Search: “research”

SMART: A Spectral Transfer Approach to Multi-Task Learning

arXiv:2604.20161v1 Announce Type: new Abstract: Multi-task learning is effective for related applications, but its performance can deteriorate when the target sample size is small. Transfer learning c

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SpaCeFormer: Fast Proposal-Free Open-Vocabulary 3D Instance Segmentation

DGX agent

arXiv:2604.20395v1 Announce Type: new Abstract: Open-vocabulary 3D instance segmentation is a core capability for robotics and AR/VR, but prior methods trade one bottleneck for another: multi-stage 2D

researcharxiv-cs-cv

23 Apr 2026

SSL-R1: Self-Supervised Visual Reinforcement Post-Training for Multimodal Large Language Models

arXiv:2604.20705v1 Announce Type: new Abstract: Reinforcement learning (RL) with verifiable rewards (RLVR) has demonstrated the great potential of enhancing the reasoning abilities in multimodal large

Stabilising Generative Models of Attitude Change

arXiv:2604.19791v1 Announce Type: new Abstract: Attitude change - the process by which individuals revise their evaluative stances - has been explained by a set of influential but competing verbal the

Strain in Sound: Soft Corrugated Tube for Local Strain Sensing with Acoustic Resonance

arXiv:2604.20017v1 Announce Type: new Abstract: We present a soft corrugated tube sensor designed to estimate strain in each half segment. When air flows through the tube, the internal corrugated cavi

researcharxiv-cs-ro

Structure-Augmented Standard Plane Detection with Temporal Aggregation in Blind-Sweep Fetal Ultrasound

arXiv:2604.20591v1 Announce Type: new Abstract: In low-resource settings, blind-sweep ultrasound provides a practical and accessible method for identifying fetal growth restriction. However, unlike fr

Structure-Aware Variational Learning of a Class of Generalized Diffusions

arXiv:2604.20188v1 Announce Type: new Abstract: Learning the underlying potential energy of stochastic gradient systems from partial and noisy observations is a fundamental problem arising in physics,

Surrogate Functionals for Machine-Learned Orbital-Free Density Functional Theory

arXiv:2604.20458v1 Announce Type: new Abstract: We introduce surrogate functionals: machine-learned energy functionals for orbital-free density functional theory (OF-DFT) which are defined not by univ

TactileEval: A Step Towards Automated Fine-Grained Evaluation and Editing of Tactile Graphics

arXiv:2604.19829v1 Announce Type: new Abstract: Tactile graphics require careful expert validation before reaching blind and visually impaired (BVI) learners, yet existing datasets provide only coarse

Task-Dependent Evaluation of LLM Output Homogenization: A Taxonomy-Guided Framework

arXiv:2509.21267v3 Announce Type: replace Abstract: Large language models often generate homogeneous outputs, but whether this is problematic depends on the specific task. For objective math tasks, re

researcharxiv-cs-cl

Task-Stratified Knowledge Scaling Laws for Post-Training Quantized Large Language Models

arXiv:2508.18609v4 Announce Type: replace-cross Abstract: Post-Training Quantization (PTQ) is a critical strategy for efficient Large Language Models (LLMs) deployment. However, existing scaling laws

Text Steganography with Dynamic Codebook and Multimodal Large Language Model

arXiv:2604.20269v1 Announce Type: cross Abstract: With the popularity of the large language models (LLMs), text steganography has achieved remarkable performance. However, existing methods still have

Text to model via SysML: Automated generation of dynamical system computational models from unstructured natural language text via enhanced System Modeling Language diagrams

arXiv:2507.06803v3 Announce Type: replace-cross Abstract: This paper contributes to speeding up the design and deployment of engineering dynamical systems by proposing a strategy for exploiting domain

The effect of the number of parameters and the number of local feature patches on loss landscapes in distributed quantum neural networks

arXiv:2504.19239v2 Announce Type: replace-cross Abstract: Quantum neural networks hold promise for tackling computationally challenging tasks that are intractable for classical computers. However, the

The Expense of Seeing: Attaining Trustworthy Multimodal Reasoning Within the Monolithic Paradigm

arXiv:2604.20665v1 Announce Type: cross Abstract: The rapid proliferation of Vision-Language Models (VLMs) is widely celebrated as the dawn of unified multimodal knowledge discovery but its foundation

The Optical and Infrared Are Connected

arXiv:2503.03816v2 Announce Type: replace-cross Abstract: Galaxies are often modelled as composites of separable components with distinct spectral signatures, implying that different wavelength ranges

The Origin of Edge of Stability

arXiv:2604.20446v1 Announce Type: new Abstract: Full-batch gradient descent on neural networks drives the largest Hessian eigenvalue to the threshold 2/eta, where eta is the learning rate. This phenom

Thinking While Listening: Fast-Slow Recurrence for Long-Horizon Sequential Modeling

arXiv:2604.01577v2 Announce Type: replace-cross Abstract: We extend the recent latent recurrent modeling to sequential input streams. By interleaving fast, recurrent latent updates with self-organizat

Too Sharp, Too Sure: When Calibration Follows Curvature

arXiv:2604.20614v1 Announce Type: new Abstract: Modern neural networks can achieve high accuracy while remaining poorly calibrated, producing confidence estimates that do not match empirical correctne

Toward Cross-Lingual Quality Classifiers for Multilingual Pretraining Data Selection

arXiv:2604.20549v1 Announce Type: cross Abstract: As Large Language Models (LLMs) scale, data curation has shifted from maximizing volume to optimizing the signal-to-noise ratio by performing quality

Towards Certified Malware Detection: Provable Guarantees Against Evasion Attacks

arXiv:2604.20495v1 Announce Type: cross Abstract: Machine learning-based static malware detectors remain vulnerable to adversarial evasion techniques, such as metamorphic engine mutations. To address

Towards Explainable Federated Learning: Understanding the Impact of Differential Privacy

arXiv:2602.10100v2 Announce Type: replace Abstract: Data privacy and eXplainable Artificial Intelligence (XAI) are two important aspects for modern Machine Learning systems. To enhance data privacy, r

Tracing Relational Knowledge Recall in Large Language Models

arXiv:2604.19934v1 Announce Type: new Abstract: We study how large language models recall relational knowledge during text generation, with a focus on identifying latent representations suitable for r

researcharxiv-cs-cl

Trajectory-Aware Reliability Modeling of Democratic Systems

arXiv:2604.20127v1 Announce Type: new Abstract: Failures in complex systems often emerge through gradual degradation and the propagation of stress across interacting components rather than through iso

Transparent Screening for LLM Inference and Training Impacts

arXiv:2604.19757v1 Announce Type: cross Abstract: This paper presents a transparent screening framework for estimating inference and training impacts of current large language models under limited obs

TTKV: Temporal-Tiered KV Cache for Long-Context LLM Inference

arXiv:2604.19769v1 Announce Type: cross Abstract: Key-value (KV) caching is critical for efficient inference in large language models (LLMs), yet its memory footprint scales linearly with context leng

uLEAD-TabPFN: Uncertainty-aware Dependency-based Anomaly Detection with TabPFN

arXiv:2604.20255v1 Announce Type: cross Abstract: Anomaly detection in tabular data is challenging due to high dimensionality, complex feature dependencies, and heterogeneous noise. Many existing meth

Ultrafast Sampling-based Kinodynamic Planning via Differential Flatness

arXiv:2603.16059v2 Announce Type: replace Abstract: Motion planning under dynamics constraints, i.e, kinodynamic planning, enables safe robot operation by generating dynamically feasible trajectories

researcharxiv-cs-ro

UniCon3R: Contact-aware 3D Human-Scene Reconstruction from Monocular Video

arXiv:2604.19923v1 Announce Type: new Abstract: We introduce UniCon3R (Unified Contact-aware 3D Reconstruction), a unified feed-forward framework for online human-scene 4D reconstruction from monocula

Unlocking the Forecasting Economy: A Suite of Datasets for the Full Lifecycle of Prediction Market: [Experiments & Analysis]

arXiv:2604.20421v1 Announce Type: new Abstract: Prediction markets are markets for trading claims on future events, such as presidential elections, and their prices provide continuously updated signal

Using Learning Theories to Evolve Human-Centered XAI: Future Perspectives and Challenges

arXiv:2604.19788v1 Announce Type: new Abstract: As Artificial Intelligence (AI) systems continue to grow in size and complexity, so does the difficulty of the quest for AI transparency. In a world of

Utterance-Level Methods for Identifying Reliable ASR-Output for Child Speech

arXiv:2604.19801v1 Announce Type: cross Abstract: Automatic Speech Recognition (ASR) is increasingly used in applications involving child speech, such as language learning and literacy acquisition. Ho

veScale-FSDP: Flexible and High-Performance FSDP at Scale

arXiv:2602.22437v3 Announce Type: replace-cross Abstract: Fully Sharded Data Parallel (FSDP), also known as Zero Redundancy Optimizer (ZeRO), is widely used for large-scale model training, because of

What Makes a Bacterial Model a Good Reservoir Computer? Predicting Performance from Separability and Similarity

arXiv:2604.19850v1 Announce Type: cross Abstract: Biological systems are promising substrates for computation because they naturally process environmental information through complex internal dynamics

WISCA: A Lightweight Model Transition Method to Improve LLM Training via Weight Scaling

arXiv:2508.16676v2 Announce Type: replace-cross Abstract: Transformer architecture gradually dominates the LLM field. Recent advances in training optimization for Transformer-based large language mode

researcharxiv-cs-cl

X-IONet: Cross-Platform Inertial Odometry Network for Pedestrian and Legged Robot

arXiv:2511.08277v2 Announce Type: replace-cross Abstract: Learning-based inertial odometry has achieved remarkable progress in pedestrian navigation. However, extending these methods to quadruped robo

A Dual Perspective on Synthetic Trajectory Generators: Utility Framework and Privacy Vulnerabilities

arXiv:2604.19653v1 Announce Type: new Abstract: Human mobility data are used in numerous applications, ranging from public health to urban planning. Human mobility is inherently sensitive, as it can c

A Network-Aware Evaluation of Distributed Energy Resource Control in Smart Distribution Systems

arXiv:2604.19715v1 Announce Type: new Abstract: Distribution networks with high penetration of Distributed Energy Resources (DERs) increasingly rely on communication networks to coordinate grid-intera

A neural operator framework for data-driven discovery of stability and receptivity in physical systems

arXiv:2604.19465v1 Announce Type: cross Abstract: Understanding how complex systems respond to perturbations, such as whether they will remain stable or what their most sensitive patterns are, is a fu

A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models

arXiv:2604.18806v1 Announce Type: new Abstract: 3D-IC netlist partitioning is commonly optimized using proxy objectives, while final PPA is treated as a costly evaluation rather than an optimization s

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A Survey on MLLM-based Visually Rich Document Understanding: Methods, Challenges, and Emerging Trends

arXiv:2507.09861v2 Announce Type: replace-cross Abstract: Visually Rich Document Understanding (VRDU) has become a pivotal area of research, driven by the need to automatically interpret documents tha

agentsarxiv-cs-ai

AC-SINDy: Compositional Sparse Identification of Nonlinear Dynamics

arXiv:2604.18889v1 Announce Type: new Abstract: We present AC-SINDy, a compositional extension of the Sparse Identification of Nonlinear Dynamics (SINDy) framework that replaces explicit feature libra

Achieving Interaction Fluidity in a Wizard-of-Oz Robotic System: A Prototype for Fluid Error-Correction

arXiv:2604.19374v1 Announce Type: new Abstract: Achieving truly fluid interaction with robots with speech interfaces remains a hard problem, and the experience of current Human-Robot Interaction (HRI)

researcharxiv-cs-ro

Adapting Self-Supervised Representations as a Latent Space for Efficient Generation

arXiv:2510.14630v2 Announce Type: replace Abstract: We introduce Representation Tokenizer (RepTok), a generative modeling framework that represents an image using a single continuous latent token obta

Adaptive Slicing-Assisted Hyper Inference for Enhanced Small Object Detection in High-Resolution Imagery

arXiv:2604.19233v1 Announce Type: new Abstract: Deep learning-based object detectors have achieved remarkable success across numerous computer vision applications, yet they continue to struggle with s

Adversarial Attacks on Medical Hyperspectral Imaging Exploiting Spectral-Spatial Dependencies and Multiscale Features

arXiv:2601.07056v2 Announce Type: replace-cross Abstract: Medical hyperspectral imaging (MHSI) has shown strong potential for disease diagnosis by capturing spectral-spatial information of tissues. Wh

Adversarial Label Invariant Graph Data Augmentations for Out-of-Distribution Generalization

arXiv:2604.08404v2 Announce Type: replace Abstract: Out-of-distribution (OoD) generalization occurs when representation learning encounters a distribution shift. This occurs frequently in practice whe

Age-Dependent Heterogeneity in the Association Between Physical Activity and Mental Distress: A Causal Machine Learning Analysis of 3.2 Million U.S. Adults

arXiv:2604.19066v1 Announce Type: new Abstract: Physical activity (PA) is widely recognized as protective against mental distress, yet whether this benefit varies systematically across population subg