Search: “research”

PlantBGC: Transformer for Plant BGC Discovery via Label-Free Domain Adaptation and Weak Supervision

arXiv:2607.27258v1 Announce Type: cross Abstract: Plant biosynthetic gene clusters (BGCs) encode specialized-metabolite pathways, yet curated plant BGC labels remain scarce, hindering supervised disco

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Research

Position, Not Provenance: Separating Reasoning Mediation from Sycophancy in Medical Vision-Language Models

DGX agent

arXiv:2607.27304v1 Announce Type: cross Abstract: Medical vision-language models (VLMs) generate chain-of-thought (CoT) reasoning before answering clinical questions, but whether this reasoning causal

researcharxiv-cs-cv

31 Jul 2026

Predict before you train: Scaling Laws for particle physics foundation models

arXiv:2607.23377v1 Announce Type: cross Abstract: The largest machine learning models in particle physics are also the most expensive to train, yet the return on scaling a given architecture cannot be

researcharxiv-cs-ai

PrintAnything: Learning an Intermediate Representation for 3D printing G-code Generation

arXiv:2607.27729v1 Announce Type: new Abstract: Point clouds are one of the most fundamental and widely used 3D representations, serving as the most basic geometric representation of 3D shapes. Nevert

ProgFormer: Hierarchical Voxel Diffusion Transformer for Longitudinal Brain MRI Prediction

arXiv:2607.27537v1 Announce Type: new Abstract: Predicting future structural MRI of a brain is challenging because longitudinal changes are often subtle and confined to specific anatomical regions, wh

Property-driven Causal Abstractions for Markov Decision Processes

arXiv:2607.26787v1 Announce Type: new Abstract: Markov Decision Processes (MDPs) are widely used as decision-making models, commonly specified over factored state spaces through state variables and th

researcharxiv-cs-ai

Prox: Training-Free FFN Activation Sparsity via Approximate Intermediate-Channel Salience in LLMs

arXiv:2607.27591v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate memory traffic and computation in large language model (LLM) inference, making them a primary target for activat

Pushing the Frontier on Approximate EFX Allocations

arXiv:2406.12413v3 Announce Type: replace-cross Abstract: We study the problem of allocating a set of indivisible goods to a set of agents with additive valuation functions, aiming to achieve approxim

researcharxiv-cs-ai

Quadratic Objective Perturbation: Curvature-Based Differential Privacy

arXiv:2605.05905v2 Announce Type: replace Abstract: Objective perturbation is a standard mechanism in differentially private empirical risk minimization. In particular, Linear Objective Perturbation (

QuantWAMs: Calibrating at the Right Granularity for World Action Models

arXiv:2607.28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient dep

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

researcharxiv-cs-ro

Random Projection Flows for Efficient Manifold Density Estimation

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

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

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