research

Near-Optimal Private Linear Regression via Iterative Hessian Mixing

arXiv:2601.07545v2 Announce Type: replace Abstract: We study differentially private ordinary least squares (DP-OLS) with bounded data (X,Y) via sketching-based mechanisms. While Gaussian sketching app

No Coin Left Behind: Maximizing Strategic Surplus Against No-Regret Dynamics

DGX agent

arXiv:2604.05129v2 Announce Type: replace-cross Abstract: We investigate the strategic surplus obtainable against a Follow-the-Regularized-Leader (FTRL) learner with constant step size eta in nimes m

researcharxiv-cs-lg

25 May 2026

Occlusion-Aware Physics-Semantic Keyframe Selection for Robust Video Editing

arXiv:2605.23192v1 Announce Type: new Abstract: Video editing has recently achieved remarkable progress with diffusion-based generative models, enabling diverse object-level manipulations from natural

On the Infinite Width and Depth Limits of Predictive Coding Networks

arXiv:2602.07697v2 Announce Type: replace-cross Abstract: Predictive coding (PC) is a biologically plausible alternative to standard backpropagation (BP) that minimises an energy function with respect

On the Koopman-Based Generalization Bounds for Multi-Task Deep Learning

arXiv:2512.19199v2 Announce Type: replace-cross Abstract: The paper establishes generalization bounds for multitask deep neural networks using operator-theoretic techniques. The authors propose a tigh

On the Stability of Spherical Hellinger-Kantorovich Flows and Their Implications for Differential Privacy

arXiv:2605.23879v1 Announce Type: cross Abstract: Gradient-flow sampling interprets a Gibbs distribution as the minimizer of an energy functional over probability measures and generates dynamics conve

One-Forcing: Towards Stable One-Step Autoregressive Video Generation

arXiv:2605.23458v1 Announce Type: cross Abstract: Recent advances have substantially improved real-time interactive video generation in the autoregressive regime. However, most existing few-step autor

OnePred: Next-Query Prediction via Recursive Intent Memory in Multi-Turn Conversations

arXiv:2605.23668v1 Announce Type: cross Abstract: Although large language model (LLM) conversational systems process millions of multi-turn dialogues daily, they remain fundamentally reactive: they re

Online Hand Gesture Recognition Using 3D Convolutional Neural Networks

arXiv:2605.23409v1 Announce Type: cross Abstract: In human computer interaction, real-time detection and classification of dynamic hand gestures is challenging as: 1) the system must run in a real-tim

Online monotone density estimation and log-optimal calibration

arXiv:2602.08927v3 Announce Type: replace-cross Abstract: We study the problem of online monotone density estimation, where density estimators must be constructed in a predictable manner from sequenti

Operator-Based Generalization Bound for Deep Learning: Insights on Multi-Task Learning

arXiv:2512.19184v2 Announce Type: replace-cross Abstract: This paper presents novel generalization bounds for vector-valued neural networks and deep kernel methods, focusing on multi-task learning thr

Optimal Dimension-Free Sampling for Regularized Classification

arXiv:2605.23726v1 Announce Type: new Abstract: We prove optimal sampling bounds achieving (1pmarepsilon)-relative error for a broad class of Lipschitz continuous classification loss functions under v

Orbax: Distributed Checkpointing with JAX

arXiv:2605.23066v1 Announce Type: cross Abstract: In a landscape of high-performance distributed ML systems, JAX has emerged as a framework of choice. However, JAX's modular design philosophy leaves i

Parametric Prior Mapping Framework for Non-stationary Probabilistic Time Series Forecasting

arXiv:2605.23402v1 Announce Type: cross Abstract: Effectively modeling non-stationary dynamics in probabilistic multivariate time series(MTS) forecasting requires balancing expressiveness with robustn

PathCal: State-Aware Reflection-Marker Calibration for Efficient Reasoning

arXiv:2605.23074v1 Announce Type: new Abstract: The emergence of Large Reasoning Language Models (LRMs) has paved the way for tackling complex reasoning tasks through test-time scaling by generating l

PixIE: Prompted Pixel-Space Low-Light Image Enhancement

arXiv:2605.23531v1 Announce Type: new Abstract: Low-light images exhibit severe noise, contrast loss, and semantic ambiguity, making enhancement a joint problem of denoising and detail recovery. We pr

Pooling and Semantic Shift: The Fundamental Challenges in Long Text Embedding and Retrieval

arXiv:2603.21437v2 Announce Type: replace Abstract: Transformer-based embedding models frequently exhibit geometric pathologies, such as anisotropy and length-induced representation collapse, which ca

ProGIC: Progressive and Lightweight Generative Image Compression with Residual Vector Quantization

arXiv:2603.02897v2 Announce Type: replace Abstract: Recent advances in generative image compression (GIC) have delivered remarkable improvements in perceptual quality. However, many GICs rely on large

RA-DCA: A Randomized Active-Set DCA for Directional Stationarity in Max-Structured DC Programs

arXiv:2605.23550v1 Announce Type: cross Abstract: We study nonsmooth difference-of-convex programs whose subtracted convex term is a finite maximum of smooth convex functions. In this setting, standar

RADAR: Relative Angular Divergence Across Representations

arXiv:2605.23028v1 Announce Type: cross Abstract: Machine learning methods rely on data. However, gathering suitable data can be challenging due to availability constraints, cost, or the need for doma

RAS: Reflection-Augmented Scaling with In-Context Learning for Executable Cypher Query Generation

arXiv:2605.22937v1 Announce Type: new Abstract: Inference-time scaling can reduce errors in structured query generation, but methods to allocate the compute for query code generation remains underexpl

Reading Calibrated Uncertainty from Language Model Trajectories

arXiv:2605.22864v1 Announce Type: new Abstract: The maximum softmax probability (MSP) represents a default approach when evaluating uncertainty quantification for language model generation with struct

Real-Time Earthquake Magnitude Classification from Initial P-Waves: Models, Dataset, and Comparative Analysis for South Asia

arXiv:2605.22836v1 Announce Type: cross Abstract: Rapid earthquake magnitude estimation is crucial for effective early warning systems that can save lives and reduce economic damage. In this paper, we

Rethinking Transfer Learning for Industrial Inspection: DINOv3 vs. ImageNet Pretraining Across RGB and X-ray Tasks

arXiv:2605.23472v1 Announce Type: new Abstract: Vision foundation models pretrained on web-scale data have recently shown strong transfer capabilities on many downstream tasks, but their effectiveness

Robots That Know What to Ask: Recovering Misaligned Rewards through Targeted Explanations

arXiv:2605.22986v1 Announce Type: cross Abstract: Learning reward functions from demonstrations assumes that demonstrations provide adequate supervision over all features -- or task-relevant aspects o

Robust Counterfactual Inference in Markov Decision Processes

arXiv:2502.13731v5 Announce Type: replace Abstract: This paper addresses a key limitation in existing counterfactual inference methods for Markov Decision Processes (MDPs). Current approaches assume a

Robust LLM Watermarking with Minimal Semantic Distortion for IP Protection

arXiv:2605.23175v1 Announce Type: cross Abstract: Proprietary large language models (LLMs) face risks of intellectual property (IP) violation, as adversaries can replicate an LLM by collecting input-o

Robust OT-Guided Generative Residual Domain Adaptation for Bike-Sharing Demand Prediction under Temporal Domain Shift

arXiv:2605.23115v1 Announce Type: new Abstract: Bike-sharing models trained on historical station-hour data may degrade when deployed in later years because travel patterns change over time. This pape

RT-NeRV: Rethinking Hybrid Neural Representations for Video via Residual Tokenization

arXiv:2403.12401v2 Announce Type: replace Abstract: Neural Representations for Videos(NeRV) have emerged as a promising paradigm for video compression by representing videos as compact neural networks

S^3GNN: Efficient Global Mixing and Local Message Passing for Long-Range Graph Learning

arXiv:2605.23467v1 Announce Type: new Abstract: Message-passing neural networks (MPNNs) often suffer from an information bottleneck when capturing long-range dependencies, leading to the oversquashing

Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids

arXiv:2605.23194v1 Announce Type: cross Abstract: Fast and reliable optimal power flow (OPF) approximation is essential for reliable smart-grid operation, yet many learning-based surrogates either fla

Scaling-Aware Adapter for Structure-Grounded LLM Reasoning

arXiv:2602.02780v3 Announce Type: replace Abstract: Large language models (LLMs) are enabling reasoning over 2D and 3D structures, yet existing methods remain modality-specific and typically compress

SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval

arXiv:2601.03260v2 Announce Type: replace-cross Abstract: AI agents have seen widespread adoption in information retrieval for scientific research, giving rise to tools such as Deep Research. However,

Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty

arXiv:2605.23378v1 Announce Type: cross Abstract: Ambulance response is time-critical in out-of-hospital cardiac arrest (OHCA), where dispatchers must balance timely arrivals with limited fleet capaci

Self-Improving In-Context Learning

arXiv:2605.23180v1 Announce Type: new Abstract: We propose to improve in-context learning (ICL) by optimizing the continuous embeddings of a fixed few-shot prompt at test time. The key observation is

Self-supervised Adversarial Purification for Graph Neural Networks

arXiv:2605.23239v1 Announce Type: new Abstract: Defending Graph Neural Networks (GNNs) against adversarial attacks requires balancing accuracy and robustness, a trade-off often mishandled by tradition

Signal Temporal Logic Motion Planning via Graphs of Convex Sets

arXiv:2605.23240v1 Announce Type: new Abstract: This paper investigates continuous-time motion planning under Signal Temporal Logic (STL) specifications. The goal is to generate smooth robot trajector

researcharxiv-cs-ro

SimInsert: Seamless Video Object Insertion via Regional Sparse Attention Fusion

arXiv:2605.23245v1 Announce Type: cross Abstract: Video object insertion requires ensuring spatio-temporal coherence and interactive realism, extending far beyond simple content placement. However, cu

SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection

arXiv:2605.23144v1 Announce Type: new Abstract: Existing language-image pre-training for remote sensing object detection is constrained by Monolithic Label Learning, which relies on exhaustively enume

Smart-Insertion-V: Photorealistic Video Insertion via a Closed-Loop Feedback Dual-Stream Framework

arXiv:2605.23891v1 Announce Type: new Abstract: Mask-free video object insertion has emerged as a challenging task, requiring harmonious integration of reference objects into source videos. However, e

Smoothed Elicitation Complexity for Approximate Gamma-calibration of Discrete Classification Tasks

arXiv:2605.23017v1 Announce Type: new Abstract: One prominent method of evaluating machine learning model trustworthiness is the notion of calibration. In the binary outcome setting, a probabilistic p

Solving the Aircraft Disassembly Scheduling Problem

arXiv:2605.23592v1 Announce Type: new Abstract: Dismantling aircrafts reaching their end of life is a complex endeavour that is necessary in terms of sustainability but yields small income margins for

SPACENUM: Revisiting Spatial Numerical Understanding in VLMs

arXiv:2605.23898v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly deployed in embodied environments, where they need produce numerical outputs such as action magnitudes an

Sparse Compositional Flow Matching by geometric assembly from motion primitives

arXiv:2605.23341v1 Announce Type: cross Abstract: Embodied trajectories, such as the executable motion sequences of robotic manipulators, underwater vehicles, and mobile robots, are a fundamental outp

Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating

arXiv:2605.23424v1 Announce Type: cross Abstract: In-network learning (INL) trains distributed neural modules by exchanging latent activations and backpropagated errors over a communication graph. Thi

Spatio-Temporal Forecasting of Retaining Wall Deformation: Mitigating Error Accumulation via Multi-Resolution ConvLSTM Stacking Ensemble

arXiv:2603.10453v2 Announce Type: replace Abstract: This study proposes a multi-resolution Convolutional Long Short-Term Memory (ConvLSTM) ensemble framework that leverages diverse temporal input reso

SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction

arXiv:2605.23440v1 Announce Type: cross Abstract: Joint Entity and Relation Extraction (JERE) is highly susceptible to weak generalization due to low-quality training data. Data augmentation is a comm

Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules

arXiv:2605.22859v1 Announce Type: cross Abstract: Automated sleep staging is commonly approached as a supervised machine learning problem, with deep learning methods dominating recent research. While