Search: “research”

Learning noisy phase transition dynamics from stochastic partial differential equations

arXiv:2604.09664v1 Announce Type: cross Abstract: The non-equilibrium dynamics of mesoscale phase transitions are fundamentally shaped by thermal fluctuations, which not only seed instabilities but ac

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Learning Visually Interpretable Oscillator Networks for Soft Continuum Robots from Video

DGX agent

arXiv:2511.18322v3 Announce Type: replace-cross Abstract: Learning soft continuum robot (SCR) dynamics from video offers flexibility but existing methods lack interpretability or rely on prior assumpt

researcharxiv-cs-cv

14 Apr 2026

LETGAMES: An LLM-Powered Gamified Approach to Cognitive Training for Patients with Cognitive Impairment

arXiv:2604.09566v1 Announce Type: cross Abstract: The application of games as a therapeutic tool for cognitive training is beneficial for patients with cognitive impairments. However, effective game d

Lightweight Low-Light Image Enhancement via Distribution-Normalizing Preprocessing and Depthwise U-Net

arXiv:2604.11071v1 Announce Type: cross Abstract: We present a lightweight two-stage framework for low-light image enhancement (LLIE) that achieves competitive perceptual quality with significantly fe

Linear Attention Based Deep Nonlocal Means Filtering for Multiplicative Noise Removal

arXiv:2407.05087v2 Announce Type: replace-cross Abstract: Multiplicative noise widely exists in radar images, medical images and other important fields' images. Compared to normal noises, multiplicati

Linear Programming for Multi-Criteria Assessment with Cardinal and Ordinal Data: A Pessimistic Virtual Gap Analysis

arXiv:2604.09555v1 Announce Type: new Abstract: Multi-criteria Analysis (MCA) is used to rank alternatives based on various criteria. Key MCA methods, such as Multiple Criteria Decision Making (MCDM)

LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops

arXiv:2506.14493v3 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown great promise but require substantial computational resources during inference. Attackers can ex

LiveGesture Streamable Co-Speech Gesture Generation Model

arXiv:2604.10927v1 Announce Type: new Abstract: We propose LiveGesture, the first fully streamable, speech-driven full-body gesture generation framework that operates with zero look-ahead and supports

LLMs for Game Theory: Entropy-Guided In-Context Learning and Adaptive CoT Reasoning

arXiv:2601.10775v2 Announce Type: replace Abstract: We propose a novel LLM-based framework for reasoning in discrete, game-theoretic tasks, illustrated with Tic-Tac-Toe. The method integrates in-conte

LLMs for Qualitative Data Analysis Fail on Security-specificComments in Human Experiments

arXiv:2604.10834v1 Announce Type: cross Abstract: [Background:] Thematic analysis of free-text justifications in human experiments provides significant qualitative insights. Yet, it is costly because

LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation

arXiv:2604.11789v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) have achieved remarkable progress in general-purpose vision--language understanding, yet they remain limited in tasks req

Locket: Robust Feature-Locking Technique for Language Models

arXiv:2510.12117v3 Announce Type: replace-cross Abstract: Chatbot service providers (e.g., OpenAI) rely on tiered subscription plans to generate revenue, offering black-box access to basic models for

LogitDynamics: Reliable ViT Error Detection from Layerwise Logit Trajectories

arXiv:2604.10643v1 Announce Type: new Abstract: Reliable confidence estimation is critical when deploying vision models. We study error prediction: determining whether an image classifier's output is

LOOPE: Learnable Optimal Patch Order in Positional Embeddings for Vision Transformers

arXiv:2504.14386v2 Announce Type: replace-cross Abstract: Positional embeddings (PE) play a crucial role in Vision Transformers (ViTs) by providing spatial information otherwise lost due to the permut

Lost in Diffusion: Uncovering Hallucination Patterns and Failure Modes in Diffusion Large Language Models

arXiv:2604.10556v1 Announce Type: new Abstract: While Diffusion Large Language Models (dLLMs) have emerged as a promising non-autoregressive paradigm comparable to autoregressive (AR) models, their fa

Lung Cancer Detection Using Deep Learning

arXiv:2604.10765v1 Announce Type: cross Abstract: Lung cancer, the second leading cause of cancer-related deaths, is primarily linked to long-term tobacco smoking (85% of cases). Surprisingly, 10-15%

M^{2}SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation

arXiv:2303.10894v3 Announce Type: replace Abstract: Accurate medical image segmentation is critical for early medical diagnosis. Most existing methods are based on U-shape structure and use element-wi

Masked Contrastive Pre-Training Improves Music Audio Key Detection

arXiv:2604.10021v1 Announce Type: cross Abstract: Self-supervised music foundation models underperform on key detection, which requires pitch-sensitive representations. In this work, we present the fi

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models

arXiv:2408.11871v4 Announce Type: replace-cross Abstract: Fake news significantly influences decision-making processes by misleading individuals, organizations, and even governments. Large language mo

Membership Inference Attacks Expose Participation Privacy in ECG Foundation Encoders

arXiv:2604.10424v1 Announce Type: new Abstract: Foundation-style ECG encoders pretrained with self-supervised learning are increasingly reused across tasks, institutions, and deployment contexts, ofte

Merging Triggers, Breaking Backdoors: Defensive Poisoning for Instruction-Tuned Language Models

arXiv:2601.04448v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have greatly advanced Natural Language Processing (NLP), particularly through instruction tuning, which enables b

METRO: Towards Strategy Induction from Expert Dialogue Transcripts for Non-collaborative Dialogues

arXiv:2604.11427v1 Announce Type: cross Abstract: Developing non-collaborative dialogue agents traditionally requires the manual, unscalable codification of expert strategies. We propose ours, a metho

Mild Over-Parameterization Benefits Asymmetric Tensor PCA

arXiv:2604.10208v1 Announce Type: new Abstract: Asymmetric Tensor PCA (ATPCA) is a prototypical model for studying the trade-offs between sample complexity, computation, and memory. Existing algorithm

Mining Attribute Subspaces for Efficient Fine-tuning of 3D Foundation Models

arXiv:2604.10095v1 Announce Type: new Abstract: With the emergence of 3D foundation models, there is growing interest in fine-tuning them for downstream tasks, where LoRA is the dominant fine-tuning p

Mitigating Privacy Risk via Forget Set-Free Unlearning

arXiv:2604.10636v1 Announce Type: new Abstract: Training machine learning models requires the storage of large datasets, which often contain sensitive or private data. Storing data is associated with

MIXAR: Scaling Autoregressive Pixel-based Language Models to Multiple Languages and Scripts

arXiv:2604.11575v1 Announce Type: new Abstract: Pixel-based language models are gaining momentum as alternatives to traditional token-based approaches, promising to circumvent tokenization challenges.

Modeling, Analysis and Activation of Planar Viscoelastically-combined Rimless Wheels

arXiv:2604.11295v1 Announce Type: new Abstract: This paper proposes novel passive-dynamic walkers formed by two cross-shaped frames and eight viscoelastic elements. Since it is a combination of two fo

researcharxiv-cs-ro

MoveFM-R: Advancing Mobility Foundation Models via Language-driven Semantic Reasoning

arXiv:2509.22403v2 Announce Type: replace Abstract: Mobility Foundation Models (MFMs) have advanced the modeling of human movement patterns, yet they face a ceiling due to limitations in data scale an

MR.ScaleMaster: Scale-Consistent Collaborative Mapping from Crowd-Sourced Monocular Videos

arXiv:2604.11372v1 Announce Type: new Abstract: Crowd-sourced cooperative mapping from monocular cameras promises scalable 3D reconstruction without specialized sensors, yet remains hindered by two sc

researcharxiv-cs-ro

Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model

arXiv:2505.23606v4 Announce Type: replace-cross Abstract: Unified generation models aim to handle diverse tasks across modalities -- such as text generation, image generation, and vision-language reas

Multidata Causal Discovery for Statistical Hurricane Intensity Forecasting

arXiv:2510.02050v3 Announce Type: replace-cross Abstract: Improving statistical forecasts of tropical cyclone (TC) intensity is limited by complex nonlinear interactions and difficulty in identifying

Safety

Multimodal Dataset Normalization and Perceptual Validation for Music-Taste Correspondences

arXiv:2604.10632v1 Announce Type: cross Abstract: Collecting large, aligned cross-modal datasets for music-flavor research is difficult because perceptual experiments are costly and small by design. W

safetyarxiv-cs-lg

Multinex: Lightweight Low-light Image Enhancement via Multi-prior Retinex

arXiv:2604.10359v1 Announce Type: cross Abstract: Low-light image enhancement (LLIE) aims to restore natural visibility, color fidelity, and structural detail under severe illumination degradation. St

Nano-EmoX: Unifying Multimodal Emotional Intelligence from Perception to Empathy

arXiv:2603.02123v3 Announce Type: replace Abstract: The development of affective multimodal language models (MLMs) has long been constrained by a gap between low-level perception and high-level intera

Near OOD Detection for Vision-Language Prompt Learning with Contrastive Logit Score

arXiv:2405.16091v2 Announce Type: replace Abstract: Prompt learning has emerged as an efficient and effective method for fine-tuning vision-language models such as CLIP. While many studies have explor

Neural Processes Maintain Calibrated Biomass Estimates Across Spatiotemporal Gaps and Disturbance

arXiv:2604.03874v2 Announce Type: replace Abstract: Monitoring deforestation-driven carbon emissions requires both spatially explicit and temporally continuous estimates of aboveground biomass density

NeuroFlow: Toward Unified Visual Encoding and Decoding from Neural Activity

arXiv:2604.09817v1 Announce Type: new Abstract: Visual encoding and decoding models act as gateways to understanding the neural mechanisms underlying human visual perception. Typically, visual encodin

NeuVolEx: Implicit Neural Features for Volume Exploration

arXiv:2604.11172v1 Announce Type: cross Abstract: Direct volume rendering (DVR) aims to help users identify and examine regions of interest (ROIs) within volumetric data, and feature representations t

Not All Denoising Steps Are Equal: Model Scheduling for Faster Masked Diffusion Language Models

arXiv:2604.02340v2 Announce Type: replace-cross Abstract: Recent advances in masked diffusion language models (MDLMs) narrow the quality gap to autoregressive LMs, but their sampling remains expensive

Not All Forgetting Is Equal: Architecture-Dependent Retention Dynamics in Fine-Tuned Image Classifiers

arXiv:2604.11508v1 Announce Type: cross Abstract: Fine-tuning pretrained image classifiers is standard practice, yet which individual samples are forgotten during this process, and whether forgetting

NSFL: A Post-Training Neuro-Symbolic Fuzzy Logic Framework for Boolean Operators in Neural Embeddings

arXiv:2604.10604v1 Announce Type: cross Abstract: Standard dense retrievers lack a native calculus for multi-atom logical constraints. We introduce Neuro-Symbolic Fuzzy Logic (NSFL), a framework that

On The Application of Linear Attention in Multimodal Transformers

arXiv:2604.10064v1 Announce Type: new Abstract: Multimodal Transformers serve as the backbone for state-of-the-art vision-language models, yet their quadratic attention complexity remains a critical b

On the Complexity of the Discussion-based Semantics in Abstraction Argumentation

arXiv:2604.11480v1 Announce Type: new Abstract: We show that deciding whether an argument a is stronger than an argument b with respect to the discussion-based semantics of Amgoud and Ben-Naim is deci

On the Robustness of Watermarking for Autoregressive Image Generation

arXiv:2604.11720v1 Announce Type: cross Abstract: The proliferation of autoregressive (AR) image generators demands reliable detection and attribution of their outputs to mitigate misinformation, and

One-Step Score-Based Density Ratio Estimation

arXiv:2604.10672v1 Announce Type: cross Abstract: Density ratio estimation (DRE) is a useful tool for quantifying discrepancies between probability distributions, but existing approaches often involve

Ontological Trajectory Forecasting via Finite Semigroup Iteration and Lie Algebra Approximation in Geopolitical Knowledge Graphs

arXiv:2604.10087v1 Announce Type: new Abstract: We present EL-DRUIN, an ontological reasoning system for geopolitical intelligence analysis that combines formal ontology, finite semigroup algebra, and

Optimal Kinodynamic Motion Planning Through Anytime Bidirectional Heuristic Search with Tight Termination Condition

arXiv:2604.11587v1 Announce Type: new Abstract: This paper introduces Bidirectional Tight Informed Trees (BTIT*), an asymptotically optimal kinodynamic sampling-based motion planning algorithm that in

researcharxiv-cs-ro

Optimal L2 Regularization in High-dimensional Continual Linear Regression

arXiv:2601.13844v2 Announce Type: replace Abstract: We study generalization in an overparameterized continual linear regression setting, where a model is trained with L2 (isotropic) regularization acr