Search: “research”

TimelineReasoner: Advancing Timeline Summarization with Large Reasoning Models

arXiv:2605.12518v1 Announce Type: cross Abstract: The proliferation of online news poses a challenge to extracting structured timelines from unstructured content. While recent studies have shown that

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TinySDP: Real Time Semidefinite Optimization for Certifiable and Agile Edge Robotics

DGX agent

arXiv:2605.13748v1 Announce Type: new Abstract: Semidefinite programming (SDP) provides a principled framework for convex relaxations of nonconvex geometric constraints in motion planning, yet existin

researcharxiv-cs-ro

14 May 2026

TurboGR: An Accelerated Training System for Large-Scale Generative Recommendation

arXiv:2605.13433v1 Announce Type: cross Abstract: Generative recommendation (GR) has emerged as a promising paradigm that replaces fragmented, scenario-specific architectures with unified Transformer-

U-HNO: A U-shaped Hybrid Neural Operator with Sparse-Point Adaptive Routing for Non-stationary PDE Dynamics

arXiv:2605.12965v1 Announce Type: new Abstract: Solutions to many partial differential equations (PDEs) display coexisting smooth global transport and localized sharp features within a single trajecto

UFO: A Domain-Unification-Free Operator Framework for Generalized Operator Learning

arXiv:2605.12700v1 Announce Type: new Abstract: Neural operators have become an effective framework for learning mappings between function spaces, yet most existing architectures realize operators wit

Uncovering Symmetry Transfer in Large Language Models via Layer-Peeled Optimization

arXiv:2605.12756v1 Announce Type: cross Abstract: Large language models (LLMs) are pretrained by minimizing the cross-entropy loss for next-token prediction. In this paper, we study whether this optim

Understanding Generalization through Decision Pattern Shift

arXiv:2605.13148v1 Announce Type: cross Abstract: Understanding why deep neural networks (DNNs) fail to generalize to unseen samples remains a long-standing challenge. Existing studies mainly examine

Unified generalization analysis for physics informed neural networks

arXiv:2605.13260v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) and their variational counterparts (VPINNs) are neural networks that incorporate physical laws, making them use

Unifying Physically-Informed Weather Priors in A Single Model for Image Restoration Across Multiple Adverse Weather Conditions

arXiv:2605.13158v1 Announce Type: new Abstract: Image restoration under multiple adverse weather conditions aims to develop a single model to recover the underlying scene with high visibility. Weather

Utility-Oriented Visual Evidence Selection for Multimodal Retrieval-Augmented Generation

arXiv:2605.13277v1 Announce Type: cross Abstract: Visual evidence selection is a critical component of multimodal retrieval-augmented generation (RAG), yet existing methods typically rely on semantic

Vector-Quantized Discrete Latent Factors Meet Financial Priors: Dynamic Cross-Sectional Stock Ranking Prediction for Portfolio Construction

arXiv:2605.13407v1 Announce Type: new Abstract: Predicting cross-sectional stock returns is challenging due to low signal-to-noise ratios and evolving market regimes. Classical factor models offer int

VIP-COP: Context Optimization for Tabular Foundation Models

arXiv:2605.12904v1 Announce Type: new Abstract: Tabular foundation models (TFMs) have emerged as a powerful paradigm for in-context learning on structured data, enabling direct prediction on new tabul

VoxCor: Training-Free Volumetric Features for Multimodal Voxel Correspondence

arXiv:2605.13798v1 Announce Type: new Abstract: Cross-modal 3D medical image analysis requires voxelwise representations that remain anatomically consistent across imaging contrasts, scanners, and acq

WARDEN: Endangered Indigenous Language Transcription and Translation with 6 Hours of Training Data

arXiv:2605.13846v1 Announce Type: cross Abstract: This paper introduces WARDEN, an early language model system capable of transcribing and translating Wardaman, an endangered Australian indigenous lan

Weakly Supervised Segmentation as Semantic-Based Regularization

arXiv:2605.13674v1 Announce Type: cross Abstract: Weakly supervised semantic segmentation (WSSS) trains dense pixel-level segmentation models from partial or coarse annotations such as bounding boxes,

Weakly-Supervised Spatiotemporal Anomaly Detection

arXiv:2605.13746v1 Announce Type: cross Abstract: In this paper, we explore a weakly supervised method for anomaly detection. Since annotating videos is time-consuming, we only look at weak video-leve

What Happens Before Decoding? Prefill Determines GUI Grounding in VLMs

arXiv:2605.12549v1 Announce Type: new Abstract: Existing training-free approaches for GUI grounding often rely on multiple inference runs, such as iterative cropping or candidate aggregation, to ident

What Information Matters? Graph Out-of-Distribution Detection via Tri-Component Information Decomposition

arXiv:2605.13032v1 Announce Type: new Abstract: Graph neural networks are widely used for node classification, but they remain vulnerable to out-of-distribution (OOD) shifts in node features and graph

What is Learnable in Valiant's Theory of the Learnable?

arXiv:2605.13840v1 Announce Type: cross Abstract: Valiant's 1984 paper is widely credited with introducing the PAC learning model, but it, in fact, introduced a different model: unlike PAC learning, t

When and Why is Optimistic Multiplicative Weights Slow? The Geometry of Energy Dissipation

arXiv:2605.13242v1 Announce Type: cross Abstract: This paper studies the convergence of the Optimistic Multiplicative Weights Update algorithm (OMWU) in two player zero-sum games. Recent works have id

When Diffusion Breaks Constraints: Sequential Autoregressive Generation with RL and MCTS

arXiv:2512.01242v3 Announce Type: replace-cross Abstract: Data-driven generative models excel in language and vision, but diffusion models often fail in constrained planning and design tasks, exhibiti

When to Think Fast and Slow? AMOR: Adaptive Entropy Gate for Hybrid Models

arXiv:2602.13215v2 Announce Type: replace Abstract: Recurrent-attention hybrids aim to combine the efficiency of recurrence with the expressivity of attention, but existing approaches typically apply

Why the Unfinished Keeps Returning: Canxianization and the Dynamics of Conscious Priority

arXiv:2605.12543v1 Announce Type: cross Abstract: Some conscious contents disappear after access; others return repeatedly, long after their triggering conditions have ceased. We propose Canxianizatio

WildPose: A Unified Framework for Robust Pose Estimation in the Wild

arXiv:2605.12774v1 Announce Type: new Abstract: Estimating camera pose in dynamic environments is a critical challenge, as most visual SLAM and SfM methods assume static scenes. While recent dynamic-a

WriteSAE: Sparse Autoencoders for Recurrent State

arXiv:2605.12770v1 Announce Type: cross Abstract: We introduce WriteSAE, the first sparse autoencoder that decomposes and edits the matrix cache write of state-space and hybrid recurrent language mode

X-Restormer++: 1st Place Solution for the UG2+ CVPR 2026 All-Weather Restoration Challenge

arXiv:2605.13258v1 Announce Type: cross Abstract: In this work, we present our winning solution for the 8th UG2+ Challenge (CVPR 2026) Track 1: Image Restoration under All-weather Conditions. Our meth

Z-Order Transformer for Feed-Forward Gaussian Splatting

arXiv:2605.13465v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have enabled significant progress in photorealistic novel view synthesis. However, traditional 3DGS reli

ZeD-MAP: Bundle Adjustment Guided Zero-Shot Depth Maps for Real-Time Aerial Imaging

arXiv:2604.04667v2 Announce Type: replace Abstract: Real-time depth reconstruction from ultra-high-resolution UAV imagery is essential for time-critical geospatial tasks such as disaster response, yet

20/20 Vision Language Models: A Prescription for Better VLMs through Data Curation Alone

arXiv:2605.11405v1 Announce Type: new Abstract: Data curation has shifted the quality-compute frontier for language-model and contrastive image-text pretraining, but its role for vision-language model

4DVGGT-D: 4D Visual Geometry Transformer with Improved Dynamic Depth Estimation

arXiv:2605.12027v1 Announce Type: new Abstract: Reconstructing dynamic 4D scenes from monocular videos is a fundamental yet challenging task. While recent 3D foundation models provide strong geometric

A categorical error sensitivity index (ISEC): A preventive ordinal decision-support measure for irrecoverable errors in manual data entry systems

arXiv:2605.12328v1 Announce Type: new Abstract: Data entry systems remain structurally vulnerable to categorical misclassifications, particularly in small and medium sized enterprises (SMEs). When nom

A Causal Language Modeling Detour Improves Encoder Continued Pretraining

arXiv:2605.12438v1 Announce Type: new Abstract: When adapting an encoder to a new domain, the standard approach is to continue training with Masked Language Modeling (MLM). We show that temporarily sw

A Comparative Study of Controlled Text Generation Systems Using Level-Playing-Field Evaluation Principles

arXiv:2605.12395v1 Announce Type: new Abstract: Background: Many different approaches to controlled text generation (CTG) have been proposed over recent years, but it is difficult to get a clear pictu

A Comparative Study of Model Selection Criteria for Symbolic Regression

arXiv:2605.11233v1 Announce Type: new Abstract: Effective model selection is critical in symbolic regression (SR) to identify mathematical expressions that balance accuracy and complexity, and have lo

A Composite Activation Function for Learning Stable Binary Representations

arXiv:2605.11558v1 Announce Type: new Abstract: Activation functions play a central role in neural networks by shaping internal representations. Recently, learning binary activation representations ha

A Controlled Counterexample to Strong Proxy-Based Explanations of OOD Performance: in a Fixed Pretraining-and-Probing Setup

arXiv:2605.11554v1 Announce Type: new Abstract: Task-agnostic structure proxies are often used to interpret why one pretraining corpus transfers better than another, but such explanations require the

A Formal Comparison Between Chain of Thought and Latent Thought

arXiv:2509.25239v3 Announce Type: replace-cross Abstract: Chain of thought (CoT) elicits reasoning in large language models by explicitly generating intermediate tokens. In contrast, latent thought re

A Mimetic Detector for Adversarial Image Perturbations

arXiv:2605.11492v1 Announce Type: new Abstract: Adversarial attacks fool deep image classifiers by adding tiny, almost invisible noise patterns to a clean image. The standard ell^infty-bounded attacks

A Mixture Autoregressive Image Generative Model on Quadtree Regions for Gaussian Noise Removal via Variational Bayes and Gradient Methods

arXiv:2605.11585v1 Announce Type: new Abstract: This paper addresses the problem of image denoising for grayscale images. We propose a probabilistic image generative model that combines a quadtree reg

A proximal gradient algorithm for composite log-concave sampling

arXiv:2605.12461v1 Announce Type: cross Abstract: We propose an algorithm to sample from composite log-concave distributions over R^d, i.e., densities of the form pipropto e^{-f-g}, assuming access to

A Semi-Supervised Framework for Speech Confidence Detection using Whisper

arXiv:2605.12387v1 Announce Type: cross Abstract: Automatic detection of speaker confidence is critical for adaptive computing but remains constrained by limited labelled data and the subjectivity of

Acceleration of horizontal numerical advection for atmospheric modeling through surrogate modeling with temporal coarse-graining

arXiv:2605.10956v1 Announce Type: cross Abstract: Machine-learned surrogate modeling of advection may accelerate geoscientific models, but existing approaches have either achieved limited speedup or h

Action Hallucination in Generative Vision-Language-Action Models

arXiv:2602.06339v2 Announce Type: replace Abstract: Robot Foundation Models, such as VLAs, promise end-to-end generative robot policies with broad generalization. Yet it remains unclear whether they f

researcharxiv-cs-ro

Active inference as a unified model of collision avoidance behavior in human drivers

arXiv:2506.02215v5 Announce Type: replace Abstract: Collision avoidance -- involving a rapid threat detection and quick execution of the appropriate evasive maneuver -- is a critical aspect of driving

researcharxiv-cs-ro

Adaptive Calibration in Non-Stationary Environments

arXiv:2605.11490v1 Announce Type: new Abstract: Making calibrated online predictions is a central challenge in modern AI systems. Much of the existing literature focuses on fully adversarial environme

Adversarial Effects on Expressibility and Trainability in Distributed Variational Quantum Algorithms

arXiv:2605.03629v1 Announce Type: cross Abstract: Distributed quantum algorithms offer a promising pathway to scale variational quantum algorithms beyond the constraints of noisy intermediate-scale qu

AI chatbots are giving out people’s real phone numbers

People report that their personal contact info was surfaced by Google AI—and there’s apparently no easy way to prevent it. A Redditor recently wrote that he was “desperate for help”: for about a month

researchmit-tech-review

AlphaEarth Satellite Embeddings for Modelling Climate Sensitive Diseases Towards Global Health Resilience

arXiv:2605.10949v1 Announce Type: cross Abstract: Malaria, childhood acute respiratory infection, and child undernutrition together account for over two million deaths annually in children under five,