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Mind the Unseen Mass: Unmasking LLM Hallucinations via Soft-Hybrid Alphabet Estimation

arXiv:2604.19162v1 Announce Type: new Abstract: This paper studies uncertainty quantification for large language models (LLMs) under black-box access, where only a small number of responses can be sam

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Mind2Drive: Predicting Driver Intentions from EEG in Real-world On-Road Driving

DGX agent

arXiv:2604.19368v1 Announce Type: new Abstract: Predicting driver intention from neurophysiological signals offers a promising pathway for enhancing proactive safety in advanced driver assistance syst

safetyarxiv-cs-cv

22 Apr 2026

MiroThinker: Pushing the Performance Boundaries of Open-Source Research Agents via Model, Context, and Interactive Scaling

model-releasesarxiv-cs-cl

arXiv:2511.11793v3 Announce Type: replace Abstract: We present MiroThinker v1.0, an open-source research agent designed to advance tool-augmented reasoning and information-seeking capabilities. Unlike

MiTA Attention: Efficient Fast-Weight Scaling via a Mixture of Top-k Activations

arXiv:2602.01219v4 Announce Type: replace-cross Abstract: The attention operator in Transformers can be viewed as a two-layer fast-weight MLP, whose weights are dynamically instantiated from input tok

researcharxiv-cs-cv

Mitigating Judgment Preference Bias in Large Language Models through Group-Based Polling

arXiv:2510.08145v2 Announce Type: replace Abstract: Large Language Models (LLMs) as automatic evaluators, commonly referred to as LLM-as-a-Judge, have also attracted growing attention. This approach p

safetyarxiv-cs-cl

Mitigating Long-Tail Bias via Prompt-Controlled Diffusion Augmentation

arXiv:2602.04749v2 Announce Type: replace Abstract: Long-tailed class imbalance remains a fundamental obstacle in semantic segmentation of high-resolution remote-sensing imagery, where dominant classe

Mixture of Predefined Experts: Maximizing Data Usage on Vertical Federated Learning

arXiv:2602.12708v2 Announce Type: replace Abstract: Vertical Federated Learning (VFL) has emerged as a critical paradigm for collaborative model training in privacy-sensitive domains such as finance a

safetyarxiv-cs-lg

MMControl: Unified Multi-Modal Control for Joint Audio-Video Generation

arXiv:2604.19679v1 Announce Type: new Abstract: Recent advances in Diffusion Transformers (DiTs) have enabled high-quality joint audio-video generation, producing videos with synchronized audio within

Model-Agnostic Meta Learning for Class Imbalance Adaptation

arXiv:2604.18759v1 Announce Type: new Abstract: Class imbalance is a widespread challenge in NLP tasks, significantly hindering robust performance across diverse domains and applications. We introduce

Tutorials

Modelling and Analysing Behaviours and Emotions via Complex User Interactions

arXiv:1902.07683v1 Announce Type: cross Abstract: Over the past 15 years, the volume, richness and quality of data collected from the combined social networking platforms has increased beyond all expe

tutorialsarxiv-cs-ai

MoonSeg3R: Monocular Online Zero-Shot Segment Anything in 3D with Reconstructive Foundation Priors

arXiv:2512.15577v2 Announce Type: replace Abstract: In this paper, we focus on online zero-shot monocular 3D instance segmentation, a novel practical setting where existing approaches fail to perform

researcharxiv-cs-cv

MORPHOGEN: A Multilingual Benchmark for Evaluating Gender-Aware Morphological Generation

arXiv:2604.18914v1 Announce Type: cross Abstract: While multilingual large language models (LLMs) perform well on high-level tasks like translation and question answering, their ability to handle gram

MOSA: Motion-Guided Semantic Alignment for Dynamic Scene Graph Generation

arXiv:2604.19631v1 Announce Type: new Abstract: Dynamic Scene Graph Generation (DSGG) aims to structurally model objects and their dynamic interactions in video sequences for high-level semantic under

MRS: Multi-Resolution Skills for HRL Agents

arXiv:2505.21410v2 Announce Type: replace Abstract: Hierarchical reinforcement learning (HRL) decomposes the policy into a manager and a worker, enabling long-horizon planning but introducing a perfor

MSDS: Deep Structural Similarity with Multiscale Representation

model-releasesarxiv-cs-cv

arXiv:2604.19159v1 Announce Type: new Abstract: Deep-feature-based perceptual similarity models have demonstrated strong alignment with human visual perception in Image Quality Assessment (IQA). Howev

Tutorials

Multi-Cycle Spatio-Temporal Adaptation in Human-Robot Teaming

arXiv:2604.19670v1 Announce Type: cross Abstract: Effective human-robot teaming is crucial for the practical deployment of robots in human workspaces. However, optimizing joint human-robot plans remai

tutorialsarxiv-cs-ai

Multi-Domain Learning with Global Expert Mapping

model-releasesarxiv-cs-cv

arXiv:2604.18842v1 Announce Type: new Abstract: Human perception generalizes well across different domains, but most vision models struggle beyond their training data. This gap motivates multi-dataset

Multi-Gait Learning for Humanoid Robots Using Reinforcement Learning with Selective Adversarial Motion Prior

arXiv:2604.19102v1 Announce Type: cross Abstract: Learning diverse locomotion skills for humanoid robots in a unified reinforcement learning framework remains challenging due to the conflicting requir

Local Ai

Multi-Level Temporal Graph Networks with Local-Global Fusion for Industrial Fault Diagnosis

arXiv:2604.18765v1 Announce Type: cross Abstract: Fault detection and diagnosis are critical for the optimal and safe operation of industrial processes. The correlations among sensors often display no

local-aiarxiv-cs-ai

Multi-modal Reasoning with LLMs for Visual Semantic Arithmetic

arXiv:2604.19567v1 Announce Type: new Abstract: Reinforcement learning (RL) as post-training is crucial for enhancing the reasoning ability of large language models (LLMs) in coding and math. However,

Multi-modal Test-time Adaptation via Adaptive Probabilistic Gaussian Calibration

arXiv:2604.19093v1 Announce Type: cross Abstract: Multi-modal test-time adaptation (TTA) enhances the resilience of benchmark multi-modal models against distribution shifts by leveraging the unlabeled

Agents

Multi-Step Gaussian Process Propagation for Adaptive Path Planning

arXiv:2604.19148v1 Announce Type: new Abstract: Efficient and robust path planning hinges on combining all accessible information sources. In particular, the task of path planning for robotic environm

agentsarxiv-cs-ro

Multi-Task Reinforcement Learning for Enhanced Multimodal LLM-as-a-Judge

arXiv:2603.11665v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have been widely adopted as MLLM-as-a-Judges due to their strong alignment with human judgment across vario

safetyarxiv-cs-cl

Applications

Multi-view Crowd Tracking Transformer with View-Ground Interactions Under Large Real-World Scenes

arXiv:2604.19318v1 Announce Type: new Abstract: Multi-view crowd tracking estimates each person's tracking trajectories on the ground of the scene. Recent research works mainly rely on CNNs-based mult

applicationsarxiv-cs-cv

Multiclass Local Calibration with the Jensen-Shannon Distance

arXiv:2510.26566v2 Announce Type: replace-cross Abstract: Developing trustworthy Machine Learning (ML) models requires their predicted probabilities to be well-calibrated, meaning they should reflect

Multilingual Language Models Encode Script Over Linguistic Structure

model-releasesarxiv-cs-cl

arXiv:2604.05090v2 Announce Type: replace Abstract: Multilingual language models (LMs) organize representations for typologically and orthographically diverse languages into a shared parameter space,

Multimodal embodiment-aware navigation transformer

arXiv:2604.19267v1 Announce Type: new Abstract: Goal-conditioned navigation models for ground robots trained using supervised learning show promising zero-shot transfer, but their collision-avoidance

safetyarxiv-cs-ro

Tutorials

Multimodal Transformer for Sample-Aware Prediction of Metal-Organic Framework Properties

arXiv:2604.19383v1 Announce Type: cross Abstract: Metal-organic frameworks (MOFs) are a major target of machine-learning-based property prediction, yet most models assume that a single framework repre

tutorialsarxiv-cs-ai

NemeSys: Toward Online Underwater Exploration with Remote Operator-in-the-loop Adaptive Autonomy

model-releasesarxiv-cs-ro

arXiv:2507.11889v2 Announce Type: replace Abstract: Adaptive mission control and dynamic parameter reconfiguration are essential for autonomous underwater vehicles (AUVs) operating in GPS-denied, comm

NeuroAI and Beyond: Bridging Between Advances in Neuroscience and ArtificialIntelligence

arXiv:2604.18637v1 Announce Type: cross Abstract: Neuroscience and Artificial Intelligence (AI) have made impressive progress in recent years but remain only loosely interconnected. Based on a worksho

Neuromorphic Continual Learning for Sequential Deployment of Nuclear Plant Monitoring Systems

arXiv:2604.18611v1 Announce Type: cross Abstract: Anomaly detection in nuclear industrial control systems (ICS) requires continuous, energy-efficient monitoring across multiple subsystems that are oft

Nexusformer: Nonlinear Attention Expansion for Stable and Inheritable Transformer Scaling

arXiv:2604.19147v1 Announce Type: cross Abstract: Scaling Transformers typically necessitates training larger models from scratch, as standard architectures struggle to expand without discarding learn

Nonmonotone subgradient methods based on a local descent lemma

arXiv:2510.19341v2 Announce Type: replace-cross Abstract: In this paper we present a nonmonotone line search subgradient algorithm tailored to upper-C^2 functions. This is a family of nonsmooth and no

researcharxiv-cs-lg

ODMA: On-Demand Memory Allocation Strategy for LLM Serving on LPDDR-Class Accelerators

arXiv:2512.09427v5 Announce Type: replace-cross Abstract: Existing memory management techniques severely hinder efficient Large Language Model serving on accelerators constrained by poor random-access

OLLM: Options-based Large Language Models

arXiv:2604.19087v1 Announce Type: new Abstract: We introduce Options LLM (OLLM), a simple, general method that replaces the single next-token prediction of standard LLMs with a extit{set of learned op

Agents

OMAC: A Holistic Optimization Framework for LLM-Based Multi-Agent Collaboration

arXiv:2505.11765v3 Announce Type: replace-cross Abstract: Agents powered by advanced large language models (LLMs) have demonstrated impressive capabilities across diverse complex applications. Recentl

agentsarxiv-cs-ai

OmniGen2: Towards Instruction-Aligned Multimodal Generation

arXiv:2506.18871v4 Announce Type: replace-cross Abstract: In this work, we introduce OmniGen2, a versatile and open-source generative model designed to provide a unified solution for diverse generatio

OmniMouse: Scaling properties of multi-modal, multi-task Brain Models on 150B Neural Tokens

arXiv:2604.18827v1 Announce Type: cross Abstract: Scaling data and artificial neural networks has transformed AI, driving breakthroughs in language and vision. Whether similar principles apply to mode

OmniParser V2: Structured-Points-of-Thought for Unified Visual Text Parsing and Its Generality to Multimodal Large Language Models

arXiv:2502.16161v2 Announce Type: replace-cross Abstract: Visually-situated text parsing (VsTP) has recently seen notable advancements, driven by the growing demand for automated document understandin

OmniVoice: Towards Omnilingual Zero-Shot Text-to-Speech with Diffusion Language Models

arXiv:2604.00688v3 Announce Type: replace Abstract: We present OmniVoice, a massively multilingual zero-shot text-to-speech (TTS) model that scales to over 600 languages. At its core is a novel diffus

On Accelerating Grounded Code Development for Research

arXiv:2604.19022v1 Announce Type: new Abstract: A major challenge for niche scientific and technical domains in leveraging coding agents is the lack of access to up-to-date, domain- specific knowledge

On Solving the Multiple Variable Gapped Longest Common Subsequence Problem

arXiv:2604.18645v1 Announce Type: new Abstract: This paper addresses the Variable Gapped Longest Common Subsequence (VGLCS) problem, a generalization of the classical LCS problem involving flexible ga

Applications

On Temperature-Constrained Non-Deterministic Machine Translation: Potential and Evaluation

arXiv:2601.13729v2 Announce Type: replace Abstract: In recent years, the non-deterministic properties of language models have garnered considerable attention and have shown a significant influence on

applicationsarxiv-cs-cl

On the Conditioning Consistency Gap in Conditional Neural Processes

arXiv:2604.19312v1 Announce Type: new Abstract: Neural processes are meta-learning models that map context sets to predictive distributions. While inspired by stochastic processes, NPs do not generall

researcharxiv-cs-lg

On the Derivation of Tightly-Coupled LiDAR-Inertial Odometry with VoxelMap

arXiv:2603.15471v2 Announce Type: replace Abstract: This note presents a concise mathematical formulation of tightly-coupled LiDAR-Inertial Odometry within an iterated error-state Kalman filter framew

researcharxiv-cs-ro

On the Generalizability of Foundation Models for Crop Type Mapping

arXiv:2409.09451v5 Announce Type: replace Abstract: Foundation models pre-trained using self-supervised learning have shown powerful transfer learning capabilities on various downstream tasks, includi

Local Ai

On the Spatiotemporal Dynamics of Generalization in Neural Networks

arXiv:2602.01651v2 Announce Type: replace-cross Abstract: Why do neural networks fail to generalize addition from 16-digit to 32-digit numbers, while a child who learns the rule can apply it to arbitr

local-aiarxiv-cs-ai

On two ways to use determinantal point processes for Monte Carlo integration

arXiv:2604.19698v1 Announce Type: new Abstract: The standard Monte Carlo estimator widehat{I}_N^{MC} of int fdomega relies on independent samples from omega and has variance of order 1/N. Replacing th

researcharxiv-cs-lg