Search: “research”

Fourier Weak SINDy: Spectral Test Function Selection for Robust Model Identification

arXiv:2604.20141v1 Announce Type: new Abstract: We introduce Fourier Weak SINDy, a minimal noise-robust and interpretable derivative-free equation learning method that combines weak-form sparse equati

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From Competition to Synergy: Unlocking Reinforcement Learning for Subject-Driven Image Generation

DGX agent

arXiv:2510.18263v2 Announce Type: replace-cross Abstract: Subject-driven image generation models face a fundamental trade-off between identity preservation (fidelity) and prompt adherence (editability

researcharxiv-cs-cv

23 Apr 2026

From Diffusion to Flow: Efficient Motion Generation in MotionGPT3

arXiv:2603.26747v2 Announce Type: replace Abstract: Recent text-driven motion generation methods span both discrete token-based approaches and continuous-latent formulations. MotionGPT3 exemplifies th

From Image to Music Language: A Two-Stage Structure Decoding Approach for Complex Polyphonic OMR

arXiv:2604.20522v1 Announce Type: cross Abstract: We propose a new approach for the second stage of a practical two-stage Optical Music Recognition (OMR) pipeline. Given symbol and event candidates fr

From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization

arXiv:2604.19884v1 Announce Type: cross Abstract: Post-Training Quantization (PTQ) is critical for the efficient deployment of Large Language Models (LLMs). While 4-bit quantization is widely regarded

Gauge-covariant stochastic neural fields: Stability and finite-width effects

arXiv:2508.18948v2 Announce Type: replace-cross Abstract: We develop a gauge-covariant stochastic effective field theory for stability and finite-width effects in deep neural systems. The model uses c

Gauge-Equivariant Graph Neural Networks for Lattice Gauge Theories

arXiv:2604.20797v1 Announce Type: cross Abstract: Local gauge symmetry underlies fundamental interactions and strongly correlated quantum matter, yet existing machine-learning approaches lack a genera

Generalization and Membership Inference Attack a Practical Perspective

arXiv:2604.19936v1 Announce Type: cross Abstract: With the emergence of new evaluation metrics and attack methodologies for Membership Inference Attacks (MIA), it becomes essential to reevaluate previ

Generative Prior-Guided Neural Interface Reconstruction for 3D Electrical Impedance Tomography

arXiv:2505.16487v3 Announce Type: replace-cross Abstract: Reconstructing complex 3D interfaces from indirect measurements remains a grand challenge in scientific computing, particularly for ill-posed

Geometric Layer-wise Approximation Rates for Deep Networks

arXiv:2604.20219v1 Announce Type: new Abstract: Depth is widely viewed as a central contributor to the success of deep neural networks, whereas standard neural network approximation theory typically p

GeoRect4D: Geometry-Compatible Generative Rectification for Dynamic Sparse-View 3D Reconstruction

arXiv:2604.20784v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from sparse multi-view videos is highly ill-posed, often leading to geometric collapse, trajectory drift, and floating

GeoRelight: Learning Joint Geometrical Relighting and Reconstruction with Flexible Multi-Modal Diffusion Transformers

arXiv:2604.20715v1 Announce Type: new Abstract: Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and

GSCompleter: A Distillation-Free Plugin for Metric-Aware 3D Gaussian Splatting Completion in Seconds

arXiv:2604.20155v1 Announce Type: new Abstract: While 3D Gaussian Splatting (3DGS) has revolutionized real-time rendering, its performance degrades significantly under sparse-view extrapolation, manif

Hallucination Early Detection in Diffusion Models

arXiv:2604.20354v1 Announce Type: new Abstract: Text-to-Image generation has seen significant advancements in output realism with the advent of diffusion models. However, diffusion models encounter di

High-Level Multi-Robot Trajectory Planning And Spurious Behavior Detection

arXiv:2510.17261v2 Announce Type: replace-cross Abstract: The reliable execution of high-level missions in multi-robot systems with heterogeneous agents, requires robust methods for detecting spurious

How Will My Business Process Unfold? Predicting Case Suffixes With Start and End Timestamps

arXiv:2509.14536v3 Announce Type: replace Abstract: Predictive process monitoring supports operational decision-making by forecasting future states of ongoing business cases. A key task is case suffix

HumanScore: Benchmarking Human Motions in Generated Videos

arXiv:2604.20157v1 Announce Type: new Abstract: Recent advances in model architectures, compute, and data scale have driven rapid progress in video generation, producing increasingly realistic content

HumorRank: A Tournament-Based Leaderboard for Evaluating Humor Generation in Large Language Models

arXiv:2604.19786v1 Announce Type: new Abstract: Evaluating humor in large language models (LLMs) is an open challenge because existing approaches yield isolated, incomparable metrics rather than unifi

Improving clinical interpretability of linear neuroimaging models through feature whitening

arXiv:2604.20675v1 Announce Type: new Abstract: Linear models are widely used in computational neuroimaging to identify biomarkers associated with brain pathologies. However, interpreting the learned

Improving End-to-End Training of Retrieval-Augmented Generation Models via Joint Stochastic Approximation

arXiv:2508.18168v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) has become a widely recognized paradigm to combine parametric memory with non-parametric memories. An RAG model

Improving Facial Emotion Recognition through Dataset Merging and Balanced Training Strategies

arXiv:2604.20307v1 Announce Type: new Abstract: In this paper, a deep learning framework is proposed for automatic facial emotion based on deep convolutional networks. In order to increase the general

Improving Molecular Force Fields with Minimal Temporal Information

arXiv:2604.19806v1 Announce Type: cross Abstract: Accurate prediction of energy and forces for 3D molecular systems is one of fundamental challenges at the core of AI for Science applications. Many po

Inference Headroom Ratio: A Diagnostic and Control Framework for Inference Stability Under Constraint

arXiv:2604.19760v1 Announce Type: new Abstract: We present a simulation-based evaluation of the Inference Headroom Ratio (IHR), a dimensionless diagnostic quantity for characterizing inference stabili

Information Aggregation with AI Agents

arXiv:2604.20050v1 Announce Type: cross Abstract: Can Large Language Models (AI agents) aggregate dispersed private information through trading and reason about the knowledge of others by observing pr

Integrated AI Nodule Detection and Diagnosis for Lung Cancer Screening Beyond Size and Growth-Based Standards Compared with Radiologists and Leading Models

arXiv:2512.00281v2 Announce Type: replace Abstract: Early detection of malignant lung nodules remains limited by reliance on size- and growth-based screening criteria, which can delay diagnosis. We pr

Investigation of cardinality classification for bacterial colony counting using explainable artificial intelligence

arXiv:2604.20026v1 Announce Type: new Abstract: Automatic bacterial colony counting is a highly sought-after technology in modern biological laboratories because it eliminates manual counting effort.

Is Four Enough? Automated Reasoning Approaches and Dual Bounds for Condorcet Dimensions of Elections

arXiv:2604.19851v1 Announce Type: cross Abstract: In an election where n voters rank m candidates, a Condorcet winning set is a committee of k candidates such that for any outside candidate, a majorit

Issues with Value-Based Multi-objective Reinforcement Learning: Value Function Interference and Overestimation Sensitivity

arXiv:2402.06266v2 Announce Type: replace Abstract: Multi-objective reinforcement learning (MORL) algorithms extend conventional reinforcement learning (RL) to the more general case of problems with m

ItemRAG: Item-Based Retrieval-Augmented Generation for LLM-Based Recommendation

arXiv:2511.15141v2 Announce Type: replace-cross Abstract: Recently, large language models (LLMs) have been widely used as recommender systems, owing to their reasoning capability and effectiveness in

KD-Judge: A Knowledge-Driven Automated Judge Framework for Functional Fitness Movements on Edge Devices

arXiv:2604.19834v1 Announce Type: new Abstract: Functional fitness movements are widely used in training, competition, and health-oriented exercise programs, yet consistently enforcing repetition (rep

Kinematic Optimization of Phalanx Length Ratios in Robotic Hands Using Potential Dexterity

arXiv:2604.20686v1 Announce Type: new Abstract: In the design stage of robotic hands, it is not straightforward to quantitatively evaluate the effect of phalanx length ratios on dexterity without defi

researcharxiv-cs-ro

LEXIS: LatEnt ProXimal Interaction Signatures for 3D HOI from an Image

arXiv:2604.20800v1 Announce Type: new Abstract: Reconstructing 3D Human-Object Interaction from an RGB image is essential for perceptive systems. Yet, this remains challenging as it requires capturing

LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model

arXiv:2604.20796v1 Announce Type: new Abstract: We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a nativel

LLM StructCore: Schema-Guided Reasoning Condensation and Deterministic Compilation

arXiv:2604.20560v1 Announce Type: new Abstract: Automatically filling Case Report Forms (CRFs) from clinical notes is challenging due to noisy language, strict output contracts, and the high cost of f

Location-Aware Pretraining for Medical Difference Visual Question Answering

arXiv:2603.04950v2 Announce Type: replace-cross Abstract: Differential medical VQA models compare multiple images to identify clinically meaningful changes and rely on vision encoders to capture fine-

Machine learning moment closure models for the radiative transfer equation IV: enforcing symmetrizable hyperbolicity in two dimensions

arXiv:2604.20143v1 Announce Type: cross Abstract: This is our fourth work in the series on machine learning (ML) moment closure models for the radiative transfer equation (RTE). In the first three pap

Markov reads Pushkin, again: A statistical journey into the poetic world of Evgenij Onegin

arXiv:2604.20221v1 Announce Type: new Abstract: This study applies symbolic time series analysis and Markov modeling to explore the phonological structure of Evgenij Onegin-as captured through a graph

MasconCube: Fast and Accurate Gravity Modeling with an Explicit Representation

arXiv:2509.08607v3 Announce Type: replace-cross Abstract: The geodesy of irregularly shaped small bodies presents fundamental challenges for gravitational field modeling, particularly as deep space ex

Maximum Entropy Semi-Supervised Inverse Reinforcement Learning

arXiv:2604.20074v1 Announce Type: new Abstract: A popular approach to apprenticeship learning (AL) is to formulate it as an inverse reinforcement learning (IRL) problem. The MaxEnt-IRL algorithm succe

Maximum Likelihood Reconstruction for Multi-Look Digital Holography with Markov-Modeled Speckle Correlation

arXiv:2604.20154v1 Announce Type: cross Abstract: Multi-look acquisition is a widely used strategy for reducing speckle noise in coherent imaging systems such as digital holography. By acquiring multi

Measuring Creativity in the Age of Generative AI: Distinguishing Human and AI-Generated Creative Performance in Hiring and Talent Systems

arXiv:2604.19799v1 Announce Type: cross Abstract: Generative AI is rapidly transforming how organizations create value and evaluate talent. While large language models enhance baseline output quality,

Mechanistic Interpretability of Large-Scale Counting in LLMs through a System-2 Strategy

arXiv:2601.02989v2 Announce Type: replace Abstract: Large language models (LLMs), despite strong performance on complex mathematical problems, exhibit systematic limitations in counting tasks. This is

Mechanistic Interpretability Tool for AI Weather Models

arXiv:2604.20467v1 Announce Type: cross Abstract: Artificial Intelligence (AI) weather models are improving rapidly, and their forecasts are already competitive with long-established traditional Numer

MMCORE: MultiModal COnnection with Representation Aligned Latent Embeddings

arXiv:2604.19902v1 Announce Type: cross Abstract: We present MMCORE, a unified framework designed for multimodal image generation and editing. MMCORE leverages a pre-trained Vision-Language Model (VLM

Model Internal Sleuthing: Finding Lexical Identity and Inflectional Features in Modern Language Models

arXiv:2506.02132v5 Announce Type: replace Abstract: Large transformer-based language models dominate modern NLP, yet our understanding of how they encode linguistic information relies primarily on stu

MOMO: A framework for seamless physical, verbal, and graphical robot skill learning and adaptation

arXiv:2604.20468v1 Announce Type: cross Abstract: Industrial robot applications require increasingly flexible systems that non-expert users can easily adapt for varying tasks and environments. However

Multi-Perspective Evidence Synthesis and Reasoning for Unsupervised Multimodal Entity Linking

arXiv:2604.20283v1 Announce Type: new Abstract: Multimodal Entity Linking (MEL) is a fundamental task in data management that maps ambiguous mentions with diverse modalities to the multimodal entities

Multi-Timescale Model Predictive Control for Slow-Fast Systems

arXiv:2511.14311v2 Announce Type: replace-cross Abstract: Model Predictive Control (MPC) has established itself as the primary methodology for constrained control, enabling autonomy across diverse app

researcharxiv-cs-ro