Search: “research”

arXiv:2409.00743v4 Announce Type: replace-cross Abstract: In recent years, much of the research on clustering algorithms has primarily focused on enhancing their accuracy and efficiency, frequently at

agentsarxiv-cs-ai

Invisible Yet Detected: PelFANet with Attention-Guided Anatomical Fusion for Pelvic Fracture Diagnosis

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arXiv:2509.13873v3 Announce Type: replace Abstract: Pelvic fractures pose significant diagnostic challenges, particularly in cases where fracture signs are subtle or invisible on standard radiographs.

researcharxiv-cs-cv

30 Jun 2026

IREU: Identity-Related Encoder-Only Unlearning for Customized Portrait Generation

arXiv:2606.29880v1 Announce Type: new Abstract: Customized Portrait Generation (CPG) technologies have been widely used to generate high-fidelity person images given an input image indicating the iden

ISAC: Training-Free Instance-to-Semantic Attention Control for Multi-Instance Generation

arXiv:2505.20935v3 Announce Type: replace Abstract: Recent open-weight text-to-image (T2I) diffusion models still struggle with multi-instance prompts, often omitting or merging instances and mixing s

Joint 3D Gravity and Magnetic Inversion via Rectified Flow and Ginzburg-Landau Guidance

arXiv:2603.06829v2 Announce Type: replace Abstract: Subsurface ore detection is of paramount importance given the rising depletion of shallow mineral resources in recent years. It is crucial to explor

JOPP-3D: Joint Open Vocabulary Semantic Segmentation on Point Clouds and Panoramas

arXiv:2603.06168v3 Announce Type: replace Abstract: Semantic segmentation across visual modalities such as 3D point clouds and panoramic images remains a challenging task, primarily due to the scarcit

JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid

arXiv:2606.16776v2 Announce Type: replace Abstract: Generalist robot policies require trustworthy evaluation and robot-usable training data, but both are difficult to scale with physical robots alone.

researcharxiv-cs-ro

Kriging and neural network models for pressure losses across perforated plates

arXiv:2606.29628v1 Announce Type: cross Abstract: In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates

Large and Deep Factor Models

arXiv:2402.06635v3 Announce Type: replace-cross Abstract: We show that a deep neural network (DNN) trained to construct a stochastic discount factor (SDF) admits an additive decomposition separating n

Latent Bridges for Multi-Table Question Answering

arXiv:2606.28916v1 Announce Type: cross Abstract: We introduce GRAB, a constructor-encoder-bridge pipeline for table question answering. Our method lifts relational data into an heterogeneous graph, e

Latent Noise Mask for Reducing Visual Redundancy in Multimodal Large Language Models

arXiv:2606.30168v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) often fail in fine-grained visual reasoning, as question-relevant visual cues are diluted by dense and redundan

LeAD-M3D: Leveraging Asymmetric Distillation for Real-Time Monocular 3D Detection

arXiv:2512.05663v3 Announce Type: replace Abstract: Real-time monocular 3D object detection remains challenging due to severe depth ambiguity, viewpoint shifts, and the high computational cost of 3D r

Learning as Observable Matrix Dynamics: Diffusive Relaxations versus Phase Transitions

arXiv:2606.29679v1 Announce Type: new Abstract: Observable Matrix Dynamics (OMD) is a diagnostic framework that probes the dynamics of high-dimensional internal representations of inputs by a neural n

Learning Deterministic Finite-State Machines from the Prefixes of a Single String is NP-Complete

arXiv:2601.12621v2 Announce Type: replace-cross Abstract: It is well known that computing a minimum deterministic finite automaton consistent with a given set of positive and negative examples is NP-h

Learning Efficient 4D Gaussian Representations from Monocular Videos with Flow Splatting

arXiv:2606.29976v1 Announce Type: new Abstract: Reconstructing dynamic 3D scenes from monocular videos is challenging due to scene complexity and temporal dynamics. With the advancement of 3D Gaussian

Learning from Acquisition: Metadata-driven Multimodal Pre-training for Cardiac MRI

arXiv:2606.28991v1 Announce Type: new Abstract: Cardiac magnetic resonance imaging (CMR) routinely records structured acquisition metadata, yet most CMR foundation models rely primarily on image-only

Learning the structure of open quantum systems

arXiv:2606.30358v1 Announce Type: cross Abstract: We design an algorithm for learning the coefficients of an n-qubit constant-local Lindbladian to arepsilon error with O(g d^2 log(n) / arepsilon^2) to

Learning to Adaptively Allocate Gaussians for Arbitrary-Scale Image Super-Resolution

arXiv:2606.29400v1 Announce Type: cross Abstract: In computer graphics, visual content is continuously warped, zoomed and resampled. This occurs when engines upscale frames, users zoom into 3D scenes,

Learning to Distributedly Estimate under Partially Known Dynamics: A Covariance-Agnostic Neural Kalman Consensus Filter

arXiv:2606.28441v1 Announce Type: cross Abstract: Online latent state estimation constitutes a fundamental challenge within the artificial intelligence field, serving as a foundational tool for divers

LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentation

arXiv:2606.30108v1 Announce Type: new Abstract: RECIST diameter measurements are widely used for tumor response assessment, but they provide only a limited 2D description of lesion extent. We present

Liquidity-Based Audit of Algorithmic Trading Strategies

arXiv:2606.29018v1 Announce Type: cross Abstract: We show that net demand for liquidity by algo strategies is identifiable from its trade and price history alone, with no knowledge of its signal or op

LLM Serving Optimization with Variable Prefill and Decode Lengths

arXiv:2508.06133v4 Announce Type: replace-cross Abstract: We study offline scheduling for large language model (LLM) serving under a fixed KV-cache memory budget, where requests have heterogeneous pro

LLMs and their Limited Theory of Mind: Evaluating Mental State Annotations in Situated Dialogue

arXiv:2509.02292v2 Announce Type: replace Abstract: What if large language models could not only infer human mindsets but also expose every blind spot in team dialogue such as discrepancies in the tea

Local-Minima-Preserving Continuous Relaxation of Ising Problems

arXiv:2606.30333v1 Announce Type: cross Abstract: The generalized Ising problem captures a broad spectrum of hard combinatorial problems, including MAX-CUT, Number Partitioning (NPP), and Maximum Inde

LogiCo: A Unified Framework for Logical and Structural Anomaly Detection

arXiv:2606.28688v1 Announce Type: new Abstract: Current anomaly detection methods primarily focus on structural anomalies, while paying insufficient attention to anomalies that violate logical constra

Lost in Aggregation: On a Fundamental Expressivity Limit of Message-Passing Graph Neural Networks

arXiv:2603.14846v3 Announce Type: replace Abstract: We define an information-complexity property for aggregation functions, capturing a vast range of practical aggregations, and prove that any Message

Machine-learnable Sets

arXiv:2606.28947v1 Announce Type: cross Abstract: In this study we present a formal definition of large discrete sets having, informally, three properties: their elements are easily recognized, easily

Majority Vote Silences Minority Values: Annotator Disagreement at the Hate/Offensive Boundary in HateXplain

arXiv:2606.28772v1 Announce Type: cross Abstract: Hate speech annotation pipelines routinely collapse annotator disagreement into majority vote labels before training. We show that this aggregation is

MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

arXiv:2606.28911v1 Announce Type: new Abstract: Machine-learned (ML) operator models can be trained to predict density functional theory (DFT) Hamiltonian/density matrices at significantly reduced com

Managing Map Cardinality in Automatic Disease Classification Mapping: Balancing Precision, Recall and Coverage

arXiv:2606.29750v1 Announce Type: new Abstract: Automatic mapping between disease classification systems, such as the International Classification of Diseases (ICD), is a challenging yet essential tas

McMg: A Learned Phase-Space Multi-channel Multigrid Preconditioner for Helmholtz Equation

arXiv:2606.30495v1 Announce Type: cross Abstract: Solving heterogeneous Helmholtz equations at high wavenumbers remains challenging because the discretized operator is indefinite, pollution degrades p

Measured-Subspace Consistency: A Plug-and-Play Operator for Diffusion Posterior Sampling in Accelerated MRI Reconstruction

arXiv:2606.28448v1 Announce Type: cross Abstract: Diffusion posterior samplers for accelerated MRI can reconstruct accurately yet still disagree on the acquired k-space across samples, placing posteri

Measuring Graph-to-Graph Semantic Similarity in Knowledge Graphs: An Empirical Evaluation of Knowledge Graph Embeddings

arXiv:2606.29180v1 Announce Type: new Abstract: A Knowledge Graph (KG) represents facts as structured triples and is widely used to organize relational knowledge across diverse domains. Just as textua

Mechanistic Personality Analysis of LLMs Steering Personality via Latent Feature Interventions

arXiv:2606.28770v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated the ability to simulate human-like OCEAN personality traits in generated text. Previous efforts have focu

MedDiffuseMix: Preserving Diagnostic Evidence with Saliency-Aware Diffusion Medical Image Data Augmentatio

arXiv:2606.28419v1 Announce Type: cross Abstract: Limited data availability, class imbalance, and domain variability remain major barriers to reliable medical image classification. Conventional augmen

MedEvoEval: Evaluating Continual Evolution of Doctor Agents through Simulated Clinical Episodes

arXiv:2606.28900v1 Announce Type: new Abstract: Doctor agents are moving beyond single-turn answer generation toward evolving clinical decision systems. Within an outpatient episode, they acquire evid

MeEvo: Metacognitive Evolution Combined with Natural Evolution for Automatic Heuristic Design

arXiv:2606.14202v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthe

MGDFIS: Multi-scale Global-detail Feature Integration Strategy for Small Object Detection

arXiv:2506.12697v3 Announce Type: replace-cross Abstract: Small-object detection in Unmanned Aerial Vehicle (UAV) imagery requires preserving weak local evidence while using broader context to separat

MirrorPPR: Exemplar-Based Portrait Photo Retouching

arXiv:2606.29308v1 Announce Type: new Abstract: While text-guided image editing has made remarkable progress, it remains limited in structural portrait retouching. Textual descriptions struggle to con

Miti360: A Comprehensive Dataset for Improved Reforestation Monitoring

arXiv:2606.29447v1 Announce Type: new Abstract: Over the past decade, interest in applying machine learning (ML) to automate forest monitoring has grown significantly. However, existing training datas

Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation

arXiv:2606.28697v1 Announce Type: cross Abstract: Pathology foundation models (PFMs) have demonstrated strong potential across clinical and scientific applications, yet their performance is often hind

ML-Powered LDAP Reconnaissance Detection using Weak Supervision

arXiv:2606.28917v1 Announce Type: new Abstract: Lightweight Directory Access Protocol (LDAP) is a protocol that allows users to query and modify Active Directory (AD) data. By default, all users have

Model Directions, Not Words: Mechanistic Topic Models Using Sparse Autoencoders

arXiv:2507.23220v2 Announce Type: replace Abstract: Traditional topic models are effective at uncovering latent themes in large text collections. However, due to their reliance on bag-of-words represe

Momentum Guidance: Plug-and-Play Guidance for Flow Models

arXiv:2602.20360v2 Announce Type: replace-cross Abstract: Flow-based generative methods offer a simple and effective framework for high-fidelity generation, yet pretrained flow models are rarely used

MTD-Map: Single-Stage Long-Term LiDAR Map Maintenance Framework via Mixture Transition Distribution

arXiv:2606.29469v1 Announce Type: new Abstract: While robust map maintenance has advanced significantly, existing studies have focused on specific tasks, especially dynamic object removal or change de

researcharxiv-cs-ro

Multi-Block Diffusion Language Models

arXiv:2606.29215v1 Announce Type: cross Abstract: Block Diffusion Language Models (BD-LMs) improve diffusion-based text generation with KV caching and flexible-length generation. A natural next step i

Multi-Contact Force Estimation for Continuum Robots via Gaussian-Parameterized Factor Graphs

arXiv:2606.29165v1 Announce Type: new Abstract: Continuum robots offer key advantages in navigating unstructured environments, but their safe operation requires accurate estimation of the external con

researcharxiv-cs-ro

Multi-Level Distributional Entropy for Explainable Network Intrusion Detection

arXiv:2606.29797v1 Announce Type: cross Abstract: Machine learning network intrusion detection systems (IDS) rely on aggregate flow statistics that discard distributional structure, while established