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Multi-Modal World Model for Physical Robot Interactions: Simultaneous Visual and Tactile Predictions for Enhanced Accuracy

arXiv:2304.11193v2 Announce Type: replace-cross Abstract: Predicting the outcomes of robotic actions, often referred to as learning a world model, in complex environments remains a fundamental challen

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Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization

DGX agent

arXiv:2605.13641v1 Announce Type: new Abstract: Complex reinforcement learning environments frequently employ multi-task and mixed-reward formulations. In these settings, heterogeneous reward distribu

safetyarxiv-cs-lg

14 May 2026

Multi-Quantile Regression for Extreme Precipitation Downscaling

arXiv:2605.12762v1 Announce Type: cross Abstract: Deep super-resolution networks for precipitation downscaling achieve strong bulk skill yet systematically under-predict the heavy-tail events that dri

Multi-Rollout On-Policy Distillation via Peer Successes and Failures

arXiv:2605.12652v1 Announce Type: cross Abstract: Large language models are often post-trained with sparse verifier rewards, which indicate whether a sampled trajectory succeeds but provide limited gu

Tutorials

Multimodal Graph-based Classification of Esophageal Motility Disorders

arXiv:2605.13623v1 Announce Type: new Abstract: Diagnosing esophageal motility disorders pose significant challenges due to the complexity of high-resolution impedance manometry (HRIM) data and variab

tutorialsarxiv-cs-lg

Multimodal Hidden Markov Models for Persistent Emotional State Tracking

arXiv:2605.12838v1 Announce Type: new Abstract: Tracking an interpretable emotional arc of a conversation via the sentiment of individual utterances processed as a whole is central to both understandi

Multistep Belief Space Dynamics Learning For Risk-Aware Control

arXiv:2605.12628v1 Announce Type: new Abstract: As autonomous vehicles move from a simplified research setting to practical use, there exists a large gap between the dynamic behavior of a human drivin

agentsarxiv-cs-ro

Multitask Multimodal Fusion with Tabular Foundation Models for Peak and Durability Prediction of Pertussis Booster Response

arXiv:2605.12852v1 Announce Type: new Abstract: Pertussis booster vaccination produces immune responses that vary widely across individuals in both peak magnitude and long-term durability. These two p

N-vium: Mixture-of-Exits Transformer for Accelerated Exact Generation

arXiv:2605.13190v1 Announce Type: cross Abstract: Improving the inference efficiency of autoregressive transformers typically means reducing FLOPs per token, usually through approximations that degrad

NAACA: Training-Free NeuroAuditory Attentive Cognitive Architecture with Oscillatory Working Memory for Salience-Driven Attention Gating

arXiv:2605.13651v1 Announce Type: cross Abstract: Audio provides critical situational cues, yet current Audio Language Models (ALMs) face an attention bottleneck in long-form recordings where dominant

Negation Neglect: When models fail to learn negations in training

arXiv:2605.13829v1 Announce Type: cross Abstract: We introduce Negation Neglect, where finetuning LLMs on documents that flag a claim as false makes them believe the claim is true. For example, models

Neural QAOA^{2}: Differentiable Joint Graph Partitioning and Parameter Initialization for Quantum Combinatorial Optimization

arXiv:2605.13072v1 Announce Type: cross Abstract: The quantum approximate optimization algorithm (QAOA) holds promise for combinatorial optimization but is constrained by limited qubits. While divide-

Neural Surrogate Forward Modelling For Electrocardiology Without Explicit Intracellular Conductivity Tensor

arXiv:2605.13366v1 Announce Type: new Abstract: Accurate forward modelling is essential for non-invasive cardiac electrophysiology, particularly in atrial fibrillation, where electrical activation is

Neural Video Compression with Domain Transfer

arXiv:2605.13476v1 Announce Type: new Abstract: Content-adaptive compression has always been a key direction in neural video coding (NVC), aiming to mitigate the domain gap between training and testin

Neurodata Without Boredom: Benchmarking Agentic AI for Data Reuse

arXiv:2605.12808v1 Announce Type: new Abstract: Neuroscience data are highly fragmented across labs, formats, and experimental paradigms, and reuse often requires substantial manual effort. A persiste

agentsarxiv-cs-lg

NeuroRisk: Physics-Informed Neural Optimization for Risk-Aware Traffic Engineering

arXiv:2605.12862v1 Announce Type: cross Abstract: In production Wide-Area Networks (WANs), correlated failures dominate availability losses, forcing operators to reserve large safety margins that leav

safetyarxiv-cs-lg

Neurosymbolic Auditing of Natural-Language Software Requirements

arXiv:2605.13817v1 Announce Type: cross Abstract: Natural-language software requirements are often ambiguous, inconsistent, and underspecified; in safety-critical domains, these defects propagate into

NFR: Neural Feature-Guided Non-Rigid Shape Registration

arXiv:2505.22445v2 Announce Type: replace-cross Abstract: In this paper, we propose a novel learning-based framework for 3D shape registration, which overcomes the challenges of significant non-rigid

No Attack Required: Semantic Fuzzing for Specification Violations in Agent Skills

arXiv:2605.13044v1 Announce Type: cross Abstract: LLM-powered agents can silently delete documents, leak credentials, or transfer funds on a routine user request, not because the agent was attacked, b

No One Knows the State of the Art in Geospatial Foundation Models

model-releasesarxiv-cs-cv

arXiv:2605.12678v1 Announce Type: new Abstract: Geospatial foundation models (GFMs) have been proposed as generalizable backbones for disaster response, land-cover mapping, food-security monitoring, a

Not Just RLHF: Why Alignment Alone Won't Fix Multi-Agent Sycophancy

arXiv:2605.12991v1 Announce Type: cross Abstract: LLM-based multi-agent pipelines flip from correct to incorrect answers under simulated peer disagreement at rates we term yield, a vulnerability widel

Object Manipulation of the Variable Topology Truss system

arXiv:2605.13086v1 Announce Type: new Abstract: This paper presents an object manipulation strategy for the Variable Topology Truss (VTT) system, a truss robot that comprises actuated truss members co

researcharxiv-cs-ro

Occlusion-Based Object Transportation Around Obstacles With a Swarm of Miniature Robots

arXiv:2605.13006v1 Announce Type: new Abstract: Swarm robotics utilises decentralised self-organising systems to form complex collective behaviours built from the bottom-up using individuals that have

agentsarxiv-cs-ro

Tutorials

OceanCBM: A Concept Bottleneck Model for Mechanistic Interpretability in Ocean Forecasting

arXiv:2605.12639v1 Announce Type: new Abstract: Extreme ocean phenomena are challenging not only to predict but to diagnose, as accurate forecasts alone do not reveal the underlying physical drivers.

tutorialsarxiv-cs-lg

OCH3R: Object-Centric Holistic 3D Reconstruction

arXiv:2605.13018v1 Announce Type: new Abstract: Object-centric scene understanding is a fundamental challenge in computer vision. Existing approaches often rely on multi-stage pipelines that first app

ODRPO: Ordinal Decompositions of Discrete Rewards for Robust Policy Optimization

arXiv:2605.12667v1 Announce Type: cross Abstract: The alignment of Large Language Models (LLMs) utilizes Reinforcement Learning from AI Feedback (RLAIF) for non-verifiable domains such as long-form qu

Offline Two-Player Zero-Sum Markov Games with KL Regularization

arXiv:2605.13025v1 Announce Type: new Abstract: We study the problem of learning Nash equilibria in offline two-player zero-sum Markov games. While existing approaches often rely on explicit pessimism

OmniLiDAR: A Unified Diffusion Framework for Multi-Domain 3D LiDAR Generation

model-releasesarxiv-cs-cv

arXiv:2605.13815v1 Announce Type: new Abstract: LiDAR scene generation is increasingly important for scalable simulation and synthetic data creation, especially under diverse sensing conditions that a

On Hallucinations in Inverse Problems: Fundamental Limits and Provable Assessment Methods

arXiv:2605.13146v1 Announce Type: cross Abstract: Artificial intelligence (AI) has transformed imaging inverse problems, from medical diagnostics to Earth observation. Yet deep neural networks can pro

On Privacy-Preserving Image Transmission in Low-Altitude Networks: A Swin Transformer-Based Framework with Federated Learning

arXiv:2605.12566v1 Announce Type: cross Abstract: The rapid development of low-altitude economy has driven the proliferation of Unmanned Aerial Vehicle (UAV) applications, including logistics, inspect

On the Generalization of Knowledge Distillation: An Information-Theoretic View

arXiv:2605.13143v1 Announce Type: cross Abstract: Knowledge distillation is widely used to improve generalization in practice, yet its theoretical understanding remains elusive. In the standard distil

safetyarxiv-cs-lg

On the Limits of Latent Reuse in Diffusion Models

arXiv:2605.13448v1 Announce Type: cross Abstract: Diffusion models are often trained in low-dimensional latent spaces, which are then reused for related but shifted datasets. In this work, we study wh

On the Sample Complexity of Differentially Private Policy Optimization

arXiv:2510.21060v3 Announce Type: replace-cross Abstract: Policy optimization (PO) is a cornerstone of modern reinforcement learning (RL), with diverse applications spanning robotics, healthcare, and

On the Size Complexity and Decidability of First-Order Progression

arXiv:2605.12691v1 Announce Type: new Abstract: Progression, the task of updating a knowledge base to reflect action effects, generally requires second-order logic. Identifying first-order special cas

Applications

Online Conformal Prediction: Enforcing monotonicity via Online Optimization

arXiv:2605.12668v1 Announce Type: cross Abstract: Conformal prediction provides a principled framework for uncertainty quantification with finite-sample coverage guarantees. While recent work has exte

applicationsarxiv-cs-lg

Hardware

OP4KSR: One-Step Patch-Free 4K Super-Resolution with Periodic Artifact Suppression

arXiv:2605.13457v1 Announce Type: new Abstract: Diffusion-based real-world image super-resolution (Real-ISR) has achieved remarkable perceptual quality; however, directly super-resolving images to 4K

hardwarearxiv-cs-cv

OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research

arXiv:2605.13618v1 Announce Type: cross Abstract: The Materials Genome Initiative catalyzed the proliferation of centralized platforms--SaaS, PaaS, and IaaS--that aggregate computational and experimen

agentsarxiv-cs-ai

Tutorials

Optimization, Generalization and Differential Privacy Bounds for Gradient Descent on Kolmogorov-Arnold Networks

arXiv:2601.22409v3 Announce Type: replace-cross Abstract: Kolmogorov--Arnold Networks (KANs) have recently emerged as a structured alternative to standard MLPs, yet a principled theory for their train

tutorialsarxiv-cs-ai

Optimization in Sparse 2D to Dense 3D Weakly Supervised Learning: Application to Multi-Label Segmentation of Large ex vivo MRI Data

arXiv:2605.12753v1 Announce Type: cross Abstract: INTRODUCTION | Fully supervised 3D segmentation of high-resolution ex vivo MRI is limited by the prohibitive cost of volumetric annotation, forcing re

OptMap: Geometric Map Distillation via Submodular Maximization

arXiv:2512.07775v2 Announce Type: replace Abstract: Autonomous robots rely on geometric maps to inform a diverse set of perception and decision-making algorithms. As autonomy requires reasoning and pl

safetyarxiv-cs-ro

Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion

arXiv:2605.12825v1 Announce Type: cross Abstract: We introduce Orthrus, a simple and efficient dual-architecture framework that unifies the exact generation fidelity of autoregressive Large Language M

OSDN: Improving Delta Rule with Provable Online Preconditioning in Linear Attention

model-releasesarxiv-cs-lg

arXiv:2605.13473v1 Announce Type: new Abstract: Linear attention and state-space models offer constant-memory alternatives to softmax attention, but often struggle with in-context associative recall.

PaMM: Periodic Motif Memory for Atomistic Models with an Explicit Local-Structure Interface

model-releasesarxiv-cs-lg

arXiv:2605.13297v1 Announce Type: new Abstract: Periodic crystals repeatedly instantiate similar local coordination motifs across translated cells and chemically related structures, but current equiva

PanoWorld: Towards Spatial Supersensing in 360^irc Panorama World

arXiv:2605.13169v1 Announce Type: cross Abstract: Multimodal large laboratory models (MLLMs) still struggle with spatial understanding under the dominant perspective-image paradigm, which inherits the

Parallel-in-Time Training of Recurrent Neural Networks for Dynamical Systems Reconstruction

arXiv:2605.12683v1 Announce Type: cross Abstract: Reconstructing nonlinear dynamical systems (DS) from data (DSR) is a fundamental challenge in science and engineering, but it inherently relies on seq

agentsarxiv-cs-ai

Parallel Scan Recurrent Neural Quantum States for Scalable Variational Monte Carlo

model-releasesarxiv-cs-lg

arXiv:2605.13807v1 Announce Type: cross Abstract: Neural-network quantum states have emerged as a powerful variational framework for quantum many-body systems, with recent progress often driven by mas

Pareto-Guided Optimal Transport for Multi-Reward Alignment

arXiv:2605.13155v1 Announce Type: new Abstract: Text-to-image generation models have achieved remarkable progress in preference optimization, yet achieving robust alignment across diverse reward model

safetyarxiv-cs-cv

Partial Optimality in the Preordering Problem

arXiv:2602.17346v2 Announce Type: replace-cross Abstract: Preordering is a generalization of clustering and partial ordering with applications in bioinformatics and social network analysis. Given a fi