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GeoMMBench and GeoMMAgent: Toward Expert-Level Multimodal Intelligence in Geoscience and Remote Sensing

arXiv:2604.08896v1 Announce Type: new Abstract: Recent advances in multimodal large language models (MLLMs) have accelerated progress in domain-oriented AI, yet their development in geoscience and rem

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GeoPAS: Geometric Probing for Algorithm Selection in Continuous Black-Box Optimisation

DGX agent

arXiv:2604.09095v1 Announce Type: new Abstract: Automated algorithm selection in continuous black-box optimisation typically relies on fixed landscape descriptors computed under a limited probing budg

model-releasesarxiv-cs-lg

13 Apr 2026

GRASP: Grounded CoT Reasoning with Dual-Stage Optimization for Multimodal Sarcasm Target Identification

arXiv:2604.08879v1 Announce Type: new Abstract: Moving beyond the traditional binary classification paradigm of Multimodal Sarcasm Detection, Multimodal Sarcasm Target Identification (MSTI) presents a

Hidden in Plain Sight: Visual-to-Symbolic Analytical Solution Inference from Field Visualizations

arXiv:2604.08863v1 Announce Type: new Abstract: Recovering analytical solutions of physical fields from visual observations is a fundamental yet underexplored capability for AI-assisted scientific rea

Hierarchical SVG Tokenization: Learning Compact Visual Programs for Scalable Vector Graphics Modeling

arXiv:2604.05072v2 Announce Type: replace Abstract: Recent large language models have shifted SVG generation from differentiable rendering optimization to autoregressive program synthesis. However, ex

HiFloat4 Format for Language Model Pre-training on Ascend NPUs

arXiv:2604.08826v1 Announce Type: cross Abstract: Large foundation models have become central to modern machine learning, with performance scaling predictably with model size and data. However, traini

HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help?

arXiv:2604.09408v1 Announce Type: new Abstract: Frontier coding agents solve complex tasks when given complete context but collapse when specifications are incomplete or ambiguous. The bottleneck is n

HM-Bench: A Comprehensive Benchmark for Multimodal Large Language Models in Hyperspectral Remote Sensing

arXiv:2604.08884v1 Announce Type: cross Abstract: While multimodal large language models (MLLMs) have made significant strides in natural image understanding, their ability to perceive and reason over

How Should Video LLMs Output Time? An Analysis of Efficient Temporal Grounding Paradigms

arXiv:2604.08966v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have advanced Video Temporal Grounding (VTG), existing methods often couple output paradigms with differe

HTNav: A Hybrid Navigation Framework with Tiered Structure for Urban Aerial Vision-and-Language Navigation

arXiv:2604.08883v1 Announce Type: cross Abstract: Inspired by the general Vision-and-Language Navigation (VLN) task, aerial VLN has attracted widespread attention, owing to its significant practical v

Improving Automatic Summarization of Radiology Reports through Mid-Training of Large Language Models

arXiv:2603.19275v2 Announce Type: replace-cross Abstract: Automatic summarization of radiology reports is an essential application to reduce the burden on physicians. Previous studies have widely used

Improving Model Performance by Adapting the KGE Metric to Account for System Non-Stationarity

arXiv:2604.03906v2 Announce Type: replace Abstract: Geoscientific systems tend to be characterized by pronounced temporal non-stationarity, arising from seasonal and climatic variability in hydrometeo

Inferring Latent Temporal Sparse Coordination Graph for Multi-Agent Reinforcement Learning

arXiv:2403.19253v3 Announce Type: replace Abstract: Effective agent coordination is crucial in cooperative Multi-Agent Reinforcement Learning (MARL). While agent cooperation can be represented by grap

Kill-Chain Canaries: Stage-Level Tracking of Prompt Injection Across Attack Surfaces and Model Safety Tiers

arXiv:2603.28013v3 Announce Type: replace-cross Abstract: Multi-agent LLM systems are entering production -- processing documents, managing workflows, acting on behalf of users -- yet their resilience

Lessons Without Borders? Evaluating Cultural Alignment of LLMs Using Multilingual Story Moral Generation

arXiv:2604.08797v1 Announce Type: cross Abstract: Stories are key to transmitting values across cultures, but their interpretation varies across linguistic and cultural contexts. Thus, we introduce mu

Listener-Rewarded Thinking in VLMs for Image Preferences

arXiv:2506.22832v3 Announce Type: replace-cross Abstract: Training robust and generalizable reward models for human visual preferences is essential for aligning text-to-image and text-to-video generat

Litmus (Re)Agent: A Benchmark and Agentic System for Predictive Evaluation of Multilingual Models

arXiv:2604.08970v1 Announce Type: cross Abstract: We study predictive multilingual evaluation: estimating how well a model will perform on a task in a target language when direct benchmark results are

Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift

arXiv:2604.08956v1 Announce Type: new Abstract: Adapting vision-language models to remote sensing imagery presents a fundamental challenge: both the visual and linguistic distributions of satellite da

Low Rank Based Subspace Inference for the Laplace Approximation of Bayesian Neural Networks

arXiv:2502.02345v2 Announce Type: replace Abstract: Subspace inference for neural networks assumes that a subspace of their parameter space suffices to produce a reliable uncertainty quantification. I

LPLCv2: An Expanded Dataset for Fine-Grained License Plate Legibility Classification

arXiv:2604.08741v1 Announce Type: new Abstract: Modern Automatic License Plate Recognition (ALPR) systems achieve outstanding performance in controlled, well-defined scenarios. However, large-scale re

LuMon: A Comprehensive Benchmark and Development Suite with Novel Datasets for Lunar Monocular Depth Estimation

arXiv:2604.09352v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is crucial for autonomous lunar rover navigation using electro-optical cameras. However, deploying terrestrial MDE netw

Mamba-Based Graph Convolutional Networks: Tackling Over-smoothing with Selective State Space

arXiv:2501.15461v4 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown great success in various graph-based learning tasks. However, it often faces the issue of over-smoothing as

Many-Tier Instruction Hierarchy in LLM Agents

arXiv:2604.09443v1 Announce Type: cross Abstract: Large language model agents receive instructions from many sources-system messages, user prompts, tool outputs, and more-each carrying different level

Many Ways to Be Fake: Benchmarking Fake News Detection Under Strategy-Driven AI Generation

arXiv:2604.09514v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have enabled the large-scale generation of highly fluent and deceptive news-like content. While prior wo

MARINER: A 3E-Driven Benchmark for Fine-Grained Perception and Complex Reasoning in Open-Water Environments

arXiv:2604.08615v1 Announce Type: cross Abstract: Fine-grained visual understanding and high-level reasoning in real-world open-water environments remain under-explored due to the lack of dedicated be

MATCHA: Efficient Deployment of Deep Neural Networks on Multi-Accelerator Heterogeneous Edge SoCs

arXiv:2604.09124v1 Announce Type: cross Abstract: Deploying DNNs on System-on-Chips (SoC) with multiple heterogeneous acceleration engines is challenging, and the majority of deployment frameworks can

MedConceal: A Benchmark for Clinical Hidden-Concern Reasoning Under Partial Observability

arXiv:2604.08788v1 Announce Type: new Abstract: Patient-clinician communication is an asymmetric-information problem: patients often do not disclose fears, misconceptions, or practical barriers unless

Medical Reasoning with Large Language Models: A Survey and MR-Bench

arXiv:2604.08559v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved strong performance on medical exam-style tasks, motivating growing interest in their deployment in real-wor

Memory-efficient Continual Learning with Prototypical Exemplar Condensation

arXiv:2603.13804v2 Announce Type: replace-cross Abstract: Rehearsal-based continual learning (CL) mitigates catastrophic forgetting by maintaining a subset of samples from previous tasks for replay. E

Memory-Efficient Transfer Learning with Fading Side Networks via Masked Dual Path Distillation

arXiv:2604.09088v1 Announce Type: new Abstract: Memory-efficient transfer learning (METL) approaches have recently achieved promising performance in adapting pre-trained models to downstream tasks. Th

Mitigating Extrinsic Gender Bias for Bangla Classification Tasks

arXiv:2411.10636v2 Announce Type: replace-cross Abstract: In this study, we investigate extrinsic gender bias in Bangla pretrained language models, a largely underexplored area in low-resource languag

Mnemis: Dual-Route Retrieval on Hierarchical Graphs for Long-Term LLM Memory

arXiv:2602.15313v2 Announce Type: replace Abstract: AI Memory, specifically how models organizes and retrieves historical messages, becomes increasingly valuable to Large Language Models (LLMs), yet e

MolPaQ: Modular Quantum-Classical Patch Learning for Interpretable Molecular Generation

arXiv:2604.08575v1 Announce Type: cross Abstract: Molecular generative models must jointly ensure validity, diversity, and property control, yet existing approaches typically trade off among these obj

MONETA: Multimodal Industry Classification through Geographic Information with Multi Agent Systems

arXiv:2604.07956v2 Announce Type: replace Abstract: Industry classification schemes are integral parts of public and corporate databases as they classify businesses based on economic activity. Due to

Multivariate Time Series Anomaly Detection via Dual-Branch Reconstruction and Autoregressive Flow-based Residual Density Estimation

arXiv:2604.08582v1 Announce Type: cross Abstract: Multivariate Time Series Anomaly Detection (MTSAD) is critical for real-world monitoring scenarios such as industrial control and aerospace systems. M

Natural Riemannian gradient for learning functional tensor networks

arXiv:2604.09263v1 Announce Type: cross Abstract: We consider machine learning tasks with low-rank functional tree tensor networks (TTN) as the learning model. While in the case of least-squares regre

NCL-BU at SemEval-2026 Task 3: Fine-tuning XLM-RoBERTa for Multilingual Dimensional Sentiment Regression

arXiv:2604.08923v1 Announce Type: new Abstract: Dimensional Aspect-Based Sentiment Analysis (DimABSA) extends traditional ABSA from categorical polarity labels to continuous valence-arousal (VA) regre

Neural networks for Text-to-Speech evaluation

arXiv:2604.08562v1 Announce Type: cross Abstract: Ensuring that Text-to-Speech (TTS) systems deliver human-perceived quality at scale is a central challenge for modern speech technologies. Human subje

Nexus: Same Pretraining Loss, Better Downstream Generalization via Common Minima

arXiv:2604.09258v1 Announce Type: new Abstract: Pretraining is the cornerstone of Large Language Models (LLMs), dominating the vast majority of computational budget and data to serve as the primary en

Noise-Aware In-Context Learning for Hallucination Mitigation in ALLMs

arXiv:2604.09021v1 Announce Type: cross Abstract: Auditory large language models (ALLMs) have demonstrated strong general capabilities in audio understanding and reasoning tasks. However, their reliab

NTIRE 2026 The 3rd Restore Any Image Model (RAIM) Challenge: Multi-Exposure Image Fusion in Dynamic Scenes (Track 2)

arXiv:2604.09030v1 Announce Type: new Abstract: This paper presents NTIRE 2026, the 3rd Restore Any Image Model (RAIM) challenge on multi-exposure image fusion in dynamic scenes. We introduce a benchm

On Semiotic-Grounded Interpretive Evaluation of Generative Art

arXiv:2604.08641v1 Announce Type: cross Abstract: Interpretation is essential to deciphering the language of art: audiences communicate with artists by recovering meaning from visual artifacts. Howeve

On-the-Fly Adaptation to Quantization: Configuration-Aware LoRA for Efficient Fine-Tuning of Quantized LLMs

arXiv:2509.25214v3 Announce Type: replace-cross Abstract: As increasingly large pre-trained models are released, deploying them on edge devices for privacy-preserving applications requires effective c

Online Intention Prediction via Control-Informed Learning

arXiv:2604.09303v1 Announce Type: cross Abstract: This paper presents an online intention prediction framework for estimating the goal state of autonomous systems in real time, even when intention is

PACED: Distillation and On-Policy Self-Distillation at the Frontier of Student Competence

arXiv:2603.11178v3 Announce Type: replace Abstract: Standard LLM distillation treats all training problems equally -- wasting compute on problems the student has already mastered or cannot yet solve.

Parameterized Complexity Of Representing Models Of MSO Formulas

arXiv:2604.08707v1 Announce Type: new Abstract: Monadic second order logic (MSO2) plays an important role in parameterized complexity due to the Courcelle's theorem. This theorem states that the probl

PhysInOne: Visual Physics Learning and Reasoning in One Suite

arXiv:2604.09415v1 Announce Type: cross Abstract: We present PhysInOne, a large-scale synthetic dataset addressing the critical scarcity of physically-grounded training data for AI systems. Unlike exi

PilotBench: A Benchmark for General Aviation Agents with Safety Constraints

arXiv:2604.08987v1 Announce Type: new Abstract: As Large Language Models (LLMs) advance toward embodied AI agents operating in physical environments, a fundamental question emerges: can models trained