foundation-Model Perspectives

arXiv:2608.11093v1 Announce Type: cross Abstract: Cross-view feature matching aims to establish reliable correspondences across images with large viewpoint variations. Over the past decade, the field

researcharxiv-cs-cv

Cross-View Sequential Visual Localization with Spatio-Temporal Context Modeling for Autonomous Driving

arXiv:2608.10660v1 Announce Type: cross Abstract: Continuous and reliable localization is essential for autonomous driving. Cross-view visual localization matches ground images with satellite maps, pr

agentsarxiv-cs-ai

Curate Before You Connect: Identity and Ontology Tagging in a Production Knowledge Graph

model-releasesarxiv-cs-ai

arXiv:2608.10644v1 Announce Type: new Abstract: Extraction produces candidate entities and relationships; writing them into a graph is where identity is decided, and identity decisions are destructive

CurveFP: Rational-Radix Logarithmic Datatypes with Closed Products for Language Models

arXiv:2608.10010v1 Announce Type: new Abstract: Low-precision datatypes reduce language-model cost, but most formats optimize scalar fidelity while leaving the arithmetic induced by their products unc

DACRI: Decision-Aware Causal Intervention Ranking for Critical Supply Chains

arXiv:2608.11154v1 Announce Type: new Abstract: Detecting or attributing a supply-chain disruption is not the same as selecting the intervention that maximizes recoverable net value. We present Critic

DashArena: Benchmarking LLMs on Interactive Analytic Dashboard Generation

model-releasesarxiv-cs-ai

arXiv:2608.10567v1 Announce Type: new Abstract: Analytic dashboards combine coordinated views and interactions for data exploration and decision-making. Recent models can generate them from data and n

Data Attribution of Emergent Misalignment with Persona Features

arXiv:2608.11025v1 Announce Type: new Abstract: Emergent misalignment (EM) is the phenomenon where fine-tuning a language model on a narrow task leads to harmful behavior in unrelated domains. A leadi

safetyarxiv-cs-cl

Deciding When to Switch: E-Processes for Adaptive Minimax Training for Generative Adversarial Nets

arXiv:2608.10096v1 Announce Type: cross Abstract: Modern data science increasingly gives rise to hypothesis-testing problems that are not naturally formulated in terms of parameters within prespecifie

Decision-Aware Approximation of Belief Functions for Evidential Combinatorial Optimization

arXiv:2608.10650v1 Announce Type: new Abstract: Reducing the number of focal elements of a mass function is classically driven by an intrinsic distance, such as Jaccard or Jousselme, that keeps the ap

Decodable But Not Detachable: Training Data Granularity Determines Parametric Modularity in Large Language Models

arXiv:2608.10214v1 Announce Type: new Abstract: Do large language models contain domain-specific parametric shells: concentrated, causally necessary neuron populations whose removal selectively degrad

Decomposition-Induced Context-Memory Conflict: When Fact-Checking Pipelines Contradict Their Own Source Text

arXiv:2608.10627v1 Announce Type: new Abstract: Decompose-then-verify pipelines, including FActScore-style fact-checkers and long-form factuality evaluators, first split a passage into atomic claims b

researcharxiv-cs-cl

Deep Learning-Based Statistical Downscaling of Sea Surface Temperature Using a Residual Corrective Neural Network

arXiv:2608.10022v1 Announce Type: cross Abstract: The large-scale oceanic and atmospheric forecasts provided by global climate models typically lack sufficient resolution to accurately capture the res

applicationsarxiv-cs-lg

DEFT: Data-Efficient Frequency-domain Top-k Sampling via Inverse Discrete Fourier Transform for Spatiotemporal Dynamical Systems Modeling

arXiv:2608.11019v1 Announce Type: new Abstract: Modeling spatiotemporal dynamical systems governed by partial differential equations (PDEs) poses two major challenges: it either requires expensive phy

DegradeQuery: Counterfactual Tuple Pretraining for Context-Aware PROTAC Degradation Prediction

model-releasesarxiv-cs-ai

arXiv:2608.10595v1 Announce Type: cross Abstract: Proteolysis-targeting chimeras (PROTACs) induce protein degradation by recruiting a target protein to an E3 ubiquitin ligase, making degradation a joi

Delays in Spiking Neural Networks: A State Space Model Approach

arXiv:2512.01906v3 Announce Type: replace Abstract: Spiking neural networks (SNNs) are biologically inspired, event-driven models suited for temporal data processing and energy-efficient neuromorphic

Demystifying Adversarial Robustness in Diffusion Models: Compression, Randomness, and Geometry

arXiv:2505.22839v2 Announce Type: replace-cross Abstract: Recent studies suggest that diffusion models significantly improve the empirical adversarial robustness of deep neural network models. While i

Deployment Is Not Destiny: Robot Recomposition in the Field with Unseen Software, Hardware, and Compute Payloads

arXiv:2608.11063v1 Announce Type: new Abstract: The tight coupling of subsystems in most robots, though a natural consequence of their complexity, leads to monolithic designs that are time-consuming a

researcharxiv-cs-ro

Derivative Computation in PINNs: Automatic Differentiation, Finite Differences and Beyond

arXiv:2608.11020v1 Announce Type: new Abstract: We systematically investigate finite-difference (FD) derivative computation in Physics-Informed Neural Networks (PINNs) as an alternative to automatic d

Detecting an Effect Is Not Learning to Act on It: A Reward-SNR Floor for LLM Acquisition Agents

arXiv:2608.10441v1 Announce Type: cross Abstract: Many pipelines can pay a per-example cost to acquire an auxiliary, model-derived observation -- an LLM's structured reasoning, a slow oracle, an expen

safetyarxiv-cs-cl

Detecting Soft Skills in ML Engineering Roles CVs

arXiv:2608.10046v1 Announce Type: new Abstract: Soft skills shape collaboration among ML engineers, data scientists, and software engineers building ML-enabled systems, yet what we know about them com

DHS has lied about these incidents over and over again and been caught in the lies over and over again. They are lying now, and nobody shoul…

DHS has lied about these incidents over and over again and been caught in the lies over and over again. They are lying now, and nobody should believe them. NOW: DHS response to Virginia woman's video

agentsanthropic--x

Diffract: Spectral View of LLM Domain Adaptation

arXiv:2608.10850v1 Announce Type: new Abstract: We study continual pre-training (CPT) as a mechanism for adapting general-purpose large language models to specialized domains: mathematics, instruction

Diffusion-Based Impedance Learning for Contact-Rich Manipulation Tasks

arXiv:2509.19696v4 Announce Type: replace-cross Abstract: Learning-based methods excel at robot motion generation but remain limited in contact-rich physical interaction. Impedance control provides st

DIMOS: Disentangling Instance-level Moving Object Segmentation

arXiv:2606.12826v2 Announce Type: replace-cross Abstract: Moving instance segmentation (MIS) attracts increasing attention due to its broad applications in traffic surveillance, autonomous driving, an

safetyarxiv-cs-ai

Discrete Coefficients and Open Invariant Covers in the Homology of Ample Groupoids

arXiv:2603.20861v2 Announce Type: replace-cross Abstract: The homology of an ample groupoid is computed from the complex of compactly supported continuous functions on the nerve. Two hypotheses routin

DistilVDR: A Compact End-to-End Visual Document Retriever via Dual-Student Distillation

model-releasesarxiv-cs-cl

arXiv:2608.10636v1 Announce Type: cross Abstract: Visual document retrieval (VDR) is dominated by multi-billion-parameter models that are slow to index at full corpus scale and expensive to serve. Pri

Distributional Uncertainty and Adaptive Decision-Making in System Co-design

arXiv:2603.14047v3 Announce Type: replace-cross Abstract: Complex engineered systems require coordinated design choices across heterogeneous components under conflicting objectives and uncertain speci

applicationsarxiv-cs-ro

Do AI weather models miss extremes?

arXiv:2608.09972v1 Announce Type: cross Abstract: First-generation AI weather models are often reported to underperform at extremes, mostly in reanalysis-based evaluations of deterministic regression

safetyarxiv-cs-ai

Do Judges Behave Like Algorithms?

arXiv:2608.10400v1 Announce Type: new Abstract: What if judges already behave like algorithms? As artificial intelligence and algorithms are deployed in many settings, including the judicial system, m