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Hybrid LLM-based Intelligent Framework for Robot Task Scheduling

arXiv:2605.15486v1 Announce Type: cross Abstract: This study introduces intelligent frameworks that use Large Language Models (LLMs) to improve task scheduling for construction robots. The LLM is fed

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Human DGX agent

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Hydra: Efficient, Correct Code Generation via Checkpoint-and-Rollback Support

DGX agent

arXiv:2605.15238v1 Announce Type: cross Abstract: Large language models are increasingly used for code generation, but many generated programs fail to compile, a prerequisite for further correctness c

researcharxiv-cs-ai

18 May 2026

HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion

arXiv:2605.15741v1 Announce Type: new Abstract: Pixel-space diffusion models bypass the reconstruction bottleneck of Variational Autoencoders (VAEs) but face a fundamental 'granularity dilemma': captu

safetyarxiv-cs-cv

Hypothesis-driven construction of mesoscopic dynamics

arXiv:2605.16211v1 Announce Type: new Abstract: Traditional scientific modeling typically begins with fixed, instance-wise effective equations and then carries out equation-specific analysis and compu

tutorialsarxiv-cs-lg

Agents

ICRL: Learning to Internalize Self-Critique with Reinforcement Learning

arXiv:2605.15224v1 Announce Type: new Abstract: Large language model-based agents make mistakes, yet critique can often guide the same model toward correct behavior. However, when critique is removed,

agentsarxiv-cs-ai

IHF-Harmony: Multi-Modality Magnetic Resonance Images Harmonization using Invertible Hierarchy Flow Model

arXiv:2602.21536v2 Announce Type: replace Abstract: Retrospective MRI harmonization is limited by poor scalability across modalities and reliance on traveling subject datasets. To address these challe

researcharxiv-cs-cv

Imitation learning for clinical decision support in pediatric ECMO

arXiv:2605.16175v1 Announce Type: new Abstract: Pediatric critical care is a dynamic, high-stakes process involving constant monitoring and adjustments in life-saving treatments. Modeling these interv

tutorialsarxiv-cs-lg

Imperfect World Models are Exploitable

arXiv:2605.15960v1 Announce Type: new Abstract: We propose a novel definition of model exploitation in reinforcement learning. Informally, a world model is exploitable if it implies that one policy sh

safetyarxiv-cs-ai

Improve Large Language Model Systems with User Logs

arXiv:2602.06470v2 Announce Type: replace-cross Abstract: Scaling training data and model parameters has long driven progress in large language models (LLMs), but this paradigm is increasingly constra

safetyarxiv-cs-ai

Improved Bounds for Reward-Agnostic and Reward-Free Exploration

model-releasesarxiv-cs-lg

arXiv:2602.16363v2 Announce Type: replace Abstract: We study reward-free and reward-agnostic exploration in episodic finite-horizon Markov decision processes (MDPs), where an agent explores an unknown

Improving Cross-Cultural Survey Simulation with Calibrated Value Personas

arXiv:2605.16193v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to simulate human opinions and survey responses, but their ability to reproduce population responses

researcharxiv-cs-cl

IndicSafe: A Benchmark for Evaluating Multilingual LLM Safety in South Asia

arXiv:2603.17915v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are deployed in multilingual settings, their safety behavior in culturally diverse, low-resource languages rem

Inductive inference of gradient-boosted decision trees on graphs for insurance fraud detection

model-releasesarxiv-cs-lg

arXiv:2510.05676v2 Announce Type: replace Abstract: Graph-based methods are becoming increasingly popular in machine learning due to their ability to model complex data and relations. Insurance fraud

Inevitable Encounters: Backdoor Attacks Involving Lossy Compression

arXiv:2603.13864v2 Announce Type: replace-cross Abstract: Real-world backdoor attacks often require poisoned datasets to be stored and transmitted before being used to compromise deep learning systems

applicationsarxiv-cs-cv

Information-Preserving Domain Transfer with Unlabeled Data in Misspecified Simulation-Based Inference

model-releasesarxiv-cs-lg

arXiv:2605.05652v2 Announce Type: replace Abstract: Simulation-based inference (SBI) provides amortized Bayesian parameter inference from simulator-generated data without requiring explicit likelihood

Integrating chemical structures as treatments improves representations of microscopy images for morphological profiling

arXiv:2504.09544v3 Announce Type: replace-cross Abstract: Recent advances in self-supervised deep learning have improved our ability to quantify cellular morphological changes in high-throughput micro

tutorialsarxiv-cs-cv

Interaction-Aware Influence Functions for Group Attribution

arXiv:2605.15675v1 Announce Type: cross Abstract: Influence functions approximate how removing a training example changes a quantity of interest, called the target function, such as a held-out loss. T

Intrinsic Wasserstein Rates for Score-Based Generative Models on Smooth Manifolds

arXiv:2605.15822v1 Announce Type: new Abstract: Score-based generative models are trained in high-dimensional ambient spaces, yet many data distributions are supported on low-dimensional nonlinear str

Introducing MELI: the Mandarin-English Language Interview Corpus

model-releasesarxiv-cs-cl

arXiv:2603.27043v2 Announce Type: replace Abstract: We introduce the Mandarin-English Language Interview (MELI) Corpus, an open-source resource of 29.8 hours of speech from 51 Mandarin-English bilingu

Invaria: Learning Scale and Density Invariance in Point Clouds via Next-Resolution Prediction

arXiv:2605.15923v1 Announce Type: new Abstract: Modern image encoders achieve high generalization by decoupling semantic meaning from resolution, an ability yet to be fully realized in the 3D domain.

tutorialsarxiv-cs-cv

IO-SVD: Input-Output Whitened SVD for Adaptive-Rank LLM Compression

arXiv:2605.15626v1 Announce Type: new Abstract: Large language models deliver strong performance across language and reasoning tasks, but their storage and compute costs remain major barriers to deplo

Local Ai

Is Agentic AI Ready for Real-World Hardware Engineering? A Deep Dive with Phoenix-bench

arXiv:2605.15226v1 Announce Type: cross Abstract: We ask whether agentic AI systems built for software engineering transfer to realistic hardware engineering. Existing hardware LLM benchmarks isolate

local-aiarxiv-cs-ai

Is One Score Enough? Rethinking the Evaluation of Sequentially Evolving LLM Memory

arXiv:2605.15384v1 Announce Type: cross Abstract: Memory plays a central role in enabling large language models (LLMs) to operate over sequential tasks by accumulating and reusing experience over time

researcharxiv-cs-ai

ITGPT: Generative Pretraining on Irregular Timeseries

arXiv:2605.16069v1 Announce Type: new Abstract: Timeseries regression models often struggle to leverage large volumes of labeled multimodal data, particularly when the data are irregularly sampled or

applicationsarxiv-cs-lg

IVGT: Implicit Visual Geometry Transformer for Neural Scene Representation

arXiv:2605.16258v1 Announce Type: cross Abstract: Reconstructing coherent 3D geometry and appearance from unposed multi-view images is a fundamental yet challenging problem in computer vision. Most ex

researcharxiv-cs-ai

Local Ai

JAM-Flow: Joint Audio-Motion Synthesis with Flow Matching

arXiv:2506.23552v2 Announce Type: replace Abstract: The intrinsic link between facial motion and speech is often overlooked in generative modeling, where talking head synthesis and text-to-speech (TTS

local-aiarxiv-cs-cv

Judge Circuits

model-releasesarxiv-cs-cl

arXiv:2605.16023v1 Announce Type: new Abstract: LLM-as-a-judge has become the dominant paradigm for grading model outputs at scale, yet the same model assigns systematically different scores when its

KaRMA: A Kinematic Metric for Fine Manipulation Ability in Robotic Hands

arXiv:2605.15548v1 Announce Type: new Abstract: Traditional robotic hand metrics focus on static properties such as workspace, manipulability, and grasp stability. However, these metrics do not direct

researcharxiv-cs-ro

Lagrangian Flow Matching: A Least-Action Framework for Principled Path Design

arXiv:2605.15419v1 Announce Type: new Abstract: Flow matching trains a neural velocity field by regression against a target velocity associated with a prescribed probability path connecting a simple i

Agents

Lamarckian Inheritance in Dynamic Environments: How Key Variables Affect Evolutionary Dynamics

arXiv:2605.15769v1 Announce Type: cross Abstract: The co-optimization of a robot's body and brain presents a coupled challenge: the morphology constrains which control strategies are effective, while

agentsarxiv-cs-ai

LAPS: Improving Incremental LiDAR Mapping using Active Pooling and Sampling for Neural Distance Fields

arXiv:2605.15496v1 Announce Type: cross Abstract: Neural distance fields offer a compact and continuous representation of 3D geometry, making them attractive for incremental LiDAR mapping. However, th

applicationsarxiv-cs-cv

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

arXiv:2603.25099v2 Announce Type: replace-cross Abstract: We present a framework in which a large language model (LLM) acts as an online adaptive controller for SIMP topology optimization, replacing c

Large Language Models Could Be Rote Learners

arXiv:2504.08300v5 Announce Type: replace-cross Abstract: Benchmark-based evaluation, e.g., multiple-choice questions (MCQs) and open-ended questions (OEQs), is widely used for evaluating Large Langua

LASER: Language Model Regression for Semi-Structured Workflow Resource and Runtime Estimation

arXiv:2512.19701v2 Announce Type: replace-cross Abstract: Accurate prediction of resource consumption and runtime for cloud workflow jobs is critical for scheduling efficiency, yet remains challenging

Latent Video Prediction Learns Better World Models

arXiv:2605.15618v1 Announce Type: cross Abstract: Self-supervised video models are increasingly framed as world models, yet their evaluation remains largely confined to a single top-1 accuracy score o

researcharxiv-cs-ai

LAtte: Hyperbolic Lorentz Attention for Cross-Subject EEG Classification

arXiv:2603.10881v2 Announce Type: replace Abstract: Electroencephalogram (EEG) classification plays a key role in medical diagnosis and brain-computer interfaces, but remains challenging due to low si

Layer Equivalence Is Not a Property of Layers Alone: How You Test Redundancy Changes What You Find

arXiv:2605.16234v1 Announce Type: cross Abstract: When researchers ask whether two transformer layers are 'equivalent' for compression, they often conflate distinct tests. Replacement asks whether one

Layer Selection in Feature-Based Losses Affects Image Quality and Microstructural Consistency in Deep Learning Super-Resolution of Brain Diffusion MRI

arXiv:2605.15895v1 Announce Type: cross Abstract: Clinical application of high-resolution diffusion MRI is hindered by hardware limitations and prohibitive scan times, motivating computational super-r

researcharxiv-cs-cv

Layer-wise Derivative Controlled Networks

arXiv:2605.15463v1 Announce Type: new Abstract: As machine learning models grow in complexity, they increasingly struggle with three conflicting demands: the need for high accuracy, the requirement fo

applicationsarxiv-cs-lg

LDGuid: A Framework for Robust Change Detection via Latent Difference Guidance

arXiv:2605.15582v1 Announce Type: new Abstract: Modern deep learning models for change detection (CD) often struggle to explicitly represent task-relevant semantic differences. This paper proposes the

tutorialsarxiv-cs-cv

Agents

LEAP: Trajectory-Level Evaluation of LLMs in Iterative Scientific Design

arXiv:2605.15341v1 Announce Type: cross Abstract: LLMs are increasingly deployed in autonomous laboratories, under the assumption that their domain priors and reasoning over iterative feedback let the

agentsarxiv-cs-ai

Learn Where Outcomes Diverge: Efficient VLA RL via Probabilistic Chunk Masking

arXiv:2605.16154v1 Announce Type: new Abstract: Reinforcement learning (RL) allows vision-language-action (VLA) policies to generalize beyond their training distribution by optimizing directly for tas

safetyarxiv-cs-lg

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization

model-releasesarxiv-cs-cv

arXiv:2605.15760v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard

Learning Bilevel Policies over Symbolic World Models for Long-Horizon Planning

arXiv:2605.15975v1 Announce Type: new Abstract: We tackle the challenge of building embodied AI agents that can reliably solve long-horizon planning problems. Imitation learning from demonstrations ha

safetyarxiv-cs-ai

Learning Context-conditioned Gaussian Overbounds for Convolution-Based Uncertainty Propagation

arXiv:2605.15789v1 Announce Type: new Abstract: Uncertainty quantification is essential in safety-critical settings--from autonomous driving to aviation, finance, and health--where decisions must rely

safetyarxiv-cs-lg

Learning Disentangled Representations for Generalized Multi-view Clustering

model-releasesarxiv-cs-cv

arXiv:2605.15640v1 Announce Type: new Abstract: Multi-View Clustering (MVC) has gained significant attention for its ability to leverage complementary information across diverse views. However, existi

Learning Dynamic Pick-and-Place for a Legged Manipulator

arXiv:2605.15713v1 Announce Type: cross Abstract: Legged manipulators extend robotic capabilities beyond static manipulation by integrating agile locomotion with versatile arm control. However, achiev

applicationsarxiv-cs-ai

Learning Dynamic Structural Specialization for Underwater Salient Object Detection

model-releasesarxiv-cs-cv

arXiv:2605.15535v1 Announce Type: new Abstract: Underwater salient object detection (USOD) has attracted increasing attention for underwater visual scene understanding and vision-guided robotic applic