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Graph Property Inference in Small Language Models: Effects of Representation and Reasoning Strategy

arXiv:2603.06635v2 Announce Type: replace Abstract: Recent progress in language modeling has expanded the range of tasks that can be approached through natural language interfaces, including problems

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Research

Grounding vs. Compositionality: On the Non-Complementarity of Reasoning in Neuro-Symbolic Systems

DGX agent

arXiv:2604.26521v1 Announce Type: new Abstract: Compositional generalization remains a foundational weakness of modern neural networks, limiting their robustness and applicability in domains requiring

researcharxiv-cs-ai

30 Apr 2026

HalluCiteChecker: A Lightweight Toolkit for Hallucinated Citation Detection and Verification in the Era of AI Scientists

arXiv:2604.26835v1 Announce Type: cross Abstract: We introduce HalluCiteChecker, a toolkit for detecting and verifying hallucinated citations in scientific papers. While AI assistant technologies have

Agents

Hankel and Toeplitz Rank-1 Decomposition of Arbitrary Matrices with Applications to Signal Direction-of-Arrival Estimation

arXiv:2604.26787v1 Announce Type: new Abstract: We consider the problems of computing the optimal rank-1 Hankel and Toeplitz-structured approximation of arbitrary matrices under L_2 and L_1-norm error

agentsarxiv-cs-lg

HealthNLP_Retrievers at ArchEHR-QA 2026: Cascaded LLM Pipeline for Grounded Clinical Question Answering

model-releasesarxiv-cs-cl

arXiv:2604.26880v1 Announce Type: new Abstract: Patient portals now give individuals direct access to their electronic health records (EHRs), yet access alone does not ensure patients understand or ac

Hearing the Room Through the Shape of the Drum: Modal-Guided Sound Recovery from Multi-Point Surface Vibrations

arXiv:2604.26678v1 Announce Type: new Abstract: Optical vibration sensing enables recovering the scene sound directly from the surface vibration of nearby objects, turning everyday objects into ``visu

researcharxiv-cs-cv

HER: Human-like Reasoning and Reinforcement Learning for LLM Role-playing

arXiv:2601.21459v4 Announce Type: replace-cross Abstract: LLM role-playing, i.e., using LLMs to simulate specific personas, has emerged as a key capability in various applications, such as companionsh

Heterogeneous Adaptive Policy Optimization: Tailoring Optimization to Every Token's Nature

arXiv:2509.16591v2 Announce Type: replace Abstract: Using entropy as a measure of heterogeneity to guide optimization has emerged as a crucial research direction in Reinforcement Learning for LLMs. Ho

safetyarxiv-cs-cl

Local Ai

Hierarchical adaptive control for real-time dynamic inference at the edge

arXiv:2604.26470v1 Announce Type: new Abstract: Industrial systems increasingly depend on Machine Learning (ML), and operate on heterogeneous nodes that must satisfy tight latency, energy, and memory

local-aiarxiv-cs-lg

Agents

Hierarchical Long-Term Semantic Memory for LinkedIn's Hiring Agent

arXiv:2604.26197v1 Announce Type: cross Abstract: Large Language Model (LLM) agents are increasingly used in real-world products, where personalized and context-aware user interactions are essential.

agentsarxiv-cs-lg

Hierarchical Multi-Persona Induction from User Behavioral Logs: Learning Evidence-Grounded and Truthful Personas

arXiv:2604.26120v1 Announce Type: new Abstract: Behavioral logs provide rich signals for user modeling, but are noisy and interleaved across diverse intents. Recent work uses LLMs to generate interpre

safetyarxiv-cs-ai

High-Dimensional Noise to Low-Dimensional Manifolds: A Manifold-Space Diffusion Framework for Degraded Hyperspectral Image Classification

arXiv:2604.26279v1 Announce Type: new Abstract: Recently, Hyperspectral Image (HSI) classification has attracted increasing attention in remote sensing. However, HSI data are inherently high-dimension

applicationsarxiv-cs-cv

HiPAN: Hierarchical Posture-Adaptive Navigation for Quadruped Robots in Unstructured 3D Environments

arXiv:2604.26504v1 Announce Type: new Abstract: Navigating quadruped robots in unstructured 3D environments poses significant challenges, requiring goal-directed motion, effective exploration to escap

safetyarxiv-cs-ro

HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models

arXiv:2604.26139v1 Announce Type: new Abstract: Diffusion large language models generate text through multi-step denoising, where hallucination signals may emerge throughout the trajectory rather than

researcharxiv-cs-cl

HOI-aware Adaptive Network for Weakly-supervised Action Segmentation

arXiv:2604.26227v1 Announce Type: new Abstract: In this paper, we propose an HOI-aware adaptive network named AdaAct for weakly-supervised action segmentation. Most existing methods learn a fixed netw

tutorialsarxiv-cs-cv

Human-in-the-Loop Benchmarking of Heterogeneous LLMs for Automated Competency Assessment in Secondary Level Mathematics

arXiv:2604.26607v1 Announce Type: new Abstract: As Competency-Based Education (CBE) is gaining traction around the world, the shift from marks-based assessment to qualitative competency mapping is a m

HumanOmni-Speaker: Identifying Who said What and When

model-releasesarxiv-cs-cv

arXiv:2603.21664v2 Announce Type: replace Abstract: While Omni-modal Large Language Models have made strides in joint sensory processing, they fundamentally struggle with a cornerstone of human intera

Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning

arXiv:2509.21983v2 Announce Type: replace-cross Abstract: Constructing robots to accomplish long-horizon tasks is a long-standing challenge within artificial intelligence. Approaches using generative

researcharxiv-cs-ai

Local Ai

Hybrid Quantum-Classical Ridgelet Neural Networks for Portfolio Optimization

arXiv:2601.03654v2 Announce Type: replace Abstract: In this study, we introduce a quantum computing method that incorporates Ridglet transforms into quantum processing pipelines for financial time-ser

local-aiarxiv-cs-lg

Hyper Input Convex Neural Networks for Shape Constrained Learning and Optimal Transport

arXiv:2604.26942v1 Announce Type: new Abstract: We introduce Hyper Input Convex Neural Networks (HyCNNs), a novel neural network architecture designed for learning convex functions. HyCNNs combine the

tutorialsarxiv-cs-lg

Identifying the Achilles' Heel: An Iterative Method for Dynamically Uncovering Factual Errors in Large Language Models

arXiv:2401.00761v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) like ChatGPT are foundational in various applications due to their extensive knowledge from pre-training and fine

applicationsarxiv-cs-ai

ImproBR: Bug Report Improver Using LLMs

arXiv:2604.26142v1 Announce Type: cross Abstract: Bug tracking systems play a crucial role in software maintenance, yet developers frequently struggle with low-quality user-submitted reports that omit

applicationsarxiv-cs-ai

Improving Bayesian Optimization for Portfolio Management with an Adaptive Scheduling

arXiv:2504.13529v4 Announce Type: replace Abstract: Existing black-box portfolio management systems are prevalent in the financial industry due to commercial and safety constraints, though their perfo

safetyarxiv-cs-lg

Incorporating Expert Knowledge into Bayesian Causal Discovery of Mixtures of Directed Acyclic Graphs

arXiv:2510.06735v2 Announce Type: replace Abstract: Bayesian causal discovery benefits from prior information elicited from domain experts, and in heterogeneous domains any prior knowledge would be ba

Incremental Strongly Connected Components with Predictions

arXiv:2604.26062v1 Announce Type: cross Abstract: Algorithms with predictions is a growing area that aims to leverage machine-learned predictions to design faster beyond-worst-case algorithms. In this

Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification

arXiv:2601.15808v2 Announce Type: replace Abstract: Recent advances in Deep Research Agents (DRAs) are transforming automated knowledge discovery and problem-solving. While the majority of existing ef

safetyarxiv-cs-ai

Inferix: A Block-Diffusion based Next-Generation Inference Engine for World Simulation

arXiv:2511.20714v2 Announce Type: replace-cross Abstract: World models serve as core simulators for fields such as agentic AI, embodied AI, and gaming, capable of generating long, physically realistic

Inferring bifurcation diagrams of two distinct chaotic systems by a single machine

arXiv:2604.26632v1 Announce Type: cross Abstract: We propose a dual-channel reservoir-computing scheme for inferring the dynamics of two distinct chaotic systems with a single machine. By augmenting a

Information Extraction from Electricity Invoices with General-Purpose Large Language Models

model-releasesarxiv-cs-cl

arXiv:2604.25927v1 Announce Type: new Abstract: Information extraction from semi-structured business documents remains a critical challenge for enterprise management. This study evaluates the capabili

Integrating Weather Foundation Model and Satellite to Enable Fine-Grained Solar Irradiance Forecasting

arXiv:2603.14845v3 Announce Type: replace-cross Abstract: Accurate day-ahead solar irradiance forecasting is essential for integrating solar energy into the power grid. However, it remains challenging

researcharxiv-cs-ai

Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI

arXiv:2502.11614v3 Announce Type: replace-cross Abstract: Prior studies have shown that distinguishing text generated by Large Language Models (LLMs) from human-written one is highly challenging for h

applicationsarxiv-cs-ai

KAYRA: A Microservice Architecture for AI-Assisted Karyotyping with Cloud and On-Premise Deployment

arXiv:2604.26869v1 Announce Type: cross Abstract: We present KAYRA, an end-to-end karyotyping system that operates inside the operational constraints of a clinical cytogenetic laboratory. KAYRA is arc

researcharxiv-cs-cv

L2RU: a Structured State Space Model with prescribed L2-bound

arXiv:2503.23818v3 Announce Type: replace-cross Abstract: Structured state-space models (SSMs) have recently emerged as a powerful architecture at the intersection of machine learning and control, fea

Language Diffusion Models are Associative Memories Capable of Retrieving Unseen Data

arXiv:2604.26841v1 Announce Type: cross Abstract: When do language diffusion models memorize their training data, and how to quantitatively assess their true generative regime? We address these questi

tutorialsarxiv-cs-ai

Laplace Approximation for Bayesian Tensor Network Kernel Machines

arXiv:2604.26673v1 Announce Type: cross Abstract: Uncertainty estimation is essential for robust decision-making in the presence of ambiguous or out-of-distribution inputs. Gaussian Processes (GPs) ar

Large Language Models for Multilingual Code Intelligence: A Survey

arXiv:2604.25960v1 Announce Type: cross Abstract: Large language models have transformed AI-assisted software engineering, but current research remains biased toward high-resource languages such as Py

applicationsarxiv-cs-lg

Last-Layer-Centric Feature Recombination: Unleashing 3D Geometric Knowledge in DINOv3 for Monocular Depth Estimation

arXiv:2604.26454v1 Announce Type: new Abstract: Monocular depth estimation (MDE) is a fundamental yet inherently ill-posed task. Recent vision foundation models (VFMs), particularly DINO-based transfo

researcharxiv-cs-cv

Latent Autoencoder Ensemble Kalman Filter for Nonlinear Data assimilation

arXiv:2603.06752v2 Announce Type: replace Abstract: The ensemble Kalman filter (EnKF) is widely used for data assimilation in high-dimensional systems, but its performance often deteriorates for stron

LATTICE: Evaluating Decision Support Utility of Crypto Agents

arXiv:2604.26235v1 Announce Type: cross Abstract: We introduce LATTICE, a benchmark for evaluating the decision support utility of crypto agents in realistic user-facing scenarios. Prior crypto agent

Layer-wise Lipschitz-Product Control for Deep Kolmogorov--Arnold Network Representations of Compositionally Structured Functions

arXiv:2604.26444v1 Announce Type: new Abstract: We prove that any continuous function f from [0,1]^n to R representable by a finite computation tree with N internal nodes and compositional sparsity s

Learning Neural Operator Surrogates for the Black Hole Accretion Code

arXiv:2604.25985v1 Announce Type: cross Abstract: General-relativistic magnetohydrodynamic (GR-MHD) simulations are essential for studying black hole accretion, relativistic jets, and magnetic reconne

Learning Over-Relaxation Policies for ADMM with Convergence Guarantees

arXiv:2604.26932v1 Announce Type: cross Abstract: The Alternating Direction Method of Multipliers (ADMM) is a widely used method for structured convex optimization, and its practical performance depen

Learning Sparse BRDF Measurement Samples from Image

arXiv:2604.26740v1 Announce Type: new Abstract: Accurate BRDF acquisition is important for realistic rendering, but dense gonioreflectometer measurements are slow and expensive. We study how to select

tutorialsarxiv-cs-cv

Learning to Ask: When LLM Agents Meet Unclear Instruction

arXiv:2409.00557v4 Announce Type: replace-cross Abstract: Equipped with the capability to call functions, modern large language models (LLMs) can leverage external tools for addressing a range of task

Agents

Learning to Rewrite Tool Descriptions for Reliable LLM-Agent Tool Use

arXiv:2602.20426v2 Announce Type: replace Abstract: While most efforts to improve LLM-based tool-using agents focus on the agent itself - through larger models, better prompting, or fine-tuning - agen

agentsarxiv-cs-ai

Learning to Route Electric Trucks Under Operational Uncertainty

arXiv:2604.26566v1 Announce Type: cross Abstract: Electric truck operations require routing decisions that remain feasible under limited battery range, long charging times, travel and energy consumpti

Learning Vision-Based Omnidirectional Navigation: A Teacher-Student Approach Using Monocular Depth Estimation

arXiv:2603.01999v2 Announce Type: replace-cross Abstract: Reliable obstacle avoidance in industrial settings demands 3D scene understanding, but widely used 2D LiDAR sensors perceive only a single hor

safetyarxiv-cs-cv

Lifting Embodied World Models for Planning and Control

arXiv:2604.26182v1 Announce Type: cross Abstract: World models of embodied agents predict future observations conditioned on an action taken by the agent. For complex embodiments, action spaces are hi

safetyarxiv-cs-ai