research

Across the Levels of Analysis: Explaining Predictive Processing in Humans Requires More Than Machine-Estimated Probabilities

arXiv:2604.09466v1 Announce Type: new Abstract: Under the lens of Marr's levels of analysis, we critique and extend two claims about language models (LMs) and language processing: first, that predicti

researcharxiv-cs-cl

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AdaCubic: An Adaptive Cubic Regularization Optimizer for Deep Learning

DGX agent

arXiv:2604.09437v1 Announce Type: new Abstract: A novel regularization technique, AdaCubic, is proposed that adapts the weight of the cubic term. The heart of AdaCubic is an auxiliary optimization pro

researcharxiv-cs-lg

13 Apr 2026

Adam-HNAG: A Convergent Reformulation of Adam with Accelerated Rate

arXiv:2604.08742v1 Announce Type: cross Abstract: Adam has achieved strong empirical success, but its theory remains incomplete even in the deterministic full-batch setting, largely because adaptive p

Adaptive Dual Residual U-Net with Attention Gate and Multiscale Spatial Attention Mechanisms (ADRUwAMS)

arXiv:2604.08893v1 Announce Type: cross Abstract: Glioma is a harmful brain tumor that requires early detection to ensure better health results. Early detection of this tumor is key for effective trea

Adding Another Dimension to Image-based Animal Detection

arXiv:2604.09210v1 Announce Type: new Abstract: Monocular imaging of animals inherently reduces 3D structures to 2D projections. Detection algorithms lead to 2D bounding boxes that lack information ab

Adjoint Matching through the Lens of the Stochastic Maximum Principle in Optimal Control

arXiv:2604.08580v1 Announce Type: cross Abstract: Reward fine-tuning of diffusion and flow models and sampling from tilted or Boltzmann distributions can both be formulated as stochastic optimal contr

Allocation for Omnidirectional Aerial Robots: Incorporating Power Dynamics

arXiv:2412.16107v4 Announce Type: replace Abstract: Tilt-rotor aerial robots are more dynamic and versatile than fixed-rotor platforms, since the thrust vector and body orientation are decoupled. Howe

researcharxiv-cs-ro

AMO-ENE: Attention-based Multi-Omics Fusion Model for Outcome Prediction in Extra Nodal Extension and HPV-associated Oropharyngeal Cancer

arXiv:2604.09280v1 Announce Type: cross Abstract: Extranodal extension (ENE) is an emerging prognostic factor in human papillomavirus (HPV)-associated oropharyngeal cancer (OPC), although it is curren

An Algorithm for Fast Assembling Large-Scale Defect-Free Atom Arrays

arXiv:2604.08669v1 Announce Type: cross Abstract: It is widely believed that tens of thousands of physical qubits are needed to build a practically useful quantum computer. Atom arrays formed by optic

ANTIC: Adaptive Neural Temporal In-situ Compressor

arXiv:2604.09543v1 Announce Type: new Abstract: The persistent storage requirements for high-resolution, spatiotemporally evolving fields governed by large-scale and high-dimensional partial different

Arbitration Failure, Not Perceptual Blindness: How Vision-Language Models Resolve Visual-Linguistic Conflicts

arXiv:2604.09364v1 Announce Type: cross Abstract: When a Vision-Language Model (VLM) sees a blue banana and answers 'yellow', is the problem of perception or arbitration? We explore the question in te

researcharxiv-cs-cl

As a Catholic, I find it abhorrent that the President of the United States would publicly attack the Successor of St. Peter. Donald Trump is…

As a Catholic, I find it abhorrent that the President of the United States would publicly attack the Successor of St. Peter. Donald Trump is flailing. His war in Iran has led to the death and injury o

researchyann-lecun--x

Attention-Based Sampler for Diffusion Language Models

arXiv:2604.08564v1 Announce Type: new Abstract: Auto-regressive models (ARMs) have established a dominant paradigm in language modeling. However, their strictly sequential decoding paradigm imposes fu

researcharxiv-cs-cl

B-MoE: A Body-Part-Aware Mixture-of-Experts 'All Parts Matter' Approach to Micro-Action Recognition

arXiv:2603.24245v3 Announce Type: replace Abstract: Micro-actions, fleeting and low-amplitude motions, such as glances, nods, or minor posture shifts, carry rich social meaning but remain difficult fo

Batch Distillation Data for Developing Machine Learning Anomaly Detection Methods

arXiv:2510.18075v2 Announce Type: replace Abstract: Machine learning (ML) holds great potential to advance anomaly detection (AD) in chemical processes. However, the development of ML-based methods is

BERT-as-a-Judge: A Robust Alternative to Lexical Methods for Efficient Reference-Based LLM Evaluation

arXiv:2604.09497v1 Announce Type: cross Abstract: Accurate evaluation is central to the large language model (LLM) ecosystem, guiding model selection and downstream adoption across diverse use cases.

Beyond Flicker: Detecting Kinematic Inconsistencies for Generalizable Deepfake Video Detection

arXiv:2512.04175v2 Announce Type: replace Abstract: Generalizing deepfake detection to unseen manipulations remains a key challenge. A recent approach to tackle this issue is to train a network with p

Beyond Isolated Clients: Integrating Graph-Based Embeddings into Event Sequence Models

arXiv:2604.09085v1 Announce Type: cross Abstract: Large-scale digital platforms generate billions of timestamped user-item interactions (events) that are crucial for predicting user attributes in, e.g

Beyond Spherical geometry: Unraveling complex features of objects orbiting around stars from its transit light curve using deep learning

arXiv:2509.14875v2 Announce Type: replace-cross Abstract: Characterizing the geometry of an object orbiting around a star from its transit light curve is a powerful tool to uncover various complex phe

BlendFusion -- Scalable Synthetic Data Generation for Diffusion Model Training

arXiv:2604.09022v1 Announce Type: new Abstract: With the rapid adoption of diffusion models, synthetic data generation has emerged as a promising approach for addressing the growing demand for large-s

Bringing Clustering to MLL: Weakly-Supervised Clustering for Partial Multi-Label Learning

arXiv:2604.09359v1 Announce Type: new Abstract: Label noise in multi-label learning (MLL) poses significant challenges for model training, particularly in partial multi-label learning (PML) where cand

Built an AI tool that cleans datasets, fills missing values, and predicts unknown fields [P]

researchr-machinelearning

A developer shared a project on r/MachineLearning showcasing an AI-powered tool designed to automate common data preprocessing tasks, including dataset cleaning, intelligent imputation of missing valu

Can We Still Hear the Accent? Investigating the Resilience of Native Language Signals in the LLM Era

arXiv:2604.08568v1 Announce Type: cross Abstract: The evolution of writing assistance tools from machine translation to large language models (LLMs) has changed how researchers write. This study inves

CaRLi-V: Camera-RADAR-LiDAR Point-Wise 3D Velocity Estimation

arXiv:2511.01383v2 Announce Type: replace Abstract: Accurate point-wise velocity estimation in 3D is crucial for robot interaction with non-rigid dynamic agents, enabling robust performance in path pl

researcharxiv-cs-ro

CERBERUS: A Three-Headed Decoder for Vertical Cloud Profiles

arXiv:2604.08772v1 Announce Type: cross Abstract: Atmospheric clouds exhibit complex three-dimensional structure and microphysical details that are poorly constrained by the predominantly two-dimensio

Characterizing Lidar Range-Measurement Ambiguity due to Multiple Returns

arXiv:2604.09282v1 Announce Type: cross Abstract: Reliable position and attitude sensing is critical for highly automated vehicles that operate on conventional roadways. Lidar sensors are increasingly

Chronological Contrastive Learning: Few-Shot Progression Assessment in Irreversible Diseases

arXiv:2603.21935v2 Announce Type: replace-cross Abstract: Quantitative disease severity scoring in medical imaging is costly, time-consuming, and subject to inter-reader variability. At the same time,

CLIP-Inspector: Model-Level Backdoor Detection for Prompt-Tuned CLIP via OOD Trigger Inversion

arXiv:2604.09101v1 Announce Type: cross Abstract: Organisations with limited data and computational resources increasingly outsource model training to Machine Learning as a Service (MLaaS) providers,

Continuous Orthogonal Mode Decomposition: Haptic Signal Prediction in Tactile Internet

arXiv:2604.09446v1 Announce Type: cross Abstract: The Tactile Internet demands sub-millisecond latency and ultra-high reliability, as high latency or packet loss could lead to haptic control instabili

Cross-Modal Knowledge Distillation from Spatial Transcriptomics to Histology

arXiv:2604.09076v1 Announce Type: new Abstract: Spatial transcriptomics provides a molecularly rich description of tissue organization, enabling unsupervised discovery of tissue niches -- spatially co

Customized Fusion: A Closed-Loop Dynamic Network for Adaptive Multi-Task-Aware Infrared-Visible Image Fusion

arXiv:2604.08924v1 Announce Type: new Abstract: Infrared-visible image fusion aims to integrate complementary information for robust visual understanding, but existing fusion methods struggle with sim

DDSP-QbE++: Improving Speech Quality for Speech Anonymisation for Atypical Speech

arXiv:2604.09246v1 Announce Type: cross Abstract: Differentiable Digital Signal Processing (DDSP) pipelines for voice conversion rely on subtractive synthesis, where a periodic excitation signal is sh

Deep Learning-Based Tracking and Lineage Reconstruction of Ligament Breakup

arXiv:2604.08711v1 Announce Type: cross Abstract: The disintegration of liquid sheets into ligaments and droplets involves highly transient, multi-scale dynamics that are difficult to quantify from hi

Deep Light Pollution Removal in Night Cityscape Photographs

arXiv:2604.09145v1 Announce Type: new Abstract: Nighttime photography is severely degraded by light pollution induced by pervasive artificial lighting in urban environments. After long-range scatterin

DeepGuard: Secure Code Generation via Multi-Layer Semantic Aggregation

arXiv:2604.09089v1 Announce Type: cross Abstract: Large Language Models (LLMs) for code generation can replicate insecure patterns from their training data. To mitigate this, a common strategy for sec

Demystifying the Silence of Correctness Bugs in PyTorch Compiler

arXiv:2604.08720v1 Announce Type: cross Abstract: Performance optimization of AI infrastructure is key to the fast adoption of large language models (LLMs). The PyTorch compiler (torch.compile), a cor

Descriptor: Parasitoid Wasps and Associated Hymenoptera Dataset (DAPWH)

arXiv:2602.20028v2 Announce Type: replace-cross Abstract: Accurate taxonomic identification is the cornerstone of biodiversity monitoring and agricultural management, particularly for the hyper-divers

Detecting Diffusion-generated Images via Dynamic Assembly ForestsDetecting Diffusion-generated Images via Dynamic Assembly Forests

arXiv:2604.09106v1 Announce Type: new Abstract: Diffusion models are known for generating high-quality images, causing serious security concerns. To combat this, most efforts rely on deep neural netwo

Detection of Hate and Threat in Digital Forensics: A Case-Driven Multimodal Approach

arXiv:2604.08609v1 Announce Type: cross Abstract: Digital forensic investigations increasingly rely on heterogeneous evidence such as images, scanned documents, and contextual reports. These artifacts

Differentially Private and Federated Structure Learning in Bayesian Networks

arXiv:2512.01708v2 Announce Type: replace-cross Abstract: Learning the structure of a Bayesian network from decentralized data poses two major challenges: (i) ensuring rigorous privacy guarantees for

DiffHLS: Differential Learning for High-Level Synthesis QoR Prediction with GNNs and LLM Code Embeddings

arXiv:2604.09240v1 Announce Type: new Abstract: High-Level Synthesis (HLS) compiles C/C++ into RTL, but exploring pragma-driven optimization choices remains expensive because each design point require

Discrete Meanflow Training Curriculum

arXiv:2604.08837v1 Announce Type: new Abstract: Flow-based image generative models exhibit stable training and produce high quality samples when using multi-step sampling procedures. One-step generati

Distilling Genomic Models for Efficient mRNA Representation Learning via Embedding Matching

arXiv:2604.08574v1 Announce Type: cross Abstract: Large Genomic Foundation Models have recently achieved remarkable results and in-vivo translation capabilities. However these models quickly grow to o

Distributed Online Convex Optimization with Compressed Communication: Optimal Regret and Applications

arXiv:2604.09276v1 Announce Type: new Abstract: Distributed online convex optimization (D-OCO) is a powerful paradigm for modeling distributed scenarios with streaming data. However, the communication

Distribution-free two-sample testing with blurred total variation distance

arXiv:2602.05862v2 Announce Type: replace-cross Abstract: Two-sample testing, where we aim to determine whether two distributions are equal or not equal based on samples from each one, is challenging

Distributionally Robust Token Optimization in RLHF

arXiv:2604.08577v1 Announce Type: cross Abstract: Large Language Models (LLMs) tend to respond correctly to prompts that align to the data they were trained and fine-tuned on. Yet, small shifts in wor

dnaHNet: A Scalable and Hierarchical Foundation Model for Genomic Sequence Learning

arXiv:2602.10603v3 Announce Type: replace Abstract: Genomic foundation models have the potential to decode DNA syntax, yet face a fundamental tradeoff in their input representation. Standard fixed-voc

Do Vision Language Models Need to Process Image Tokens?

arXiv:2604.09425v1 Announce Type: new Abstract: Vision Language Models (VLMs) have achieved remarkable success by integrating visual encoders with large language models (LLMs). While VLMs process dens