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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

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DGX agent

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

researcharxiv-cs-cv

13 Apr 2026

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

Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion

arXiv:2604.09018v1 Announce Type: new Abstract: Face Anti-Spoofing (FAS) algorithms, designed to secure face recognition systems against spoofing, struggle with limited dataset diversity, impairing th

Dual Mamba for Node-Specific Representation Learning: Tackling Over-Smoothing with Selective State Space Modeling

arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b

Dynamic sparsity in tree-structured feed-forward layers at scale

arXiv:2604.08565v1 Announce Type: cross Abstract: At typical context lengths, the feed-forward MLP block accounts for a large share of a transformer's compute budget, motivating sparse alternatives to

[ECCV2026] Workshop notification of reject/accept[D]

researchr-machinelearning

This Reddit thread on r/MachineLearning discusses the workshop paper accept/reject notifications for ECCV 2026, the European Conference on Computer Vision (ECCV), a biennial premier research conferenc

Efficient Unlearning through Maximizing Relearning Convergence Delay

arXiv:2604.09391v1 Announce Type: cross Abstract: Machine unlearning poses challenges in removing mislabeled, contaminated, or problematic data from a pretrained model. Current unlearning approaches a

EfficientSign: An Attention-Enhanced Lightweight Architecture for Indian Sign Language Recognition

arXiv:2604.08694v1 Announce Type: new Abstract: How do you build a sign language recognizer that works on a phone? That question drove this work. We built EfficientSign, a lightweight model which take

EGMOF: Efficient Generation of Metal-Organic Frameworks Using a Hybrid Diffusion-Transformer Architecture

arXiv:2511.03122v2 Announce Type: replace-cross Abstract: Designing materials with targeted properties remains challenging due to the vastness of chemical space and the scarcity of property-labeled da

EngageTriBoost: Predictive Modeling of User Engagement in Digital Mental Health Intervention Using Explainable Machine Learning

arXiv:2604.08589v1 Announce Type: new Abstract: Mental health challenges among young adults, are on the rise, necessitating effective solutions such as digital mental health interventions (DMHIs). Des

EquiformerV3: Scaling Efficient, Expressive, and General SE(3)-Equivariant Graph Attention Transformers

arXiv:2604.09130v1 Announce Type: cross Abstract: As SE(3)-equivariant graph neural networks mature as a core tool for 3D atomistic modeling, improving their efficiency, expressivity, and physical con

EVOKE: Emotion Vocabulary Of Korean and English

arXiv:2602.10414v2 Announce Type: replace Abstract: This paper introduces EVOKE (Emotion Vocabulary of Korean and English), a Korean-English parallel dataset of emotion words. The dataset offers compr

researcharxiv-cs-cl

Exploiting Web Search Tools of AI Agents for Data Exfiltration

arXiv:2510.09093v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are now routinely used to autonomously execute complex tasks, from natural language processing to dynamic workflo

researcharxiv-cs-cl

Explorable Theorems: Making Written Theorems Explorable by Grounding Them in Formal Representations

arXiv:2604.02598v2 Announce Type: replace-cross Abstract: LLM-generated explanations can make technical content more accessible, but there is a ceiling on what they can support interactively. Because