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Margin-Adaptive Confidence Ranking for Reliable LLM Judgement

arXiv:2605.15416v1 Announce Type: cross Abstract: Jung et al. (2025) introduce a hypothesis testing framework for guaranteeing agreement between large language models (LLMs) and human judgments, relyi

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Martingale Neural Operators: Learning Stochastic Marginals via Doob-Meyer Factorization

DGX agent

arXiv:2605.15806v1 Announce Type: new Abstract: Neural operators excel as deterministic surrogates, but inevitably collapse to the conditional mean when applied to stochastic PDEs, discarding the vari

researcharxiv-cs-lg

18 May 2026

Mask-Morph Graph U-Net: A Generalisable Mesh-Based Surrogate for Crashworthiness Field Prediction under Large Geometric Variation

arXiv:2605.15231v1 Announce Type: cross Abstract: Nonlinear finite element crash simulations are accurate but computationally expensive, limiting their use in iterative design optimisation. Machine-le

MaTe: Images Are All You Need for Material Transfer via Diffusion Transformer

arXiv:2605.15660v1 Announce Type: new Abstract: Recent diffusion-based methods for material transfer rely on image fine-tuning or complex architectures with assistive networks, but face challenges inc

safetyarxiv-cs-cv

MaxSketch: Robust Distinct Counting in Streams via Random Projections

arXiv:2605.15571v1 Announce Type: cross Abstract: Estimating the number of distinct elements in a data stream is well understood when repeated elements are identical. In modern settings, however, obse

researcharxiv-cs-lg

Measuring Maximum Activations in Open Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.15572v1 Announce Type: new Abstract: The dynamic range of activations is a first-order constraint for low-bit quantization, activation scaling, and stable LLM inference. Prior work characte

Agents

Mecha-nudges for Machines

arXiv:2603.23433v2 Announce Type: replace Abstract: AI agents are becoming active decision-makers on the Internet. As they make decisions in the same environments as humans, the environments themselve

agentsarxiv-cs-ai

Applications

Metropolis-Scale Road Network Datasets for Fine-Grained Urban Traffic Modeling

arXiv:2510.02278v2 Announce Type: replace Abstract: Modeling traffic dynamics is a critical challenge for urban computing, with applications from real-time traffic management to infrastructure plannin

applicationsarxiv-cs-lg

MHGraphBench: Knowledge Graph-Grounded Benchmarking of Mental Health Knowledge in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2605.15589v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in the mental health domain, yet it remains unclear how well they capture related biomedical knowledg

MI-CXR: A Benchmark for Longitudinal Reasoning over Multi-Interval Chest X-rays

arXiv:2605.15574v1 Announce Type: new Abstract: Longitudinal chest X-ray (CXR) interpretation requires reasoning over disease evolution across multiple patient visits, yet most existing medical VQA be

MIND: Decoupling Model-Induced Label Noise via Latent Manifold Disentanglement

arXiv:2605.16081v1 Announce Type: cross Abstract: The paradigm of learning from automatic annotations driven by pre-trained experts and Foundation Models dominates data-hungry applications. However, i

local-aiarxiv-cs-cv

Mind Dreamer: Untethering Imagination via Active Latent Intervention on Latent Manifolds

arXiv:2605.16030v1 Announce Type: new Abstract: Model-Based Reinforcement Learning (MBRL) leverages latent imagination for sample efficiency, yet remains constrained by Historical Tethering: imaginati

safetyarxiv-cs-lg

Mind the Motions: Benchmarking Theory-of-Mind in Everyday Body Language

arXiv:2511.15887v2 Announce Type: replace Abstract: Our ability to interpret others' mental states through nonverbal cues (NVCs) is fundamental to our survival and social cohesion. While existing Theo

researcharxiv-cs-cl

Minerva-Ego: Spatiotemporal Hints for Egocentric Video Understanding

arXiv:2605.15342v1 Announce Type: new Abstract: Video reasoning models are a core component of egocentric and embodied agents. However, standard benchmarks for assessing models provide only evaluation

Missing-Data-Induced Phase Transitions in Spectral PLS for Multimodal Learning

arXiv:2601.21294v2 Announce Type: replace Abstract: Partial Least Squares (PLS) learns shared structure from paired data via the top singular vectors of the empirical cross-covariance (PLS-SVD), but m

safetyarxiv-cs-lg

Misspecified Explore-then-Exploit Leads to Supra-Competitive Prices

arXiv:2605.16064v1 Announce Type: cross Abstract: We study whether simple algorithmic pricing systems can systematically produce collusive-like prices in multi-firm markets. We consider firms using an

Modeling Music as a Time-Frequency Image: A 2D Tokenizer for Music Generation

arXiv:2605.15831v1 Announce Type: cross Abstract: Autoregressive music generation depends strongly on the audio tokenizer. Existing high-fidelity codecs often use residual multi-codebook quantization,

Monotone and Separable Set Functions: Characterizations and Neural Models

arXiv:2510.23634v3 Announce Type: replace-cross Abstract: Motivated by applications for set containment problems, we consider the following fundamental problem: can we design set-to-vector functions s

MorphoHELM: A Comprehensive Benchmark for Evaluating Representations for Microscopy-Based Morphology Assays

arXiv:2605.15383v1 Announce Type: new Abstract: Microscopy images contain rich information about how cells respond to perturbations, making them essential to applications like drug screening. To quant

MR2-ByteTrack: CNN and Transformer-based Video Object Detection for AI-augmented Embedded Vision Sensor Nodes

arXiv:2605.15423v1 Announce Type: cross Abstract: Modern smart vision sensors need on-device intelligence to process video streams, as cloud computing is often impractical due to bandwidth, latency, a

mRadNet: A Compact Radar Object Detector with MetaFormer

arXiv:2509.16223v3 Announce Type: replace-cross Abstract: Frequency-modulated continuous wave radars have gained increasing popularity in the automotive industry. Their robustness against adverse weat

researcharxiv-cs-cv

Multi-Fidelity Flow Matching: Cascaded Refinement of PDE Solutions

arXiv:2605.16118v1 Announce Type: new Abstract: The source distribution in conditional flow matching is a design parameter that can be calibrated to data, not a default isotropic prior. We exploit thi

Multi-Level Contextual Token Relation Modeling for Machine-Generated Text Detection

arXiv:2605.16107v1 Announce Type: new Abstract: Machine-generated texts (MGTs) pose risks such as disinformation and phishing, underscoring the need for reliable detection. Metric-based methods, which

local-aiarxiv-cs-cl

Multi-level Self-supervised Pretraining on Compositional Hierarchical Graph for Molecular Property Prediction

arXiv:2605.16088v1 Announce Type: cross Abstract: Self-supervised pretraining on molecular graphs has emerged as a promising approach for molecular property prediction, yet most existing methods opera

Multi-Probe Zero Collision Hash (MPZCH): Mitigating Embedding Collisions and Enhancing Model Freshness in Large-Scale Recommenders

arXiv:2602.17050v3 Announce Type: replace Abstract: Embedding tables are critical components of large-scale recommendation systems, facilitating the efficient mapping of high-cardinality categorical f

Multimodal Object Detection Under Sparse Forest-Canopy Occlusion

arXiv:2605.15326v1 Announce Type: new Abstract: Reliable detection of humans beneath forest canopy remains a difficult remote-sensing challenge due to sparse, structured, and viewpoint-dependent occlu

researcharxiv-cs-cv

MuteBench: Modality Unavailability Tolerance Evaluation for Incomplete Multimodal Fusion

arXiv:2605.15235v1 Announce Type: new Abstract: Multimodal physiological data powers clinical AI systems from intensive care units to wearable devices, but sensors routinely fail in practice. Two fail

MyoChallenge 2025: A New Benchmark for Human Athletic Intelligence

model-releasesarxiv-cs-ro

arXiv:2605.15650v1 Announce Type: new Abstract: Athletic performance represents the pinnacle of human motor intelligence, demanding rapid choices, precise control, agility, and coordinated physical ex

Navigating Potholes with Geometry-Aware Sharpness Minimization

model-releasesarxiv-cs-ai

arXiv:2605.16134v1 Announce Type: cross Abstract: Sharpness-aware minimization (SAM) encourages flat minima by perturbing parameters along directions of high loss curvature, but treats all parameter d

Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters?

arXiv:2507.10236v2 Announce Type: replace Abstract: As generative Artificial Intelligence (AI) advances, the realism of AI generated imagery has reached a threshold capable of deceiving even vigilant

NavRL++: A System-Level Framework for Improving Sim-to-Real Transfer in Reinforcement Learning-Based Robot Navigation

arXiv:2605.15559v1 Announce Type: new Abstract: Recent years have witnessed significant progress in autonomous navigation using reinforcement learning. However, existing approaches largely emphasize r

safetyarxiv-cs-ro

Neural Activation Patterns Across Language Model Architectures: A Comprehensive Analysis of Cognitive Task Performance

arXiv:2605.15436v1 Announce Type: new Abstract: This paper presents a comprehensive analysis of neural activation patterns across six distinct large language model (LLM) architectures, examining their

researcharxiv-cs-cl

Tutorials

Neural Backward Filtering Forward Guiding

arXiv:2601.23030v2 Announce Type: replace-cross Abstract: Inference in nonlinear continuous stochastic processes on trees is challenging, particularly when observations are sparse and the topology is

tutorialsarxiv-cs-lg

Neural Point-Forms

arXiv:2605.15524v1 Announce Type: cross Abstract: Point cloud learning often rests on the premise that observed samples are noisy traces of an underlying geometric object, such as a manifold embedded

Neural Policy Composition from Free Energy Minimization

arXiv:2512.04745v3 Announce Type: replace-cross Abstract: The ability to flexibly compose previously acquired skills to execute intelligent behaviors is a hallmark of natural intelligence. Such compos

Neurosymbolic Object-Centric Learning with Distant Supervision

arXiv:2506.16129v2 Announce Type: replace Abstract: Neurosymbolic learning can use symbolic rules to provide supervision for latent concepts from weak labels, but it commonly assumes that the entities

researcharxiv-cs-cv

Neutral-Reference Prompting for Vision-Language Models

arXiv:2605.15615v1 Announce Type: new Abstract: Efficient transfer learning of vision-language models (VLMs) commonly suffers from a Base-New Trade-off (BNT): improving performance on unseen (new) cla

safetyarxiv-cs-cv

Agents

NIMO Controller: a self-driving laboratory orchestrator based on the Model Context Protocol

arXiv:2605.15227v1 Announce Type: new Abstract: Self-driving laboratories (SDLs) have attracted increasing attention as a means of accelerating scientific discovery; however, developing SDL software r

agentsarxiv-cs-ai

Njord: A Probabilistic Graph Neural Network for Ensemble Ocean Forecasting

arXiv:2605.15470v1 Announce Type: new Abstract: Ocean dynamics are inherently chaotic, yet existing machine learning ocean models produce only deterministic forecasts. We introduce Njord, a probabilis

NoiseShift: Resolution-Aware Noise Recalibration for Better Low-Resolution Image Generation

arXiv:2510.02307v2 Announce Type: replace-cross Abstract: Text-to-image diffusion models often degrade when sampled at resolutions outside the final training resolution set. Prior work has largely emp

Not All Tasks Quantize Equally: Fisher-Guided Quantization for Visual Geometry Transformer

arXiv:2605.15828v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models, represented by Visual Geometry Grounded Transformer (VGGT), jointly predict multiple visual geometry tasks such a

local-aiarxiv-cs-cv

NOVA: Fundamental Limits of Knowledge Discovery Through AI

arXiv:2605.15219v1 Announce Type: new Abstract: Can AI systems discover genuinely new knowledge through iterative self improvement, and if so, at what cost? We introduce the NOVA framework, which mode

Nudging Beyond the Comfort Zone: Efficient Strategy-Guided Exploration for RLVR

arXiv:2605.15726v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a scalable paradigm for improving the reasoning capabilities of large language mode

Offline Reinforcement Learning with Universal Horizon Models

arXiv:2605.15603v1 Announce Type: cross Abstract: Model-based reinforcement learning (RL) offers a compelling approach to offline RL by enabling value learning on imagined on-policy trajectories. Howe

Offline Semantic Guidance for Efficient Vision-Language-Action Policy Distillation

model-releasesarxiv-cs-ai

arXiv:2605.16241v1 Announce Type: cross Abstract: Billion-parameter Vision-Language-Action (VLA) policies have recently shown impressive performance in robotic manipulation, yet their size and inferen

OgBench: A Framework for Evaluating Graph Neural Networks on Omics Data

arXiv:2605.15511v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have become the dominant framework for inductive graph-level learning. Yet most benchmarks focus on the regime n gg p, wher

OHP-RL: Online Human Preference as Guidance in Reinforcement Learning for Robot Manipulation

arXiv:2605.15971v1 Announce Type: new Abstract: While reinforcement learning (RL) enables robots to acquire skills autonomously, its real-world deployment is severely limited by inefficient and unsafe

safetyarxiv-cs-ro

OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL

arXiv:2602.10687v3 Announce Type: replace-cross Abstract: Existing forgery detection methods are often limited to uni-modal or bi-modal settings, failing to handle the interleaved text, images, and vi