Search: “research”

Multi-modal panoramic 3D outdoor datasets for place categorization

arXiv:2604.13142v1 Announce Type: cross Abstract: We present two multi-modal panoramic 3D outdoor (MPO) datasets for semantic place categorization with six categories: forest, coast, residential area,

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Multistage Conditional Compositional Optimization

DGX agent

arXiv:2604.14075v1 Announce Type: cross Abstract: We introduce Multistage Conditional Compositional Optimization (MCCO) as a new paradigm for decision-making under uncertainty that combines aspects of

researcharxiv-cs-lg

16 Apr 2026

Native Hybrid Attention for Efficient Sequence Modeling

arXiv:2510.07019v3 Announce Type: replace Abstract: Transformers excel at sequence modeling but face quadratic complexity, while linear attention offers improved efficiency but often compromises recal

Neural 3D Reconstruction of Planetary Surfaces from Descent-Phase Wide-Angle Imagery

arXiv:2604.13235v1 Announce Type: new Abstract: Digital elevation modeling of planetary surfaces is essential for studying past and ongoing geological processes. Wide-angle imagery acquired during spa

Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models

arXiv:2601.11340v2 Announce Type: replace Abstract: Chain-of-Thought reasoning has significantly enhanced the problem-solving capabilities of Large Language Models. Unfortunately, current models gener

Neuromorphic Spiking Ring Attractor for Proprioceptive Joint-State Estimation

arXiv:2604.14021v1 Announce Type: new Abstract: Maintaining stable internal representations of continuous variables is fundamental for effective robotic control. Continuous attractor networks provide

researcharxiv-cs-ro

node2vec or triangle-biased random walks: stationarity, regularity & recurrence

arXiv:2604.13681v1 Announce Type: cross Abstract: The node2vec random walk is a non-Markovian random walk on the vertex set of a graph, widely used for network embedding and exploration. This random w

OmniTrace: A Unified Framework for Generation-Time Attribution in Omni-Modal LLMs

arXiv:2604.13073v1 Announce Type: new Abstract: Modern multimodal large language models (MLLMs) generate fluent responses from interleaved text, image, audio, and video inputs. However, identifying wh

On an L^2 norm for stationary ARMA processes

arXiv:2408.10610v5 Announce Type: replace Abstract: We propose an L^2 norm for stationary Autoregressive Moving Average (ARMA) models. We look at ARMA models within the Hilbert space of the past with

OneHOI: Unifying Human-Object Interaction Generation and Editing

arXiv:2604.14062v1 Announce Type: new Abstract: Human-Object Interaction (HOI) modelling captures how humans act upon and relate to objects, typically expressed as triplets. Existing approaches split

Outperforming Self-Attention Mechanisms in Solar Irradiance Forecasting via Physics-Guided Neural Networks

arXiv:2604.13455v1 Announce Type: new Abstract: Accurate Global Horizontal Irradiance (GHI) forecasting is critical for grid stability, particularly in arid regions characterized by rapid aerosol fluc

PAT-VCM: Plug-and-Play Auxiliary Tokens for Video Coding for Machines

arXiv:2604.13294v1 Announce Type: new Abstract: Existing video coding for machines is often trained for a specific downstream task and model. As a result, the compressed representation becomes tightly

Physically-Guided Optical Inversion Enable Non-Contact Side-Channel Attack on Isolated Screens

arXiv:2604.13419v1 Announce Type: new Abstract: Noncontact exfiltration of electronic screen content poses a security challenge, with side-channel incursions as the principal vector. We introduce an o

Physics-Informed Neural Networks for Methane Sorption: Cross-Gas Transfer Learning, Ensemble Collapse Under Physics Constraints, and Monte Carlo Dropout Uncertainty Quantification

arXiv:2604.13992v1 Announce Type: new Abstract: Accurate methane sorption prediction across heterogeneous coal ranks requires models that combine thermodynamic consistency, efficient knowledge transfe

Physics-Informed Neural Networks for Solving Derivative-Constrained PDEs

arXiv:2604.13723v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) recast PDE solving as an optimisation problem in function space by minimising a residual-based objective, yet m

Physics-informed reservoir characterization from bulk and extreme pressure events with a differentiable simulator

arXiv:2604.13291v1 Announce Type: new Abstract: Accurate characterization of subsurface heterogeneity is challenging but essential for applications such as reservoir pressure management, geothermal en

PRiMeFlow: Capturing Complex Expression Heterogeneity in Perturbation Response Modelling

arXiv:2604.13986v1 Announce Type: new Abstract: Predicting the effects of perturbations in-silico on cell state can identify drivers of cell behavior at scale and accelerate drug discovery. However, m

Provably Efficient Offline-to-Online Value Adaptation with General Function Approximation

arXiv:2604.13966v1 Announce Type: new Abstract: We study value adaptation in offline-to-online reinforcement learning under general function approximation. Starting from an imperfect offline pretraine

Quantifying and Understanding Uncertainty in Large Reasoning Models

arXiv:2604.13395v1 Announce Type: cross Abstract: Large Reasoning Models (LRMs) have recently demonstrated significant improvements in complex reasoning. While quantifying generation uncertainty in LR

QuantileMark: A Message-Symmetric Multi-bit Watermark for LLMs

arXiv:2604.13786v1 Announce Type: new Abstract: As large language models become standard backends for content generation, practical provenance increasingly requires multi-bit watermarking. In provider

Quantum Machine Learning for Colorectal Cancer Data: Anastomotic Leak Classification and Risk Factors

arXiv:2604.13951v1 Announce Type: new Abstract: This study evaluates colorectal risk factors and compares classical models against Quantum Neural Networks (QNNs) for anastomotic leak prediction. Analy

RadarSplat-RIO: Indoor Radar-Inertial Odometry with Gaussian Splatting-Based Radar Bundle Adjustment

arXiv:2604.13492v1 Announce Type: cross Abstract: Radar is more resilient to adverse weather and lighting conditions than visual and Lidar simultaneous localization and mapping (SLAM). However, most r

Randomized Neural Networks for Integro-Differential Equations with Application to Neutron Transport

arXiv:2604.13830v1 Announce Type: cross Abstract: Integro-differential equations arise in a wide range of applications, including transport, kinetic theory, radiative transfer, and multiphysics modeli

Reachability Constraints in Variational Quantum Circuits: Optimization within Polynomial Group Module

arXiv:2604.13735v1 Announce Type: cross Abstract: This work identifies a necessary condition for any variational quantum approach to reach the exact ground state. Briefly, the norms of the projections

Reconstruction of a 3D wireframe from a single line drawing via generative depth estimation

arXiv:2604.13549v1 Announce Type: new Abstract: The conversion of 2D freehand sketches into 3D models remains a pivotal challenge in computer vision, bridging the gap between human creativity and digi

ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks

arXiv:2603.28942v3 Announce Type: replace Abstract: The pervasive deployment of deep learning models across critical domains has concurrently intensified privacy concerns due to their inherent propens

Right Regions, Wrong Labels: Semantic Label Flips in Segmentation under Correlation Shift

arXiv:2604.13326v1 Announce Type: new Abstract: The robustness of machine learning models can be compromised by spurious correlations between non-causal features in the input data and target labels. A

RobotPan: A 360^irc Surround-View Robotic Vision System for Embodied Perception

arXiv:2604.13476v1 Announce Type: cross Abstract: Surround-view perception is increasingly important for robotic navigation and loco-manipulation, especially in human-in-the-loop settings such as tele

Robust Ultra Low-Bit Post-Training Quantization via Stable Diagonal Curvature Estimate

arXiv:2604.13806v1 Announce Type: new Abstract: Large Language Models (LLMs) are widely used across many domains, but their scale makes deployment challenging. Post-Training Quantization (PTQ) reduces

Saber: An Efficient Sampling with Adaptive Acceleration and Backtracking Enhanced Remasking for Diffusion Language Model

arXiv:2510.18165v2 Announce Type: replace-cross Abstract: Diffusion language models (DLMs) are emerging as a powerful and promising alternative to the dominant autoregressive paradigm, offering inhere

Scalable unsupervised feature selection via weight stability

arXiv:2506.06114v4 Announce Type: replace Abstract: Unsupervised feature selection is critical for improving clustering performance in high-dimensional data, where irrelevant features can obscure mean

Scale-Invariant Sampling in Multi-Arm Bandit Motion Planning for Object Extraction

arXiv:2604.14026v1 Announce Type: new Abstract: Object extraction tasks often occur in disassembly problems, where bolts, screws, or pins have to be removed from tight, narrow spaces. In such problems

researcharxiv-cs-ro

SceneGlue: Scene-Aware Transformer for Feature Matching without Scene-Level Annotation

arXiv:2604.13941v1 Announce Type: new Abstract: Local feature matching plays a critical role in understanding the correspondence between cross-view images. However, traditional methods are constrained

SEDTalker: Emotion-Aware 3D Facial Animation Using Frame-Level Speech Emotion Diarization

arXiv:2604.13335v1 Announce Type: new Abstract: We introduce SEDTalker, an emotion-aware framework for speech-driven 3D facial animation that leverages frame-level speech emotion diarization to achiev

SiLVR: A Simple Language-based Video Reasoning Framework

arXiv:2505.24869v3 Announce Type: replace Abstract: Recent advances in test-time optimization have led to remarkable reasoning capabilities in Large Language Models (LLMs), enabling them to solve high

Simulation-Based Optimisation of Batting Order and Bowling Plans in T20 Cricket

arXiv:2604.13861v1 Announce Type: new Abstract: This paper develops a unified Markov Decision Process (MDP) framework for optimising two recurring in-match decisions in T20 cricket namely batting orde

Singularity Avoidance in Inverse Kinematics: A Unified Treatment of Classical and Learning-based Methods

arXiv:2604.13405v1 Announce Type: new Abstract: Singular configurations cause loss of task-space mobility, unbounded joint velocities, and solver divergence in inverse kinematics (IK) for serial manip

researcharxiv-cs-ro

Some Theoretical Limitations of t-SNE

arXiv:2604.13295v1 Announce Type: new Abstract: t-SNE has gained popularity as a dimension reduction technique, especially for visualizing data. It is well-known that all dimension reduction technique

Sparse or Dense? A Mechanistic Estimation of Computation Density in Transformer-based LLMs

arXiv:2601.22795v2 Announce Type: replace Abstract: Transformer-based large language models (LLMs) are comprised of billions of parameters arranged in deep and wide computational graphs. Several studi

SSD-GS: Scattering and Shadow Decomposition for Relightable 3D Gaussian Splatting

arXiv:2604.13333v1 Announce Type: new Abstract: We present SSD-GS, a physically-based relighting framework built upon 3D Gaussian Splatting (3DGS) that achieves high-quality reconstruction and photore

Structure- and Stability-Preserving Learning of Port-Hamiltonian Systems

arXiv:2604.13297v1 Announce Type: cross Abstract: This paper investigates the problem of data-driven modeling of port-Hamiltonian systems while preserving their intrinsic Hamiltonian structure and sta

Swap Regret Minimization Through Response-Based Approachability

arXiv:2602.06264v2 Announce Type: replace Abstract: We consider the problem of minimizing different notions of swap regret in online optimization. These forms of regret are tightly connected to correl

The Gaussian Latent Machine: Efficient Prior and Posterior Sampling for Inverse Problems

arXiv:2505.12836v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions comm

The Signal is in the Steps: Local Scoring for Reasoning Data Selection

arXiv:2510.03988v2 Announce Type: replace Abstract: Distilling long-form reasoning from teacher models into smaller students requires selecting which candidate solutions to train on. Recent work argue

Towards Patient-Specific Deformable Registration in Laparoscopic Surgery

arXiv:2604.13186v1 Announce Type: new Abstract: Unsafe surgical care is a critical health concern, often linked to limitations in surgeon experience, skills, and situational awareness. Integrating pat

Towards Unconstrained Human-Object Interaction

arXiv:2604.14069v1 Announce Type: new Abstract: Human-Object Interaction (HOI) detection is a longstanding computer vision problem concerned with predicting the interaction between humans and objects.

Training-Free Semantic Multi-Object Tracking with Vision-Language Models

arXiv:2604.14074v1 Announce Type: new Abstract: Semantic Multi-Object Tracking (SMOT) extends multi-object tracking with semantic outputs such as video summaries, instance-level captions, and interact

Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations

arXiv:2601.07422v2 Announce Type: replace Abstract: Despite their impressive capabilities, large language models (LLMs) frequently generate hallucinations. Previous work shows that their internal stat