research

RaDiVe: Robust 4D Radar Odometry with Distance-Bounded NDT and Velocity-Discrepancy Point Uncertainty

arXiv:2607.28045v1 Announce Type: new Abstract: Recent advances in 4D radar enable robust perception in adverse weather; however, the inherent sparsity, noise, and limited positional precision of rada

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Random Projection Flows for Efficient Manifold Density Estimation

DGX agent

arXiv:2509.25228v3 Announce Type: replace Abstract: Accurate density estimation is crucial for understanding complex high-dimensional data, but it becomes challenging when the data lies on or near low

researcharxiv-cs-lg

31 Jul 2026

Reasoning Consensus: Structural Ensembling of LLM Reasoning via Weighted DAG Aggregation

arXiv:2607.27783v1 Announce Type: new Abstract: Large Language Models (LLMs) explore problems through chain-of-thought, but this exploration is buried in unstructured prose. On high-stakes tasks, user

Recall Before You Rank: Similarity-Guided Top-K Reuse for Efficient Long-Context Attention

arXiv:2607.27692v1 Announce Type: new Abstract: Top-K sparse attention reduces the cost of Softmax and value aggregation by attending to only a small subset of key--value (KV) entries. However, identi

Reflected diffusion, no-flux continuity equations and confined Lagrangian flows in bounded domains

arXiv:2607.28344v1 Announce Type: cross Abstract: Motivated by marginal distribution flows of reflected diffusions in bounded domains, we investigate when a density/flux pair solving a no-flux continu

Rethinking EEG-Based Disease Diagnosis: Decoupling Instance Representation Learning from Subject-Level Supervision

arXiv:2607.27274v1 Announce Type: new Abstract: EEG-based disease diagnosis requires one prediction per subject, yet common pipelines segment recordings into short instances, inherit the subject label

RiO-DETR: DETR for Real-time Oriented Object Detection

arXiv:2603.09411v2 Announce Type: replace Abstract: We present RiO-DETR: DETR for Real-time Oriented Object Detection, the first real-time oriented detection transformer to the best of our knowledge.

RIPPLE: Generating Multi-Channel Phase, Not Recovering It

arXiv:2607.27775v1 Announce Type: new Abstract: Generative models synthesize magnitude spectra with high fidelity, while phase is delegated to a recovery module---Griffin--Lim, a vocoder, or a latent

Robust Residual Finite Scalar Quantization for Neural Compression

arXiv:2508.15860v4 Announce Type: replace-cross Abstract: Finite Scalar Quantization (FSQ) offers simplified training but suffers from residual magnitude decay in multi-stage settings, where subsequen

Robust Wavelength Selection for Partial Least Squares Sugar Content Estimation Using Combinatorial Bayesian Optimization

arXiv:2607.27645v1 Announce Type: cross Abstract: Wavelength selection is one of the important preprocessing methods in near-infrared spectroscopy to improve prediction accuracy and interpretability o

RRM: Experience-Driven Reflective Retrieval Memory for Long-Horizon Multimodal Reasoning

arXiv:2607.28156v1 Announce Type: new Abstract: Existing multimodal long-term memory agents use external memory to overcome the limited context available for long videos. However, most methods emphasi

S-Avatar: Diffusion-Guided Gaussian Head Avatars from a Single Image

arXiv:2607.28164v1 Announce Type: new Abstract: We propose S-Avatar, a novel method for generating photorealistic 3D head avatars from a single image using a diffusion-guided 3D model generation modul

S-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring

arXiv:2607.27913v1 Announce Type: new Abstract: Foundation models offer a promising paradigm for Electroencephalography (EEG) analysis, leveraging generalizable representations from vast unlabeled dat

Same Branches, Different Trees: A Bifurcation Connectedness Metric for Coronary Artery Segmentation and FFR-CT Decision Agreement

arXiv:2607.28327v1 Announce Type: new Abstract: Fractional flow reserve derived from CT angiography (FFR-CT) simulates flow through a patient-specific vessel model, so its accuracy depends on the conn

Sample More, Reflect Less: Self-Refine and Reflexion Lose to Repeated Sampling at Equal Token Cost, from 1.5B to 7B

arXiv:2607.28576v1 Announce Type: new Abstract: Methods that make a language model plan, criticise and rewrite its own answer, reflect on mistakes, pick the best of several attempts, or debate with co

Schreier-Coset Graph Rewiring

arXiv:2607.27479v1 Announce Type: new Abstract: The information flow in the graph neural networks (GNNs) is fundamentally constrained by over-squashing, where structural bottlenecks impede long range

SciSchema.org: A Multidisciplinary Collection of Schemas for Structured Scientific Process Descriptions

arXiv:2607.27955v1 Announce Type: cross Abstract: Scientific processes are often described in heterogeneous article discourse, with details needed for comparison, reproducibility, reuse, and automatio

SDO: Structure-Aware Data Organization for Efficient LLM Post-Training

arXiv:2607.27273v1 Announce Type: new Abstract: Post-training of large language models is expensive, and existing efficiency improvements mainly focus on selecting informative samples or designing tra

SE(3)-MeanFlow: Few-Step Protein Backbone Generation on Lie Groups

arXiv:2607.27431v1 Announce Type: new Abstract: Generative modeling of protein backbones promises the de novo design of proteins with prescribed structural and functional properties. Existing diffusio

Search Strategies for Optimal Classification and Regression Trees

arXiv:2607.28170v1 Announce Type: new Abstract: Optimal decision trees (ODTs) are compact, interpretable machine learning models that globally optimize a given objective, but their scalability remains

Semantic-Aligned Structural Abstraction for Multimodal Sentiment Analysis

arXiv:2607.27790v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) aims to interpret complex human emotions by integrating natural language with non-verbal modalities. Non-verbal moda

Semi-Supervised Learning for Molecular Graphs via Ensemble Consensus

arXiv:2607.28304v1 Announce Type: new Abstract: Machine learning is transforming molecular sciences by accelerating property prediction, simulation, and the discovery of new molecules and materials. A

ShadowDancer: Teaching Video World Models Any Action by Learning Unified Dynamics Representations from a Video and Its Shadow

arXiv:2607.28362v1 Announce Type: new Abstract: We present ShadowDancer, a novel approach to any-action, frame-level control of interactive video world models. The obstacle is representational: existi

Shared Semantic Codebook Distillation for Unpaired Cross-Modal Medical Classification

arXiv:2607.27357v1 Announce Type: new Abstract: Cross-modal knowledge distillation can transfer diagnostic knowledge from a strong but costly teacher modality to a cheaper and more deployable student

Sparsity Induced Identifiability in Matrix Tri-Factorisation

arXiv:2607.27507v1 Announce Type: new Abstract: Matrix factorisation is a fundamental tool for exploiting low-dimensional structure in high-dimensional data, with applications such as data compression

SPFM-Net: Semantic-Prior-Guided Frequency-Constrained Mamba for Invisible Watermark Attack

arXiv:2607.27811v1 Announce Type: new Abstract: Existing watermark attacks typically rely on predefined signal-processing operations or locally constrained restoration networks, making it difficult to

Stage-Replay Divergence Follows the KV Cache: Fixed-Prefix Precision Controls and Bidirectional Cache Transplantation

arXiv:2607.28495v1 Announce Type: cross Abstract: Stage-replay diagnostics reconstruct intermediate token prefixes and treat fresh-prefill continuation as continuation from the decoder state that orig

Structuring Quantitative Image Analysis with Object Prominence

arXiv:2409.00216v2 Announce Type: replace Abstract: When photographers or media professionals compose an image, they make deliberate choices about what to foreground and what to background, shaping ho

TCA-SIR: Learning Target-Conditioned Abstractions for Scientific Inspiration Retrieval

arXiv:2607.28498v1 Announce Type: cross Abstract: Scientific hypothesis generation for AI for Science typically involves Scientific Inspiration Retrieval (SIR) followed by hypothesis composition. Exis

Test-Time Backdoor Detection for Object Detection Models

arXiv:2503.15293v2 Announce Type: replace Abstract: Object detection models are vulnerable to backdoor attacks, where attackers poison a small subset of training samples by embedding a predefined trig

The MADRS Pipeline: Supporting Depression Assessment in Clinical Trials

arXiv:2607.28190v1 Announce Type: new Abstract: Depression is a major mental disorder for which diagnosis relies primarily on clinical assessments. Automated methods to support its detection via the p

Theatre Chapbooks At Scale: A Statistical Comparative Analysis of Typography

arXiv:2607.27266v1 Announce Type: new Abstract: We propose a statistical methodology that quantifies the similarity of typefaces between printed historical books. This provides a tool that accelerates

Theia: Large-Scale Multimodal Captioning and Automated Validation of the Incidents1M Dataset for Data-Free Distillation

arXiv:2607.28269v1 Announce Type: new Abstract: The deployment of Vision-Language Models (VLMs) in critical domains like disaster management requires high-quality multimodal datasets, especially for t

Three-Photon Bayesian Imaging of Ortho-Positronium

arXiv:2607.27741v1 Announce Type: cross Abstract: PET provides functional images relying on two-photon coincidences from positron-electron annihilation. In human tissue, about 40% of annihilations are

TIER-MoE: Trust-Informed Expert Routing via Conditional Modality Risk for Multimodal Fusion in Biomedical Classification

arXiv:2607.27289v1 Announce Type: new Abstract: The promise of multimodal fusion lies in combining complementary sources of evidence, yet more evidence does not always yield a better prediction. Recen

TongueReenact: Geometry-Anchored Tongue Synthesis for Face Reenactment

arXiv:2607.28039v1 Announce Type: new Abstract: Modern face reenactment systems achieve impressive pose and expression transfer using geometry-driven representations. However, they largely ignore tong

TopoFormer: Topology Meets Attention for Graph Learning

arXiv:2607.28259v1 Announce Type: new Abstract: We introduce Topoformer, a lightweight and scalable framework for graph representation learning that encodes topological structure into attention-friend

Toward Multi-Modal Deep Learning for Pulmonary Disease Classification: A Texture-Based Machine Learning Pilot Study on Public Chest X-Ray Data

arXiv:2607.27286v1 Announce Type: cross Abstract: Automated classification of pulmonary disease from chest radiographs is a widely studied application of machine learning in medical imaging. This pape

Towards joint scaling laws with optimal batch size schedules

arXiv:2607.27731v1 Announce Type: new Abstract: Modern deep learning typically keeps the batch size static throughout training, thus overlooking the joint effect of learning rate and batch size on the

Towards Practical Algorithm Selection for Unsupervised Domain Adaptation in Medical Imaging

arXiv:2607.28125v1 Announce Type: new Abstract: Numerous unsupervised domain adaptation (UDA) algori-thms exist, but for clinical practice, selecting the best-suited one along with proper hyperparamet

(Towards) Scalable Reliable Automated Evaluation with Large Language Models

arXiv:2607.28282v1 Announce Type: new Abstract: Evaluating the quality and relevance of textual outputs from Large Language Models (LLMs) remains challenging and resource-intensive. Existing automated

Towards Structurally Explainable Machine-Generated Text Detection: A Graph-Perspective Framework

arXiv:2505.12507v2 Announce Type: replace Abstract: Despite the success of machine-generated text detectors, the black-box nature remains a critical limitation. Traditional explainability methods rely

TSOG: A Format For Temporally And Spatially Ordered Gaussians

arXiv:2607.28049v1 Announce Type: cross Abstract: We propose Temporally and Spatially Ordered Gaussians (TSOG), a format for efficient representation of 4D Gaussian Splatting (4DGS) content. TSOG exte

Understanding Submodular Information Measure Based Objectives for Representation Learning: A Variance and Separation Perspective

arXiv:2607.27660v1 Announce Type: cross Abstract: Submodular Information Measures (SIMs) have recently emerged as a powerful framework for representation learning and multimodal learning. In particula

VETO: Towards Protecting Images From Frontier AI Editing

arXiv:2607.27292v1 Announce Type: new Abstract: The rise of powerful, accessible image-editing models such as FLUX.2 has brought high-fidelity editing within broad reach. Their capabilities now extend

ViP-Rig: Visual-Prompted Controllable Rigging

arXiv:2607.27982v1 Announce Type: new Abstract: Rigging is inherently task-dependent because the same mesh may require different skeletons and deformation behaviors across animation tasks. In practice

VisualRouter: Query-Grounded Visual Sampling for Long Video Understanding

arXiv:2607.28463v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have achieved significant progress in video understanding, yet understanding long videos remains challenging due to

Weather Emulators at the Frontier of Heat Extremes Predictability

arXiv:2607.28220v1 Announce Type: cross Abstract: Atmospheric predictability declines rapidly beyond the next ten days, such that forecasts at longer lead times primarily convey large-scale trends rat