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Loss-Aware Feature-Map Pruning in Convolutional Neural Networks Using Multi-Armed Bandits

arXiv:2607.22564v1 Announce Type: new Abstract: Convolutional neural networks often contain redundant feature maps that increase storage and inference cost. This paper presents a loss-aware feature-ma

researcharxiv-cs-ai

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LoTA-N2N: Local Trace Adaptation for Zero-Shot Self-Supervised Image Denoising

DGX agent

arXiv:2607.24135v1 Announce Type: new Abstract: Single-image self-supervised denoising replaces unavailable clean targets with surrogate targets constructed from noisy observations. Its effectiveness

model-releasesarxiv-cs-cv

28 Jul 2026

Applications

Low-Latency Turn-Taking via Context-Aware Preface Generation in a Real-World Dialogue Robot

arXiv:2607.23204v1 Announce Type: cross Abstract: Large language model (LLM)-based dialogue systems suffer response delays because generation begins only after final speech recognition. While fixed fi

applicationsarxiv-cs-cl

Applications

Low-light Image Enhancement via Multi-scale Attention combined with Fourier Transform

arXiv:2607.24002v1 Announce Type: new Abstract: Low-light image enhancement (LLIE) aims to improve image quality and clarity in diverse and demanding low-illumination environments. However, existing d

applicationsarxiv-cs-cv

Low-Rank Dependence Decomposition via Accelerated Symmetric Non-negative Matrix Factorization

model-releasesarxiv-cs-lg

arXiv:2607.24518v1 Announce Type: new Abstract: Symmetric non-negative matrix factorization (SymNMF) recovers latent group structure from a dependence matrix, but its dense, quadratic-memory objective

LowAux-RDNet: Low-Pass Residual Supervision with Scene-Balanced Real-World Training for Single-Image Reflection Removal

arXiv:2607.22707v1 Announce Type: new Abstract: Single-image reflection removal aims to recover a clean transmission layer from one image captured through glass. We study an explicit decomposition pip

LU-500: A Logo Benchmark for Concept Unlearning

arXiv:2607.24101v1 Announce Type: cross Abstract: Concept unlearning is increasingly used to limit the reproduction of protected or unsafe visual concepts in text-to-image models. Existing evaluations

LuxInstruct: A Cross-Lingual Instruction Tuning Dataset For Luxembourgish

arXiv:2510.07074v2 Announce Type: replace-cross Abstract: Instruction tuning has become a key technique for enhancing the performance of large language models, enabling them to better follow human pro

Machine Learning for Cloud Detection in IASI Measurements: A Data-Driven SVM Approach with Physical Constraints

arXiv:2508.10120v2 Announce Type: replace-cross Abstract: Cloud detection is fundamental for the interpretation and operational exploitation of hyperspectral infrared sounders, yet the capability of i

Making Mathematical Knowledge Explainable, Accessible and Interoperable Through Large Language Model Integration

arXiv:2607.24512v1 Announce Type: new Abstract: Mathematical models are central to formalizing research problems, yet their documentation often falls short of FAIR principles. Knowledge bases such as

Mamba-CL: Optimizing Selective State Space Model in Null Space for Continual Learning

arXiv:2411.15469v3 Announce Type: replace Abstract: Continual Learning (CL) aims to equip AI models with the ability to learn a sequence of tasks over time, without forgetting previously learned knowl

tutorialsarxiv-cs-cv

MANGO: A Global Single-Date Paired Dataset for Mangrove Segmentation

arXiv:2601.17039v2 Announce Type: replace-cross Abstract: Mangroves are critical for climate-change mitigation, requiring reliable monitoring for effective conservation. While deep learning has emerge

Manifold-Constrained Noise Optimization for Diverse Diffusion Sampling

arXiv:2607.23937v1 Announce Type: new Abstract: Few-step distilled diffusion models generate high-quality images quickly, but often lose per-prompt diversity, producing near-identical samples across r

MAPLE: Efficient and Diverse Multi-Alpha Generation for Portfolio Construction

arXiv:2607.24131v1 Announce Type: new Abstract: Classical alpha mining achieves strong risk-adjusted returns by combining many low-correlated predictive signals, yet deep learning stock-ranking method

Local Ai

MarineEVT: Advancing Event-Centric Marine Video Understanding via Visual Tool Reasoning

arXiv:2607.24064v1 Announce Type: cross Abstract: Recent Vision-Language Models (VLMs) have achieved remarkable success in visual understanding, driven by the growing availability of high-quality imag

local-aiarxiv-cs-ai

Markerless Motion Capture in Routine Clinical Upper Limb Assessments: Validity and Insights Beyond Ordinal Scoring

arXiv:2607.23608v1 Announce Type: new Abstract: The Action Research Arm Test (ARAT) is a widely-used upper limb outcome measure in neurorehabilitation, but its ordinal scoring is subjective and suffer

Agents

MARS: Multi-hop Adaptive Retrieval and SPARQL Generation for KGQA

arXiv:2607.14561v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong reasoning performance, but their tendency to hallucinate limits their reliability in knowledge

agentsarxiv-cs-cl

Masked Autoencoders Learn Perception-Relevant Representations from Resting State Neural Data

arXiv:2607.22615v1 Announce Type: cross Abstract: Clinical neuroprosthetics face a data bottleneck: labeled perception trials are scarce while hours of spontaneous neural activity are largely underuti

tutorialsarxiv-cs-ai

Masked Distillation: Internalizing the Chain-of-Thought in Language Models

arXiv:2607.22629v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) produce long, explicit chains of intermediate steps before generating a final answer at inference time. These intermediate

researcharxiv-cs-ai

MATS: A novel multi-modality multi-task learning framework for 3D perception in autonomous driving

arXiv:2607.24224v1 Announce Type: new Abstract: Multi-modality data from different sensors provides rich complementary information for 3D perception, becoming an essential component in reliable autono

MAViE: A Multi-scale Adaptive Vision Encoder for Fine-grained Visual Perception and Efficient Multimodal Reasoning

arXiv:2607.24424v1 Announce Type: new Abstract: Vision-language models commonly project all tokens produced by a pretrained vision encoder into a large language model. However, final-layer features ca

Maximum Satisfiability of Simple Temporal Problems

arXiv:2607.23785v1 Announce Type: cross Abstract: The Simple Temporal Problem (STP) is a core framework for quantitative temporal constraints. As STP data can be inconsistent, we study MAXSTP: compute

Measuring Negative Campaigning across Languages with Large Language Models: A Study of 18 Million Tweets in 19 Countries

model-releasesarxiv-cs-cl

arXiv:2507.17636v2 Announce Type: replace Abstract: Negative campaigning is a defining feature of electoral competition, yet comparative research on its drivers has remained limited by the high cost a

MedDDC-Eval: Diagnosis-Decoupled Evaluation of Multi-Turn Medical Consultation Agents

arXiv:2607.18999v2 Announce Type: replace-cross Abstract: Evaluating multi-turn medical consultation agents requires judging the diagnostic support provided by the histories they elicit through intera

MedFailBench: A Clinician-Built Open-Source Benchmark for Medical AI Safety Boundary Inspection

arXiv:2607.15166v2 Announce Type: replace Abstract: Most medical AI benchmarks measure whether a model knows the correct answer. MedFailBench asks a different question: which safety boundary failed? W

MedLoCoMo: A Long-Context Multi-Session Medical Dialogue Benchmark for Large Language Models

arXiv:2607.22566v1 Announce Type: new Abstract: MedLoCoMo is a Medical Long-Context Memory benchmark for patient-specific clinical reasoning over multi-admission medical dialogue. Existing medical QA

MEGA-CL: A Molecular Foundation Model for Generalizable ADMET Prediction through Graph External Attention and Contrastive Learning

model-releasesarxiv-cs-lg

arXiv:2607.24314v1 Announce Type: new Abstract: Predicting the absorption, distribution, metabolism, excretion and toxicity (ADMET) properties of small molecules remains a major challenge in drug disc

MegaSlide-DiT: Memory-Centric Adaptation and Deformable Local Attention for Efficient Video Diffusion

arXiv:2607.22696v1 Announce Type: cross Abstract: High-resolution video diffusion models built on Diffusion Transformers (DiTs) deliver strong fidelity but quickly exhaust the memory budget of a singl

MemChain: Learning Interpretable Memory Traces for Memory-Augmented LLM Agents

arXiv:2607.24097v1 Announce Type: new Abstract: Memory-augmented LLM agents typically answer queries by retrieving relevant memories and feeding them directly to an answer model. This retrieval-as-evi

MEMENTO: Memory-Guided Memetic Code-as-Policy Evolution

arXiv:2607.22832v1 Announce Type: new Abstract: Long-horizon embodied tasks require policies that execute many dependent actions before task success can be observed. Representing policies as executabl

safetyarxiv-cs-lg

MEMOIR: Temporal Behavioral Memory for Recommendation Across the Preference-Drift Spectrum

arXiv:2607.23986v1 Announce Type: cross Abstract: We propose MEMOIR, a framework that segments user interaction histories into temporal windows, generates semantic behavioral memory for each period us

researcharxiv-cs-cl

Memory Efficient Audio Synthesis with Decoupled Temporal Depth Diffusion Transformers

model-releasesarxiv-cs-cl

arXiv:2607.23811v1 Announce Type: cross Abstract: Siri Expressive Voices synthesize rich, configurable speech in real time and entirely on device, powered by AFM 3 Core Advanced, Apple's most powerful

Memory for Attention: Language-Conditioned Re-Perception with a Vision--Language--Motion Map

arXiv:2607.23797v1 Announce Type: new Abstract: A robot carrying a persistent, behavior-annotated map faces two planning questions, and its memory answers only one well. The spatial-navigation questio

tutorialsarxiv-cs-ro

MemTX: Transactional Belief Commit for Stateful Agent Memory

arXiv:2607.23929v1 Announce Type: new Abstract: LLM agents increasingly coordinate through persistent shared memory: one agent's write becomes another agent's premise, and eventually a tool call with

MemVLN: Episodic and Procedural Memory for Vision-and-Language Navigation

arXiv:2607.23504v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to maintain long-horizon visual history for trajectory consistency wh

Meshless Domain Randomization via Explicit Parameter Perturbation of 3D Gaussian Splatting

arXiv:2607.22890v1 Announce Type: cross Abstract: Domain Randomization (DR) is a standard technique for closing the Sim-to-Real gap, yet traditional DR pipelines rely on classical computer graphics re

Metamorphic Testing for Clinical ML Models: A Framework Proposal and Pilot Study

arXiv:2607.22984v1 Announce Type: cross Abstract: Machine learning models for clinical prediction tasks, such as in-hospital mortality and sepsis onset, routinely achieve high AUROC scores. However, A

Metric Surface Reconstruction of Neurosurgical Scenes from Monocular Operating Microscope Images and Microscope Pose

arXiv:2607.22773v1 Announce Type: cross Abstract: Objective: We evaluated whether metric 3D geometry of neurosurgical operative exposure can be recovered from standard monocular operating-microscope i

MicroZoom: Structure-Preserving Detail Synthesis at Extreme Scale

arXiv:2607.24729v1 Announce Type: new Abstract: We introduce MicroZoom, a generative framework for gigapixel image synthesis at the microscopic scale. Given a standard photograph and a sparse set of c

tutorialsarxiv-cs-cv

MIITA: Memory-Induced Inference-Time Adaptation for Continual Learning with Small Language Models

arXiv:2607.22556v1 Announce Type: new Abstract: Continual learning (CL) is essential for small language models (SLMs) to adapt to evolving real-world needs in resource-constrained deployments. However

MIME: Multimodal Interactive Motion Encoder

arXiv:2607.22702v1 Announce Type: new Abstract: Text-motion representation learning has advanced rapidly, with growing interest in multi person interactions for animation, AR/VR, and embodied AI. Thes

safetyarxiv-cs-cv

Mini-batch Noise Lowers Sharpness via Dominant-Subspace Fluctuations

arXiv:2607.23012v1 Announce Type: new Abstract: During SGD training, the gradients often align strongly with the dominant subspace spanned by the top-k eigenvectors of the Hessian of the loss. While t

Minimax Lower Bounds of Kernel Discrepancy Estimation: MMD, HSIC, KSD

arXiv:2607.24235v1 Announce Type: cross Abstract: Over the past 20 years, kernel discrepancies have been leveraged as a highly powerful tool for quantifying the disagreement of distributions, with num

Applications

MINT-V2X: A Mobility-Integrated Network Trajectory Dataset for Predictive Resource Management

arXiv:2607.22654v1 Announce Type: new Abstract: Vehicle-to-Everything (V2X) communication systems are based on datasets that not only contain vehicle trajectory data but also wireless network paramete

applicationsarxiv-cs-ai

MioFFAn: an Annotation Software for Formula Formalization with LLM Automation Capabilities

arXiv:2607.22552v1 Announce Type: new Abstract: The automatic translation of mathematical expressions in scientific literature into executable symbolic code (a process we refer to as Formula Formaliza

researcharxiv-cs-cl

MiSS: A Logic-Driven Explanation of Minimal Sufficient Coalitions for Point Cloud Classifiers

arXiv:2607.24074v1 Announce Type: new Abstract: We present MiSS, a black-box, query-based framework for explaining 3D point cloud classifiers through perturbation-relative sufficiency reasoning. MiSS

researcharxiv-cs-ai

Mission-Level Runtime Assurance for LLM-Assisted ISR Swarms over a Verification-Aware Fabric

arXiv:2607.23532v1 Announce Type: cross Abstract: Swarms of LLM-assisted autonomous robots are increasingly proposed for cooperative intelligence, surveillance, and reconnaissance (ISR) in contested e

MixQuant: Adaptive Mixed-Precision Quantization for Large Language Models

arXiv:2607.23047v1 Announce Type: cross Abstract: Mixed-precision quantization improves the accuracy of post-training quantization by allocating higher bitwidths to sensitive layers, but existing meth