All entries

Minimal-Intervention KV Retention: A Design-Space Study and a Diversity-Penalty Survivor

arXiv:2605.14292v1 Announce Type: cross Abstract: KV-cache compression at small budgets is a crowded design space spanning cache representation, head-wise routing, compression cadence, decoding behavi

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Mining Subscenario Refactoring Opportunities in Behaviour-Driven Software Test Suites: ML Classifiers and LLM-Judge Baselines

DGX agent

arXiv:2605.14568v1 Announce Type: cross Abstract: Context. Behaviour-Driven Development (BDD) software test suites accumulate duplicated step subsequences. Three published refactoring patterns are ava

model-releasesarxiv-cs-cl

15 May 2026

Local Ai

Mistletoe: Stealthy Acceleration-Collapse Attacks on Speculative Decoding

arXiv:2605.14005v1 Announce Type: new Abstract: Speculative decoding has become a widely adopted technique for accelerating large language model (LLM) inference by drafting multiple candidate tokens a

local-aiarxiv-cs-cl

Mitigating Data Scarcity in Psychological Defense Classification with Context-Aware Synthetic Augmentation

arXiv:2605.14380v1 Announce Type: new Abstract: Psychological defense mechanisms (PDMs) are unconscious cognitive processes that modulate how individuals perceive and respond to emotional distress. Au

researcharxiv-cs-cl

Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models

arXiv:2605.14530v1 Announce Type: new Abstract: Large diffusion vision-language models (LDVLMs) have recently emerged as a promising alternative to autoregressive models, enabling parallel decoding fo

safetyarxiv-cs-cv

MiVE: Multiscale Vision-language features for reference-guided video Editing

arXiv:2605.14664v1 Announce Type: new Abstract: Reference-guided video editing takes a source video, a text instruction, and a reference image as inputs, requiring the model to faithfully apply the in

Mixed Integer Goal Programming for Personalized Meal Optimization with User-Defined Serving Granularity

arXiv:2605.13849v1 Announce Type: new Abstract: Determining what to eat to satisfy nutritional requirements is one of the oldest optimization problems in operations research, yet existing formulations

Tutorials

Mixture-of-Visual-Thoughts: Exploring Context-Adaptive Reasoning Mode Selection for General Visual Reasoning

arXiv:2509.22746v2 Announce Type: replace Abstract: Current visual reasoning methods mainly focus on exploring specific reasoning modes. Although improvements can be achieved in particular domains, th

tutorialsarxiv-cs-ai

ML-Embed: Inclusive and Efficient Embeddings for a Multilingual World

arXiv:2605.15081v1 Announce Type: cross Abstract: The development of high-quality text embeddings is increasingly drifting toward an exclusionary future, defined by three critical barriers: prohibitiv

MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring

arXiv:2510.23477v2 Announce Type: replace Abstract: Effective math tutoring requires not only solving problems but also diagnosing students' difficulties and guiding them step by step. While multimoda

Model-Adaptive Tool Necessity Reveals the Knowing-Doing Gap in LLM Tool Use

arXiv:2605.14038v1 Announce Type: new Abstract: Large language models (LLMs) increasingly act as autonomous agents that must decide when to answer directly vs. when to invoke external tools. Prior wor

Modeling Bounded Rationality in Drug Shortage Pharmacists Using Attention-Guided Dynamic Decomposition

arXiv:2605.14111v1 Announce Type: new Abstract: Hospital pharmacists make high-stakes decisions to mitigate drug shortages under uncertainty, time pressure, and patient risk. Interviews revealed that

Monitoring Data-aware Temporal Properties (Extended Version)

arXiv:2605.14666v1 Announce Type: new Abstract: Dynamic systems in AI are often complex and heterogeneous, so that an internal specification is not accessible and verification techniques such as model

MonoPRIO: Adaptive Prior Conditioning for Unified Monocular 3D Object Detection

arXiv:2605.14781v1 Announce Type: new Abstract: Monocular 3D object detection remains challenging because metric size and depth are underdetermined by single-view evidence, particularly under occlusio

MonoSpheres: Large-Scale Monocular SLAM-Based UAV Exploration through Perception-Coupled Mapping and Planning

arXiv:2511.17299v2 Announce Type: replace Abstract: Autonomous exploration of unknown environments is a key capability for mobile robots, but it is largely unsolved for robots equipped with only a sin

agentsarxiv-cs-ro

Moral Susceptibility and Robustness under Persona Role-Play in Large Language Models

arXiv:2511.08565v3 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly operate in social contexts, motivating analysis of how they express and shift moral judgments. In th

MoRe: Modular Representations for Principled Continual Representation Learning on Squantial Data

arXiv:2605.14364v1 Announce Type: new Abstract: Continual learning requires models to adapt to new data while preserving previously acquired knowledge. At its core, this challenge can be viewed as pri

safetyarxiv-cs-lg

Motion Planning for Autonomous Vehicles using Optimization over Graphs of Convex Sets

arXiv:2605.14199v1 Announce Type: new Abstract: Motion planning for autonomous vehicles requires generating collision-free and dynamically feasible trajectories in complex environments under real-time

agentsarxiv-cs-ro

MoZoo:Unleashing Video Diffusion power in animal fur and muscle simulation

model-releasesarxiv-cs-cv

arXiv:2605.13857v1 Announce Type: cross Abstract: The creation of cinematic-quality animal effects necessitates the precise modeling of muscle and fur dynamics, a process that remains both labor-inten

MPU: Towards Secure and Privacy-Preserving Knowledge Unlearning for Large Language Models

arXiv:2602.23798v2 Announce Type: replace-cross Abstract: Machine unlearning for large language models often faces a privacy dilemma in which strict constraints prohibit sharing either the server's pa

Multi-Block Attention for Efficient Channel Estimation in IRS-Assisted mmWave MIMO

arXiv:2605.15032v1 Announce Type: cross Abstract: Intelligent Reflecting Surfaces (IRSs) are a promising technology for enhancing the spectral and energy efficiency of millimeter-wave (mmWave) multipl

Multi-Dimensional Model Integrity and Responsibility Assessment Index and Scoring Framework

arXiv:2605.14550v1 Announce Type: new Abstract: Artificial intelligence in high-stakes tabular domains cannot be evaluated by predictive performance alone, yet current practice still assesses explaina

safetyarxiv-cs-lg

Multi-proposal Collaboration and Multi-task Training for Weakly-supervised Video Moment Retrieval

arXiv:2605.14838v1 Announce Type: new Abstract: This study focuses on weakly-supervised Video Moment Retrieval (VMR), aiming to identify a moment semantically similar to the given query within an untr

Multi-scale Coarse-to-fine Modeling for Test-time Human Motion Control

arXiv:2605.14935v1 Announce Type: new Abstract: We present MSCoT, a multi-scale, coarse-to-fine model for test-time human motion synthesis and control. Unlike recent approaches that rely on multiple i

safetyarxiv-cs-cv

Multi-Scale Dequant: Eliminating Dequantization Bottleneck via Activation Decomposition for Efficient LLM Inference

arXiv:2605.13915v1 Announce Type: cross Abstract: Quantization is essential for efficient large language model (LLM) inference, yet the dequantization step-converting low-bit weights back to high-prec

MultiEmo-Bench: Multi-label Visual Emotion Analysis for Multi-modal Large Language Models

arXiv:2605.14635v1 Announce Type: cross Abstract: This paper introduces a multi-label visual emotion analysis benchmark dataset for comprehensively evaluating the ability of multimodal large language

Applications

MultiMat: Multimodal Program Synthesis for Procedural Materials using Large Multimodal Models

arXiv:2509.22151v3 Announce Type: replace Abstract: Material node graphs are programs that generate the 2D channels of procedural materials, including geometry such as roughness and displacement maps,

applicationsarxiv-cs-cv

Multimodal Causal-Driven Representation Learning for Generalizable Medical Image Segmentation

arXiv:2508.05008v2 Announce Type: replace Abstract: Vision-Language Models (VLMs), such as CLIP, have demonstrated remarkable zero-shot capabilities in various computer vision tasks. However, their ap

MUON+: Towards More Effective Muon via One Additional Normalization Step for LLM Pre-training

arXiv:2602.21545v3 Announce Type: replace Abstract: Muon has recently emerged as a strong optimizer for large language model pre-training, orthogonalizing the momentum matrix via Newton--Schulz polar

nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI

arXiv:2605.14941v1 Announce Type: cross Abstract: Electroencephalogram (EEG) signals are highly susceptible to artifacts, resulting in a low signal-to-noise ratio which makes extraction of meaningful

Native Parallel Reasoner: Reasoning in Parallelism via Self-Distilled Reinforcement Learning

arXiv:2512.07461v3 Announce Type: replace Abstract: We introduce Native Parallel Reasoner (NPR), a teacher-free framework that enables Large Language Models (LLMs) to self-evolve genuine parallel reas

safetyarxiv-cs-cl

Natural Synthesis: Outperforming Reactive Synthesis Tools with Large Reasoning Models

arXiv:2605.15131v1 Announce Type: new Abstract: Reactive synthesis, the problem of automatically constructing a hardware circuit from a logical specification, is a long-standing challenge in formal ve

Near-Miss: Latent Policy Failure Detection in Agentic Workflows

arXiv:2603.29665v2 Announce Type: replace Abstract: Agentic systems for business process automation often require compliance with policies governing conditional updates to the system state. Evaluation

Applications

Nearest-Neighbor Radii under Dependent Sampling

arXiv:2605.14343v1 Announce Type: new Abstract: Nearest-neighbor methods are fundamental to classical and modern machine learning, yet their geometric properties are typically analyzed under independe

applicationsarxiv-cs-lg

NEST: Nested Event Stream Transformer for Sequences of Multisets

arXiv:2602.00520v3 Announce Type: replace Abstract: Event stream data often exhibit hierarchical structure in which multiple events co-occur, resulting in a sequence of multisets (i.e., bags of events

safetyarxiv-cs-lg

Network-Aware Bilinear Tokenization for Brain Functional Connectivity Representation Learning

arXiv:2605.14048v1 Announce Type: new Abstract: Masked autoencoders (MAEs) have recently shown promise for self-supervised representation learning of resting-state brain functional connectivity (FC).

Hardware

Neural Field Thermal Tomography: A Differentiable Physics Framework for Non-Destructive Evaluation

arXiv:2603.11045v2 Announce Type: replace-cross Abstract: Inverse problems for stiff parabolic partial differential equations (PDEs), such as the inverse heat conduction problem (IHCP), are severely i

hardwarearxiv-cs-ai

Neural Fields for NV-Center Inverse Sensing

arXiv:2605.13988v1 Announce Type: new Abstract: Inverse problems in scientific sensing are often solved with either hand-designed regularizers or supervised networks trained on simulated labels, yet b

Neural Signals Generate Clinical Notes in the Wild

arXiv:2601.22197v3 Announce Type: replace-cross Abstract: Generating clinical reports that summarize abnormal patterns, diagnostic findings, and clinical interpretations from long-term EEG recordings

NeuroAtlas: Benchmarking Foundation Models for Clinical EEG and Brain-Computer Interfaces

arXiv:2605.14698v1 Announce Type: cross Abstract: Foundation models (FMs) promise to extract unified representations that generalize across downstream tasks. They have emerged across fields, including

NeuroMambaLLM: Dynamic Graph Learning of fMRI Functional Connectivity in Autistic Brains Using Mamba and Language Model Reasoning

arXiv:2602.13770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated strong semantic reasoning across multimodal domains. However, their integration with graph-base

Neuromorphic Graph Anomaly Detection via Adaptive STDP and Spiking Graph Neural Networks

arXiv:2605.13863v1 Announce Type: cross Abstract: Anomaly detection in dynamic networks is critical for applications from cybersecurity to industrial monitoring, yet existing methods face challenges i

NeuroTrain: Surveying Local Learning Rules for Spiking Neural Networks with an Open Benchmarking Framework

arXiv:2605.15058v1 Announce Type: cross Abstract: The rapid expansion of spiking neural networks (SNNs) has led to a proliferation of training algorithms that differ widely in biological inspiration,

Nexus : An Agentic Framework for Time Series Forecasting

arXiv:2605.14389v1 Announce Type: new Abstract: Time series forecasting is not just numerical extrapolation, but often requires reasoning with unstructured contextual data such as news or events. Whil

NodeSynth: Socially Aligned Synthetic Data for AI Evaluation

arXiv:2605.14381v1 Announce Type: cross Abstract: Recent advancements in generative AI facilitate large-scale synthetic data generation for model evaluation. However, without targeted approaches, thes

Non-linear Interventions on Large Language Models

arXiv:2605.14749v1 Announce Type: cross Abstract: Intervention is one of the most representative and widely used methods for understanding the internal representations of large language models (LLMs).

Non-Stationary Online Structured Prediction with Surrogate Losses

arXiv:2510.07086v2 Announce Type: replace Abstract: Online structured prediction, including online classification as a special case, is the task of sequentially predicting labels from input features.

Not All Symbols Are Equal: Importance-Aware Constellation Design for Semantic Communication

arXiv:2605.14940v1 Announce Type: cross Abstract: Semantic communication systems for goal-oriented transmission must protect task-relevant information not only through source compression but also via