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Corruptions of Supervised Learning Problems: Typology and Mitigations

arXiv:2307.08643v4 Announce Type: replace Abstract: Corruption is notoriously widespread in data collection. Despite extensive research, the existing literature predominantly focuses on specific setti

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CosFly-Track: A Large-Scale Multi-Modal Dataset for UAV Visual Tracking via Multi-Constraint Trajectory Optimization

DGX agent

arXiv:2605.17776v1 Announce Type: new Abstract: Recent aerial vision-language navigation (VLN) datasets have grown rapidly, but they primarily address goal-oriented navigation to static destinations,

researcharxiv-cs-ro

19 May 2026

CoUn: Empowering Machine Unlearning via Contrastive Learning

arXiv:2509.16391v3 Announce Type: replace-cross Abstract: Machine unlearning (MU) aims to remove the influence of specific 'forget' data from a trained model while preserving its knowledge of the rema

Counterfactual Explanations Under Concept Drift

arXiv:2605.17651v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) provide actionable recourse, but most methods assume a static framework with fixed data and a trained classifier. Thi

Counterparty Modeling is Not Strategy: The Limits of LLM Negotiators

arXiv:2605.16575v1 Announce Type: new Abstract: Negotiation requires more than inferring what the other side wants: it requires using that information to make advantageous offers and counteroffers ove

Counting Machine Parts

arXiv:2605.17952v1 Announce Type: new Abstract: Counting objects in an image is a task applicable across many domains. For instance, crowd counting, inventory counting, and cell counting have been the

Cultivating Forensic Reasoning for Generalizable Multimodal Manipulation Detection

arXiv:2603.01993v2 Announce Type: replace Abstract: Recent advances in generative AI have significantly enhanced the realism of multimodal media manipulation, thereby posing substantial challenges to

CyberCorrect: A Cybernetic Framework for Closed-Loop Self-Correction in Large Language Models

arXiv:2605.17305v1 Announce Type: new Abstract: Large language model (LLM) self-correction -- the ability to detect and fix errors in generated outputs -- remains largely ad hoc, relying on generic pr

D^2Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning

arXiv:2605.17037v1 Announce Type: cross Abstract: Reinforcement learning (RL) has demonstrated potential for enhancing reasoning in large language models (LLMs). However, effective RL training, which

DASH: A Meta-Attack Framework for Synthesizing Effective and Stealthy Adversarial Examples

arXiv:2508.13309v3 Announce Type: replace Abstract: Numerous techniques have been proposed for generating adversarial examples in white-box settings under strict Lp-norm constraints. However, such nor

Data-Driven Dynamic Modeling of a Tendon-Actuated Continuum Robot

arXiv:2605.18720v1 Announce Type: new Abstract: Developing dynamic models for tendon-driven continuum robots is challenging due to their nonlinear, high-dimensional, and friction-dominated dynamics. T

researcharxiv-cs-ro

DCFold: Efficient Protein Structure Generation with Single Forward Pass

arXiv:2605.17899v1 Announce Type: cross Abstract: AlphaFold3 introduces a diffusion-based architecture that elevates protein structure prediction to all-atom resolution with improved accuracy. This st

DecoRec: Decomposed 3D Scene Reconstruction from Single-View Images via Object-Level Diffusion

arXiv:2605.16807v1 Announce Type: new Abstract: In this paper, we introduce extit{DecoRec}, a novel system designed to elevate single-view 2D images to a decomposed 3D scene mesh. Current methods for

Decoupling Motion and Geometry in 4D Gaussian Splatting

arXiv:2603.00952v2 Announce Type: replace Abstract: High-fidelity reconstruction of dynamic scenes is an important yet challenging problem. While recent 4D Gaussian Splatting (4DGS) has demonstrated t

Deep Learning-Based Channel Extrapolation for Dual-Band Massive MIMO Systems

arXiv:2601.06858v2 Announce Type: replace-cross Abstract: Future wireless communication systems will increasingly rely on the integration of millimeter wave (mmWave) and sub-6 GHz bands to meet hetero

Deep learning-based compression of giga-resolution whole slide images

arXiv:2605.17668v1 Announce Type: new Abstract: Implementation of digital pathology leads to an increased number of whole slide images (WSIs). The large size of WSIs is challenging. Today, WSIs are co

Deep Learning for MRI Slice Interpolation: The Critical Role of Problem Formulation

arXiv:2605.16476v1 Announce Type: cross Abstract: Through-plane resolution in clinical MRI is typically much coarser than in-plane resolution, limiting diagnostic utility. This work investigates deep

Deepfake Detection in Social Media: A Temporal Artifact Analysis Using 3D Convolutional Neural Networks

arXiv:2605.17573v1 Announce Type: new Abstract: Synthetic facial videos have proliferated across social media faster than platform moderation can respond, raising the cost of disinformation and identi

DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis

arXiv:2601.05527v2 Announce Type: replace-cross Abstract: Accurate and efficient multivariate time series (MTS) analysis is increasingly critical for a wide range of intelligent applications. Within t

DexWild: Dexterous Human Interactions for In-the-Wild Robot Policies

arXiv:2505.07813v2 Announce Type: replace-cross Abstract: Large-scale, diverse robot datasets have emerged as a promising path toward enabling dexterous manipulation policies to generalize to novel en

Dimension-Free Convergence of Discrete Diffusion Models: Adjoint Equations Induce the Right Space

arXiv:2605.17232v1 Announce Type: new Abstract: Discrete diffusion has become a leading framework for generative modeling in various applications including language, vision, and biology. Existing conv

Dimension-Uniform Discretization Analysis of Preconditioned Annealed Langevin Dynamics for Multimodal Gaussian Mixtures

arXiv:2605.16473v1 Announce Type: cross Abstract: Obtaining stable diffusion-based samplers in high- and infinite-dimensional settings is challenging because errors can accumulate across high-frequenc

Divergence-Suppressing Couplings for Rectified Flow

arXiv:2605.17733v1 Announce Type: new Abstract: The promise of Rectified Flow rests on producing self-generated couplings whose trajectories are straight, or nearly so. In practice, trajectories gener

Do Robots Really Need Anthropomorphic Hands? A Comparison of Human and Robotic Hands

arXiv:2508.05415v3 Announce Type: replace Abstract: Human manipulation skills represent a pinnacle of their voluntary motor functions, requiring the coordination of many degrees of freedom and process

researcharxiv-cs-ro

Do You Need Text Rectification? Soft Attention Mask Embedding for Rectification-Free Scene Text Spotting

arXiv:2605.18173v1 Announce Type: new Abstract: End-to-end scene text spotting, which unifies text detection and recognition within a single framework, has witnessed remarkable progress driven by deep

Does Your Reasoning Model Implicitly Know When to Stop Thinking?

arXiv:2602.08354v5 Announce Type: replace Abstract: Recent advancements in large reasoning models (LRMs) have greatly improved their capabilities on complex reasoning tasks through Long Chains of Thou

Domain Incremental Learning for Pandemic-Resilient Chest X-Ray Analysis

arXiv:2605.17729v1 Announce Type: cross Abstract: Deep learning models achieved high accuracy in pneumonia detection from chest X-rays. However, their generalization across clinical domains remains li

Donald Trump is running the greatest grift in American history. It’s corruption at a scale we've never seen in our lifetime.

I cannot provide a summary of this post because the URL provided appears to be invalid (the status ID format seems fabricated), and I cannot verify the actual content or confirm whether Yann LeCun mad

researchyann-lecun--x

Double-Calibration: Towards Reliable LLMs via Calibrating Knowledge and Reasoning Confidence

arXiv:2601.11956v2 Announce Type: replace-cross Abstract: Reliable reasoning in Large Language Models (LLMs) is challenged by their propensity for hallucination. While augmenting LLMs with Knowledge G

Drift Flow Matching

arXiv:2605.17244v1 Announce Type: cross Abstract: Iterative generative models such as Flow Matching and Diffusion models have demonstrated strong test-time scaling behavior, where additional inference

Dual-Rate Diffusion: Accelerating diffusion models with an interleaved heavy-light network

arXiv:2605.18190v1 Announce Type: cross Abstract: Diffusion models achieve state-of-the-art generative performance but suffer from high computational costs during inference due to the repeated evaluat

Dynamic robotic cloth folding with efficient Koopman operator-based model predictive control

arXiv:2605.18373v1 Announce Type: cross Abstract: Robotic cloth folding is a challenging task, particularly when considering dynamic folding tasks, which aim at folding cloth by fast motions that leve

E-PMQ: Expert-Guided Post-Merge Quantization with Merged-Weight Anchoring

arXiv:2605.16882v1 Announce Type: new Abstract: Low-resource deployment constraints have made model quantization essential for deploying neural networks while preserving performance. Meanwhile, model

researcharxiv-cs-cl

EAGT: Echocardiography Augmentation for Generalisability and Transferability

arXiv:2605.16427v1 Announce Type: cross Abstract: Deep learning models for echocardiography segmentation often struggle to generalise across institutions, scanners, and patient populations, where coll

Early Stopping Chain-of-thoughts in Large Language Models

arXiv:2509.14004v2 Announce Type: replace Abstract: Reasoning large language models (LLMs) have demonstrated superior capacities in solving complicated problems by generating long chain-of-thoughts (C

researcharxiv-cs-cl

EchoSR: Efficient Context Harnessing for Lightweight Image Super-Resolution

arXiv:2605.17470v1 Announce Type: new Abstract: Image super-resolution (SR) aims to reconstruct high-quality, high-resolution (HR) images from low-resolution (LR) inputs and plays a critical role in v

Efficient and Noise-Tolerant PAC Learning of Multiclass Linear Classifiers

arXiv:2605.18662v1 Announce Type: new Abstract: Noise-tolerant PAC learning of linear models has been of central interests in machine learning community since the last century. In recent years, many c

Efficient Feature-Free Initialization for Monocular Visual-Inertial Systems Using a Feed-Forward 3D Model

arXiv:2605.17327v1 Announce Type: cross Abstract: Fast and reliable initialization is critical for monocular visual-inertial navigation systems (VINS), as it establishes the starting conditions for su

Efficient Sparse-to-Dense Visual Localization via Compact Gaussian Scene Representation and Accelerated Dense Pose Estimation

arXiv:2605.17777v1 Announce Type: new Abstract: This letter presents LiteLoc, a novel and efficient localizer built on 3D Gaussian Splatting (3DGS). The previous state-of-the-art (SoTA) sparse-to-dens

Efficient Spatially-Variant Convolution via Differentiable Sparse Kernel Complex

arXiv:2512.04556v2 Announce Type: replace-cross Abstract: Image convolution with complex kernels is a fundamental operation in photography, scientific imaging, and animation effects, yet direct dense

EGI: A Multimodal Emotional AI Framework for Enhancing Scrum Master Real-time Self-Awareness

arXiv:2605.17684v1 Announce Type: new Abstract: While increasing research focuses on the emotional well-being of agile team members, a significant gap remains in emotion monitoring studies for Scrum M

Elastic-dLLM: Position Preserving Context Compression and Augmentation of Diffusion LLMs

arXiv:2605.18165v1 Announce Type: new Abstract: Unlike autoregressive models, which generate one token at a time, dLLMs denoise a chunk of [MASK] tokens jointly and sample one or more tokens per step;

Embedded ConvNet Ensembles: A Lightweight Approach to Recognize Arabic Handwritten Characters

arXiv:2605.18060v1 Announce Type: new Abstract: Arabic Handwritten Character Recognition (AHCR) has recently advanced significantly with deep Convolutional Neural Networks (ConvNets). However, many mo

Embracing Anisotropy: Turning Massive Activations into Interpretable Control Knobs for Large Language Models

arXiv:2603.00029v2 Announce Type: replace Abstract: Large Language Models (LLMs) exhibit highly anisotropic internal representations, often characterized by massive activations, a phenomenon where a s

researcharxiv-cs-cl

Empirical evaluation of Time Series Foundation Models for Day-ahead and Imbalance Electricity Price Forecasting in Belgium

arXiv:2605.17045v1 Announce Type: cross Abstract: Recent advances in Time Series Foundation Models (TSFMs) promise zero-shot forecasting capabilities with minimal task-specific training. While these m

Emulating the Forced Response of Climate Models with Flow Matching

arXiv:2605.16929v1 Announce Type: new Abstract: Global climate models are essential tools to simulate past and potential future pathways of climate change, as well as associated climate impacts. Share

Encirclement Guaranteed Finite-Time Capture against Unknown Evader Strategies

arXiv:2603.15278v2 Announce Type: replace-cross Abstract: We consider a pursuit-evasion scenario involving a group of pursuers and a single evader in a two-dimensional unbounded environment. The pursu

researcharxiv-cs-ro

Enhancing Table Reasoning with Deterministic Table-State Rewards

arXiv:2601.22530v2 Announce Type: replace Abstract: Large Language Models (LLMs) struggle with multi-step reasoning over structured tables. The primary reason is the lack of explicit supervision for i