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CounterFlow: A Two-Phase Inference-Time Sampling for Counterfactual Video Foley Generation

arXiv:2605.18916v1 Announce Type: cross Abstract: We investigate Counterfactual Video Foley Generation, which aims to adopt a sound-source identity that contradicts the visual evidence while remaining

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Research

CPC-VAR:Continual Personalized and Compositional Generation in Visual Autoregressive Models

DGX agent

arXiv:2605.19750v1 Announce Type: new Abstract: Visual autoregressive (VAR) models have recently emerged as an efficient paradigm for text-to-image generation. Despite their strong generative capabili

researcharxiv-cs-cv

20 May 2026

CRAFT: Critic-Refined Adaptive Key-Frame Targeting for Multimodal Video Question Answering

arXiv:2605.19075v1 Announce Type: cross Abstract: Grounded multi-video question answering over real-world news events requires systems to surface query-relevant evidence across heterogeneous video arc

CriterAlign: Criterion-Centric Rationale Alignment for Code Preference Judging

arXiv:2605.19665v1 Announce Type: cross Abstract: Pairwise human preference prediction is central to evaluating code-generation systems, where quality often depends on task-specific trade-offs beyond

Critique-Guided Distillation for Robust Reasoning via Refinement

arXiv:2505.11628v4 Announce Type: replace Abstract: Supervised fine-tuning with expert demonstrations often produces models that imitate outputs without internalizing the reasoning processes needed fo

tutorialsarxiv-cs-cl

Cross-modal Consistency Guidance for Robust Emotion Control in Auto-Regressive TTS Models

arXiv:2510.13293v3 Announce Type: replace Abstract: While Text-to-Speech (TTS) systems enable emotional control via natural-language instructions, expressiveness, naturalness, and speech quality degra

safetyarxiv-cs-cl

Cross-Paradigm Knowledge Distillation: A Comprehensive Study of Bidirectional Transfer Between Random Forests and Deep Neural Networks for Big Data Applications

arXiv:2605.19299v1 Announce Type: new Abstract: The exponential growth of big data has intensified the need for efficient and interpretable machine learning models that can handle diverse data charact

Cross-Subject Intracranial EEG Reconstruction from Scalp Recordings Using Multi-Scale Cross-Attention Transformers

arXiv:2605.18897v1 Announce Type: cross Abstract: Intracranial EEG (iEEG) provides high-fidelity neural recordings essential for clinical and brain-computer interface applications, but acquiring these

Cross-View Attention Fusion Net: A Prior-Guided Dual-View Representation Learning for Cardiac Output Estimation from Short-Term PPG Signals

model-releasesarxiv-cs-lg

arXiv:2605.19666v1 Announce Type: cross Abstract: Accurate cardiac output (CO) estimation from photoplethysmography (PPG) is promising for unobtrusive hemodynamic monitoring, but remains difficult sin

Cross-View Splatter: Feed-Forward View Synthesis with Georeferenced Images

arXiv:2605.19656v1 Announce Type: new Abstract: We present Cross-View Splatter, a feed-forward method that predicts pixel-aligned Gaussian splats for outdoor scenes captured at ground level AND by sat

Cubit: Token Mixer with Kernel Ridge Regression

arXiv:2605.06501v2 Announce Type: replace-cross Abstract: Since its introduction in 2017, the Transformer has become one of the most widely adopted architectures in modern deep learning. Despite exten

researcharxiv-cs-cl

CutVerse: A Compositional GUI Agents Benchmark for Media Post-Production Editing

arXiv:2605.19484v1 Announce Type: cross Abstract: While GUI agents have made significant progress in web navigation and basic operating system tasks, their capabilities in professional creative workfl

D-CLING: Prior-Preserving Depth-Conditioned Fine-Tuning for Navigation Foundation Models

arXiv:2605.19690v1 Announce Type: new Abstract: Navigation Foundation Models (NFMs) trained on large cross-embodied datasets have demonstrated powerful generalizability in various scenarios. Adopting

safetyarxiv-cs-ro

D-Convexity: A Unified Differentiable Convex Shape Prior via Quasi-Concavity for Data-driven Image Segmentation

arXiv:2605.19210v1 Announce Type: new Abstract: Convexity is a fundamental geometric prior that underlies many natural and man-made structures, yet remains challenging to impose effectively in end-to-

researcharxiv-cs-cv

D-PACE: Dynamic Position-Aware Cross-Entropy for Parallel Speculative Drafting

arXiv:2605.18810v1 Announce Type: cross Abstract: Speculative decoding accelerates LLM inference by having a small drafter propose tokens that a larger target model verifies in parallel. Recent diffus

D^3-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market

model-releasesarxiv-cs-lg

arXiv:2605.20036v1 Announce Type: new Abstract: Ride-hailing platforms like DiDi Chuxing operate in highly dynamic environments where balancing driver supply and passenger demand is critical. Although

Local Ai

DAG-Based QoS-Aware Dynamic Task Placement for Networked Multi-Stage Control Pipelines

arXiv:2605.19887v1 Announce Type: cross Abstract: Current Physical AI (PAI) relies heavily on closed-loop visual-servoing pipelines, whose perception and planning stages may become computationally int

local-aiarxiv-cs-ro

Applications

DarkLLM: Learning Language-Driven Adversarial Attacks with Large Language Models

arXiv:2605.18868v1 Announce Type: cross Abstract: While vision and multimodal foundation models underpin critical tasks from perception to complex reasoning, they remain highly vulnerable to adversari

applicationsarxiv-cs-ai

Data-centric Design of Learning-based Surgical Gaze Perception Models in Multi-Task Simulation

arXiv:2602.09259v2 Announce Type: replace Abstract: In robot-assisted minimally invasive surgery (RMIS), reduced haptic feedback and depth cues increase reliance on expert visual perception, motivatin

tutorialsarxiv-cs-ro

Data-driven Acceleration of MPC with Guarantees

arXiv:2511.13588v2 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) is a powerful framework for optimal control but can be too slow for low-latency applications. We present a data

Applications

Data-Efficient Self-Supervised Algorithms for Fine-Grained Birdsong Analysis

arXiv:2511.12158v3 Announce Type: replace Abstract: Research in bioacoustics, neuroscience, and linguistics often uses birdsong as a proxy to acquire knowledge across diverse areas. This requires audi

applicationsarxiv-cs-lg

Data-Free Client Contribution Estimation via Logit Maximization for Federated Learning

arXiv:2605.18892v1 Announce Type: cross Abstract: Federated learning (FL) enables collaborative learning of computer vision models, where privacy and regulatory constraints prevent centralizing data a

deadtrees.earth-aerial: A Multi-Resolution Aerial Image Dataset for Tree Cover and Mortality Detection

arXiv:2605.19605v1 Announce Type: new Abstract: Forests worldwide are increasingly threatened by climate change and disturbances such as fire, pests, and pathogens, creating an urgent need for scalabl

Agents

Decentralized autonomous organization and blockchain-based incentivization framework for community-based facilities management

arXiv:2605.18773v1 Announce Type: cross Abstract: Traditional facility management often relies on centralized decision-making structures that limit stakeholder participation, leading to misalignment w

agentsarxiv-cs-ai

Hardware

Decentralized Direct Volume Rendering: A Browser-Native GPU Architecture for MRI Digital Twins in Resource-Constrained Settings

arXiv:2605.19737v1 Announce Type: cross Abstract: Digital Twin (DT) technology holds immense potential for surgical planning and personalized medicine. However, generating interactive, patient-specifi

hardwarearxiv-cs-cv

DecisionBench: A Benchmark for Emergent Delegation in Long-Horizon Agentic Workflows

arXiv:2605.19099v1 Announce Type: new Abstract: We introduce DecisionBench, a benchmark substrate for emergent delegation in long-horizon agentic workflows. The substrate fixes a task suite (GAIA, tau

Decoding Rewards in Competitive Games: Inverse Game Theory with Entropy Regularization

arXiv:2601.12707v2 Announce Type: replace Abstract: Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackl

tutorialsarxiv-cs-lg

Agents

DECOR: Auditing LLM Deception via Information Manipulation Theory

arXiv:2605.19270v1 Announce Type: new Abstract: Large language models can deceive by subtly manipulating truthful information -- omitting key facts, shifting focus, or obscuring meaning -- making such

agentsarxiv-cs-cl

Deep Learning-Assisted Improved Differential Fault Attacks on Lightweight Stream Ciphers

arXiv:2603.29382v2 Announce Type: replace-cross Abstract: Lightweight cryptographic primitives are widely deployed in resource-constrained environments, particularly in Internet of Things (IoT) device

Deep Neural Network for Musical Instrument Recognition using MFCCs

arXiv:2105.00933v3 Announce Type: replace-cross Abstract: The task of efficient automatic music classification is of vital importance and forms the basis for various advanced applications of AI in the

Applications

Deep Neural Sheaf Diffusion

arXiv:2605.19021v1 Announce Type: new Abstract: Deep Graph Neural Networks (GNNs) are essential for capturing complex dependencies in graph-structured data. However, scaling GNNs to depth remains chal

applicationsarxiv-cs-lg

Deep Tech to Space: Space Data Centers and AI Revolution at the Edge

arXiv:2605.19892v1 Announce Type: cross Abstract: Dramatic cost reductions driven by private sector innovations have led to a rapid increase in the number of satellites in orbit and a corresponding su

DEFLECT: Delay-Robust Execution via Flow-matching Likelihood-Estimated Counterfactual Tuning for VLA Policies

arXiv:2605.19294v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies are typically deployed with asynchronous inference: the robot executes a previously predicted action chunk while

Delta Attention Residuals

arXiv:2605.18855v1 Announce Type: cross Abstract: Attention Residuals replace standard additive residual connections with learned softmax attention over previous layer outputs, enabling selective cros

researcharxiv-cs-cv

Density-Ratio Losses for Post-Hoc Learning to Defer

arXiv:2605.19557v1 Announce Type: cross Abstract: We study post-hoc Learning to Defer (L2D) through the lens of ideal distributions: divergence-regularized reweightings of the data distribution under

Depth, Not Data: An Analysis of Hessian Spectral Bifurcation

arXiv:2602.00545v2 Announce Type: replace Abstract: The eigenvalue distribution of the Hessian matrix plays a crucial role in understanding the optimization landscape of deep neural networks. Prior wo

Depth2Pose: A Pose-Based Benchmark for Monocular Depth Estimation without Ground-Truth Depth

arXiv:2605.19797v1 Announce Type: new Abstract: Monocular depth estimation has improved significantly in recent years, driven by increasingly powerful models and large-scale training data. Predicted d

DeRegiME: Deep Regime Mixtures for Probabilistic Forecasting under Distribution Shift

arXiv:2605.19231v1 Announce Type: new Abstract: We introduce DeRegiME -- Deep Regime Mixture of Experts -- a direct multi-horizon probabilistic forecaster that separates latent uncertainty regimes fro

Local Ai

Descriptive versus Regulatory Uncertainty in Bounded Predictive Systems

arXiv:2605.18909v1 Announce Type: new Abstract: Any system that models the world under finite representational capacity must compress; any compression entails a prior; and the prior is the system's bi

local-aiarxiv-cs-lg

Detecting Fluent Optimization-Based Adversarial Prompts via Sequential Entropy Changes

arXiv:2605.19966v1 Announce Type: cross Abstract: Optimization-based adversarial suffixes can jailbreak aligned large language models (LLMs) while remaining fluent, weakening static and windowed perpl

Diagnosing Multi-step Reasoning Failures in Black-box LLMs via Stepwise Confidence Attribution

arXiv:2605.19228v1 Announce Type: cross Abstract: Large Language Models have achieved strong performance on reasoning tasks with objective answers by generating step-by-step solutions, but diagnosing

tutorialsarxiv-cs-ai

Differential-Integral Neural Operator for Long-Term Turbulence Forecasting

arXiv:2509.21196v3 Announce Type: replace-cross Abstract: Accurately forecasting the long-term evolution of turbulence represents a grand challenge in scientific computing and is crucial for applicati

Difficulty-Controllable Cloze Question Distractor Generation

arXiv:2511.01526v2 Announce Type: replace Abstract: Multiple-choice cloze questions are commonly used to assess linguistic proficiency and comprehension. However, generating high-quality distractors r

researcharxiv-cs-cl

Diffusion and Flow-based Copulas: Forgetting and Remembering Dependencies

arXiv:2509.19707v2 Announce Type: replace-cross Abstract: Copulas are a fundamental tool for modelling multivariate dependencies in data, forming the method of choice in diverse fields and application

tutorialsarxiv-cs-lg

Diffusion Graph Posterior Sampling for Nonlinear Inverse Problems with Application to Electrical Impedance Tomography

arXiv:2605.19621v1 Announce Type: cross Abstract: Deep generative models have emerged as state-of-the-art for solving inverse problems, but applying them to inverse problems for PDEs, like electrical

tutorialsarxiv-cs-lg

Digital Voices of Survival: From Social Media Disclosures to Support Provisions for Domestic Violence Victims

arXiv:2509.12288v2 Announce Type: replace-cross Abstract: Domestic Violence (DV) is a pervasive public health problem characterized by patterns of coercive and abusive behavior within intimate relatio

Dimensional Balance Improves Large Scale Spatiotemporal Prediction Performance

arXiv:2605.18793v1 Announce Type: cross Abstract: Accurate spatiotemporal pattern analysis is critical in fields such as urban traffic, meteorology, and public health monitoring. However, existing met

Directed Acyclic Graph Convolutional Networks

arXiv:2506.12218v2 Announce Type: replace-cross Abstract: Directed acyclic graphs (DAGs) are central to science and engineering applications including causal inference, scheduling, and neural architec

safetyarxiv-cs-lg