Search: “research”

A Universal Avoidance Method for Diverse Multi-branch Generation

arXiv:2604.17323v1 Announce Type: new Abstract: Modern generative models still lack human-level creativity, particularly in multi-branch diversity. Prior approaches to address this problem often incur

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Advancing Vision Transformer with Enhanced Spatial Priors

DGX agent

arXiv:2604.18549v1 Announce Type: new Abstract: In recent years, the Vision Transformer (ViT) has garnered significant attention within the computer vision community. However, the core component of Vi

researcharxiv-cs-cv

21 Apr 2026

AI Approach for MRI-only Full-Spine Vertebral Segmentation and 3D Reconstruction in Paediatric Scoliosis

arXiv:2604.17846v1 Announce Type: new Abstract: MRI is preferred over CT in paediatric imaging because it avoids ionising radiation, but its use in spine deformity assessment is largely limited by the

Amortized Inverse Kinematics via Graph Attention for Real-Time Human Avatar Animation

arXiv:2604.16629v1 Announce Type: new Abstract: Inverse kinematics (IK) is a core operation in animation, robotics, and biomechanics: given Cartesian constraints, recover joint rotations under a known

An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal

arXiv:2604.18293v1 Announce Type: new Abstract: Surprisal theory hypothesizes that the difficulty of human sentence processing increases linearly with surprisal, the negative log-probability of a word

An Exploration of Mamba for Speech Self-Supervised Models

arXiv:2506.12606v2 Announce Type: replace Abstract: While Mamba has demonstrated strong performance in language modeling, its potential as a speech self-supervised learning (SSL) model remains underex

Annotation Entropy Predicts Per-Example Learning Dynamics in LoRA Fine-Tuning

arXiv:2604.16332v1 Announce Type: cross Abstract: We find that LoRA fine-tuning exhibits un-learning on contested examples: items with high annotator disagreement show increasing loss during training,

AnyLift: Scaling Motion Reconstruction from Internet Videos via 2D Diffusion

arXiv:2604.17818v1 Announce Type: new Abstract: Reconstructing 3D human motion and human-object interactions (HOI) from Internet videos is a fundamental step toward building large-scale datasets of hu

Applications of deep generative models to DNA reaction kinetics and to cryogenic electron microscopy

arXiv:2604.16851v1 Announce Type: cross Abstract: This dissertation explores how deep generative models can advance the analysis of challenging biological problems by integrating domain knowledge with

ArbGraph: Conflict-Aware Evidence Arbitration for Reliable Long-Form Retrieval-Augmented Generation

arXiv:2604.18362v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) remains unreliable in long-form settings, where retrieved evidence is noisy or contradictory, making it difficult f

Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering

arXiv:2604.17255v1 Announce Type: new Abstract: Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models

AstroSURE: Learning to Remove Noise from Astronomical Images Without Ground Truth Data

arXiv:2604.16793v1 Announce Type: cross Abstract: In astronomical imaging, the low photon count of exposures necessitates extensive post-processing steps, including contamination removal and denoising

Asymptotic behavior of eigenvalues of large rank perturbations of large random matrices

arXiv:2507.12182v4 Announce Type: replace-cross Abstract: The paper is concerned with deformed Wigner random matrices. These matrices are closely related to Deep Neural Networks (DNNs): weight matrice

Attention-ResUNet for Automated Fetal Head Segmentation

arXiv:2604.18148v1 Announce Type: new Abstract: Automated fetal head segmentation in ultrasound images is critical for accurate biometric measurements in prenatal care. While existing deep learning ap

Authenticated Contradictions from Desynchronized Provenance and Watermarking

arXiv:2603.02378v2 Announce Type: replace-cross Abstract: Cryptographic provenance standards such as C2PA and invisible watermarking are positioned as complementary defenses for content authentication

Automated Classification of Plasma Regions at Mars Using Machine Learning

arXiv:2604.17131v1 Announce Type: cross Abstract: The plasma environment around Mars is highly variable because it is strongly influenced by the solar wind. Accurate identification of plasma regions a

Automated Palynological Analysis System: Integrating Deep Metric Learning and U^{2}-Net Detection in Hinfty bright field microscopy

arXiv:2604.16743v1 Announce Type: new Abstract: Traditional melissopalynology is a time-consuming and subjective process, often taking 4-6 hours per sample. We present an automated, high-throughput mi

AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning

arXiv:2604.18445v1 Announce Type: new Abstract: Performance, power, and area (PPA) optimization is a fundamental task in RTL design, requiring a precise understanding of circuit functionality and the

AutoRubric: Rubric-Based Generative Rewards for Faithful Multimodal Reasoning

arXiv:2510.14738v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have rapidly advanced from perception tasks to complex multi-step reasoning, yet reinforcement learning wit

Balance-Guided Sparse Identification of Multiscale Nonlinear PDEs with Small-coefficient Terms

arXiv:2604.18414v1 Announce Type: new Abstract: Data-driven discovery of governing equations has advanced significantly in recent years; however, existing methods often struggle in multiscale systems

BARD: Bridging AutoRegressive and Diffusion Vision-Language Models Via Highly Efficient Progressive Block Merging and Stage-Wise Distillation

arXiv:2604.16514v1 Announce Type: new Abstract: Autoregressive vision-language models (VLMs) deliver strong multimodal capability, but their token-by-token decoding imposes a fundamental inference bot

Barrier-enforced multi-objective optimization for direct point and sharp interval forecasting

arXiv:2604.18492v1 Announce Type: new Abstract: This paper proposes a multi-step probabilistic forecasting framework using a single neural-network based model to generate simultaneous point and interv

Model Releases

BasketHAR: A Multimodal Dataset for Human Activity Recognition and Sport Analysis in Basketball Training Scenarios

model-releasesarxiv-cs-cv

arXiv:2604.17065v1 Announce Type: new Abstract: Human Activity Recognition (HAR) involves the automatic identification of user activities and has gained significant research interest due to its broad

Beam-Plasma Collective Oscillations in Intense Charged-Particle Beams: Dielectric Response Theory, Langmuir Wave Dispersion, and Unsupervised Detection via Prometheus

arXiv:2603.10457v3 Announce Type: replace-cross Abstract: We develop a theoretical and computational framework for beam-plasma collective oscillations in intense charged-particle beams at intermediate

Before You Interpret the Profile: Validity Scaling for LLM Metacognitive Self-Report

arXiv:2604.17707v1 Announce Type: new Abstract: Clinical personality assessment screens response validity before interpreting substantive scales. LLM evaluation does not. We apply the validity scaling

Beyond Binary Contrast: Modeling Continuous Skeleton Action Spaces with Transitional Anchors

arXiv:2604.17914v1 Announce Type: new Abstract: Self-supervised contrastive learning has emerged as a powerful paradigm for skeleton-based action recognition by enforcing consistency in the embedding

Beyond Black-Box Labels: Interpretable Criteria for Diagnosing SubjectiveNLP Tasks

arXiv:2604.17022v1 Announce Type: new Abstract: Subjective NLP datasets typically aggregate annotator judgments into a single gold label, making it difficult to diagnose whether disagreement reflects

Beyond Fine-Tuning: In-Context Learning and Chain-of-Thought for Reasoned Distractor Generation

arXiv:2604.17574v1 Announce Type: new Abstract: Distractor generation (DG) remains a labor-intensive task that still significantly depends on domain experts. The task focuses on generating plausible y

Beyond Static Benchmarks: Synthesizing Harmful Content via Persona-based Simulation for Robust Evaluation

arXiv:2604.17020v1 Announce Type: new Abstract: Static benchmarks for harmful content detection face limitations in scalability and diversity, and may also be affected by contamination from web-scale

Beyond the Failures: Rethinking Foundation Models in Pathology

arXiv:2510.23807v5 Announce Type: replace-cross Abstract: Despite their successes in vision and language, foundation models have stumbled in pathology, revealing low accuracy, instability, and heavy c

Beyond URLs: Metadata Diversity and Position for Efficient LLM Pretraining

arXiv:2511.21613v2 Announce Type: replace Abstract: Incorporating metadata in Large Language Models (LLMs) pretraining has recently emerged as a promising approach to accelerate training. However prio

Beyond Verifiable Rewards: Rubric-Based GRM for Reinforced Fine-Tuning SWE Agents

arXiv:2604.16335v1 Announce Type: new Abstract: Despite recent progress in Large Language Model (LLM) Agents for Software Engineering (SWE) tasks, end-to-end fine-tuning typically relies on verifiable

Bilinear Input Modulation for Mamba: Koopman Bilinear Forms for Memory Retention and Multiplicative Computation

arXiv:2604.17221v1 Announce Type: cross Abstract: Selective State Space Models (SSMs), notably Mamba, employ diagonal state transitions that limit both memory retention and bilinear computational capa

BioVLM: Routing Prompts, Not Parameters, for Cross-Modality Generalization in Biomedical VLMs

arXiv:2604.17629v1 Announce Type: new Abstract: Pretrained biomedical vision-language models (VLMs) such as BioMedCLIP perform well on average but often degrade on challenging modalities where inter-c

Bounded Graph Clustering with Graph Neural Networks

arXiv:2512.05623v2 Announce Type: replace Abstract: In community detection, many methods require the user to specify the number of clusters in advance since an exhaustive search over all possible valu

Brain-CLIPLM: Decoding Compressed Semantic Representations in EEG for Language Reconstruction

arXiv:2604.16370v1 Announce Type: new Abstract: Decoding natural language from non-invasive electroencephalography (EEG) remains fundamentally limited by low signal-to-noise ratio and restricted infor

Bridging Coarse and Fine Recognition: A Hybrid Approach for Open-Ended Multi-Granularity Object Recognition in Interactive Educational Games

arXiv:2604.16785v1 Announce Type: new Abstract: Recent advances in Multimodal Large Language Models (MLLMs) have enabled open-ended object recognition, yet they struggle with fine-grained tasks. In co

Calibrating Model-Based Evaluation Metrics for Summarization

arXiv:2604.17200v1 Announce Type: new Abstract: Recent advances in summary evaluation are based on model-based metrics to assess quality dimensions, such as completeness, conciseness, and faithfulness

CamPVG: Camera-Controlled Panoramic Video Generation with Epipolar-Aware Diffusion

arXiv:2509.19979v2 Announce Type: replace Abstract: Recently, camera-controlled video generation has seen rapid development, offering more precise control over video generation. However, existing meth

Central Limit Theorems for Asynchronous Averaged Q-Learning

arXiv:2509.18964v3 Announce Type: replace Abstract: This paper establishes central limit theorems for Polyak-Ruppert averaged Q-learning under asynchronous updates. We prove a non-asymptotic central l

Centre manifold theorem for maps along manifolds of fixed points

arXiv:2604.18202v1 Announce Type: cross Abstract: We prove a centre manifold theorem for a map along a manifold-with-boundary of fixed points, and provide an application to the study of gradient desce

Chaos-Enhanced Prototypical Networks for Few-Shot Medical Image Classification

arXiv:2604.17300v1 Announce Type: cross Abstract: The scarcity of labeled clinical data in oncology makes Few-Shot Learning (FSL) a critical framework for Computer Aided Diagnostics, but we observed t

Class-specific diffusion models improve military object detection in a low-data domain

arXiv:2604.18076v1 Announce Type: new Abstract: Diffusion-based image synthesis has emerged as a promising source of synthetic training data for AI-based object detection and classification. In this w

Classification of systolic murmurs in heart sounds using multiresolution complex Gabor dictionary and vision transformer

arXiv:2604.16563v1 Announce Type: new Abstract: Systolic murmurs are extra heart sounds that occur during the contraction phase of the cardiac cycle, often indicating heart abnormalities caused by tur

Clinical Note Bloat Reduction for Efficient LLM Use

arXiv:2604.16364v1 Announce Type: cross Abstract: Health systems are rapidly deploying large language models (LLMs) that use clinical notes for clinical decision support applications. However, modern

Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion

arXiv:2604.16552v1 Announce Type: new Abstract: Recent text-to-scene generation approaches largely reduced the manual efforts required to create 3D scenes. However, their focus is either to generate a

CoAct: Co-Active LLM Preference Learning with Human-AI Synergy

arXiv:2604.17501v1 Announce Type: new Abstract: Learning from preference-based feedback has become an effective approach for aligning LLMs across diverse tasks. However, high-quality human-annotated p

Coevolving Representations in Joint Image-Feature Diffusion

arXiv:2604.17492v1 Announce Type: new Abstract: Joint image-feature generative modeling has recently emerged as an effective strategy for improving diffusion training by coupling low-level VAE latents