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HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction

arXiv:2506.03837v2 Announce Type: replace-cross Abstract: The discovery of high-temperature superconducting materials holds great significance for human industry and daily life. In recent years, resea

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Human-Certified Module Repositories for the AI Age

DGX agent

arXiv:2603.02512v4 Announce Type: replace-cross Abstract: Human-Certified Module Repositories (HCMRs) are introduced in this work as a new architectural model for constructing trustworthy software in

researcharxiv-cs-ai

19 May 2026

Agents

Human-Flow Digital Twin for Predicting the Effects of Mobility Introduction on Visitor Circulation

arXiv:2605.17426v1 Announce Type: cross Abstract: We propose a framework for predicting the effects of mobility introduction measures using a human-flow digital twin. This digital twin incorporates a

agentsarxiv-cs-lg

Hunt Instead of Wait: Evaluating Deep Data Research on Large Language Models

arXiv:2602.02039v2 Announce Type: replace Abstract: The agency expected of Agentic Large Language Models goes beyond answering correctly, requiring autonomy to set goals and decide what to explore. We

Hybrid Feature Combinations with CNN for Bangla Fake News Classification

arXiv:2605.17481v1 Announce Type: new Abstract: Nowadays, people in Bangladesh frequently rely on the internet and social media for daily news instead of traditional newspapers. However, the spread of

researcharxiv-cs-cl

Hybrid Quantum-Classical Neural Architecture Search

arXiv:2605.18345v1 Announce Type: cross Abstract: Hybrid quantum-classical neural networks (HQNNs) are emerging as a practical approach for quantum machine learning in the noisy intermediate-scale qua

researcharxiv-cs-lg

Hybrid Quantum-MambaVision: A Quantum-enhanced State Space Model for Calibrated Mixed-type Wafer Defect Detection

arXiv:2605.16404v1 Announce Type: new Abstract: Extracting actionable knowledge from industrial visual data is fundamentally bottlenecked by extreme class imbalance and the prohibitive computational c

applicationsarxiv-cs-cv

HyDRA: Hybrid Dynamic Routing Architecture for Heterogeneous LLM Pools

model-releasesarxiv-cs-cl

arXiv:2605.17106v1 Announce Type: new Abstract: Production LLM deployments increasingly maintain heterogeneous model pools spanning order-of-magnitude cost differences. Existing routers make binary st

HydroAgent: Closing the Gap Between Frontier LLMs and Human Experts in Hydrologic Model Calibration via Simulator-Grounded RL

model-releasesarxiv-cs-lg

arXiv:2605.17792v1 Announce Type: new Abstract: Calibrating distributed hydrologic models is a critical bottleneck across operational water resources management - streamflow prediction, reservoir oper

Hypergraph Pattern Machine: Compositional Tokenization for Higher-Order Interactions

arXiv:2605.16527v1 Announce Type: cross Abstract: Hypergraphs model higher-order relations that drive real-world decisions, from drug prescriptions to recommendations. A central structural signal in s

applicationsarxiv-cs-ai

HyperPersona: A Multi-Level Hypergraph Framework for Text-Based Automatic Personality Prediction

arXiv:2605.17355v1 Announce Type: new Abstract: As a modern commodity, language has become a vast repository of socially and psychologically significant traits and concepts, reflecting the ways people

local-aiarxiv-cs-ai

HyperTea: A Hypergraph-based Temporal Enhancement and Alignment Network for Moving Infrared Small Target Detection

arXiv:2508.10678v2 Announce Type: replace Abstract: In practical application scenarios, moving infrared small target detection (MIRSTD) remains highly challenging due to the target's small size, weak

local-aiarxiv-cs-cv

HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbone

arXiv:2605.17286v1 Announce Type: new Abstract: While hyperspectral imaging provides rich spatial-spectral information across hundreds of narrow wavelength bands for precise material identification, g

HYVINT: Intensity-Driven Hypergraph Generation with Variational Representations

arXiv:2605.16836v1 Announce Type: cross Abstract: Hypergraphs provide a principled framework for modeling polyadic interactions, with applications in recommendation systems, social networks, and molec

applicationsarxiv-cs-lg

Identifiable Token Correspondence for World Models

arXiv:2605.16457v1 Announce Type: cross Abstract: Transformer-based world models have shown strong performance in visual reinforcement learning, but often suffer from temporal inconsistency in long-ho

Identify Then Project: Contrastive Learning of Latent Dynamics from Partial Observations with Port-Hamiltonian Structure

arXiv:2605.16682v1 Announce Type: new Abstract: Identifying latent state representations and dynamics is essential when direct modeling in observation space is infeasible, particularly under partial a

researcharxiv-cs-lg

Identifying Latent Actions and Dynamics from Offline Data via Demonstrator Diversity

arXiv:2603.17577v2 Announce Type: replace-cross Abstract: Can latent actions and environment dynamics be recovered from offline trajectories when actions are never observed? We study this question in

IdGlow: Dynamic Identity Modulation for Multi-Subject Generation

arXiv:2603.00607v2 Announce Type: replace-cross Abstract: Multi-subject image generation requires seamlessly harmonizing multiple reference identities within a coherent scene. However, existing method

local-aiarxiv-cs-ai

'I'm Not Mad, Just Focused'': Understanding Human Emotions in Human-Robot Collaboration

arXiv:2605.16816v1 Announce Type: new Abstract: Human-robot collaboration (HRC) can benefit from robots' abilities to interpret human emotional states. However, current emotion recognition (ER) models

safetyarxiv-cs-ro

Image-to-Video Diffusion: From Foundations to Open Frontiers

arXiv:2605.17248v1 Announce Type: new Abstract: Diffusion-based extit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional c

Imaging Hidden Objects with Consumer LiDAR via Motion Induced Sampling

arXiv:2605.17865v1 Announce Type: new Abstract: LiDARs are being increasingly deployed for consumer imaging in handheld, wearable, and robotic applications. These sensors can capture the time-of-fligh

iMiGUE-3K: A Large-Scale Benchmark for Micro-Gesture Analysis with Self-Supervised Learning

model-releasesarxiv-cs-cv

arXiv:2605.17179v1 Announce Type: new Abstract: Emotion understanding is a fundamental challenge in affective computing and artificial intelligence. While existing approaches predominantly focus on fa

Implicit Hierarchical GRPO: Decoupling Tool Invocation from Execution for Tool-Integrated Mathematical Reasoning

arXiv:2605.18500v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly leveraged tool invocation to enhance their reasoning capabilities. However, existing approaches typically

safetyarxiv-cs-cl

Improved Baselines with Representation Autoencoders

arXiv:2605.18324v1 Announce Type: cross Abstract: Representation Autoencoders (RAE) replace traditional VAE with pretrained vision encoders. In this paper, we systematically investigate several design

Improving BM25 Code Retrieval Under Fixed Generic Tokenization: Adaptive q-Log Odds as a Drop-In BM25 Fix

arXiv:2605.18561v1 Announce Type: cross Abstract: In retrieval-augmented coding, failures often begin when the relevant file is absent from the retrieved context. Under frozen generic tokenization, wh

Improving MLLM Training Efficiency via Stage-Aware Sparsity

arXiv:2509.18150v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated outstanding performance across a variety of domains. However, training MLLMs is oft

Improving Random Forests by Smoothing

arXiv:2505.06852v2 Announce Type: replace Abstract: Random forest regression is a powerful non-parametric method that adapts to local data characteristics through data-driven partitioning, making it e

local-aiarxiv-cs-lg

Improving Spatio-Temporal Residual Error Propagation by Mitigating Over-Squashing

arXiv:2605.18068v1 Announce Type: cross Abstract: Residual error propagation remains a fundamental problem in recurrent models, where small prediction inaccuracies compound over time and degrade long-

applicationsarxiv-cs-ai

In-context learning enables continental-scale subsurface temperature prediction from sparse local observations

arXiv:2605.16665v1 Announce Type: new Abstract: Continental-scale knowledge of subsurface temperature is limited by the cost and sparsity of borehole measurements, but such information is essential fo

local-aiarxiv-cs-lg

Incantation: Natural Language as the Action Interface for Multi-Entity Video World Models

model-releasesarxiv-cs-cv

arXiv:2605.18601v1 Announce Type: new Abstract: Modern interactive video world models have achieved impressive visual fidelity, yet lack fine-grained multi-entity control and cross-entity, cross-world

Incentive-Aware Federated Averaging with Performance Guarantees under Strategic Participation

arXiv:2603.20873v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient collaborative learning framework that enables model training across multiple agents with privat

local-aiarxiv-cs-lg

Individual utilities of life satisfaction reveal inequality aversion unrelated to political alignment

arXiv:2509.07793v4 Announce Type: replace-cross Abstract: How should well-being be prioritised in society, and what trade-offs are people willing to make between fairness and personal well-being? We i

Inducing Spatial Locality in Vision Transformers through the Training Protocol

arXiv:2605.16390v1 Announce Type: new Abstract: We investigate whether the training protocol can induce spatial locality in the early layers of a Vision Transformer (ViT) trained from scratch, without

InFeR: Informed Failure Resilience in Learned Visual Navigation Control

arXiv:2510.24680v2 Announce Type: replace Abstract: While imitation learning (IL) has enabled successful visual navigation in many common environments, IL policies are prone to unpredictable failures

safetyarxiv-cs-ro

Inference-Time Diversity in RL-Trained Lean Theorem Provers: A Diagnostic Study

arXiv:2601.16172v2 Announce Type: replace Abstract: RL-trained Lean theorem provers mode-collapse at inference time: on miniF2F-test with DeepSeek-Prover-V1.5-RL, doubling the i.i.d. sampling budget f

Infini-News: Efficiently Queryable Access to 1.3 Billion Processed Common Crawl News Articles

arXiv:2605.18337v1 Announce Type: new Abstract: Large-scale news corpora support a wide range of research in Computational Social Science and NLP, yet access remains constrained: commercial archives i

researcharxiv-cs-cl

InfoFlow: A Framework for Multi-Layer Transformer Analysis

model-releasesarxiv-cs-lg

arXiv:2605.17930v1 Announce Type: new Abstract: While the approximation properties of single-layer Transformer architectures have been studied in recent works, a rigorous theoretical understanding of

Information-Theoretic Storage Cost in Sentence Comprehension

arXiv:2602.18217v2 Announce Type: replace Abstract: Real-time sentence comprehension imposes a significant load on working memory, as comprehenders must maintain contextual information to anticipate f

researcharxiv-cs-cl

Informative Graph Structure Learning

arXiv:2605.16809v1 Announce Type: new Abstract: The quality of graph-structured data is fundamental to the success of modern graph analysis techniques such as Graph Neural Networks (GNNs). However, re

applicationsarxiv-cs-lg

InstructAV2AV: Instruction-Guided Audio-Video Joint Editing

arXiv:2605.18467v1 Announce Type: new Abstract: Recent diffusion-based methods have achieved impressive progress in video content manipulation. However, they typically ignore the accompanying audio, l

Integration of AI in Cybersecurity: Current Trends with a Focused Look at Intrusion Detection Applications

arXiv:2605.17219v1 Announce Type: cross Abstract: Artificial Intelligence (AI) is widely adopted today for its ability to detect patterns, automate tasks, and reduce time and cost across various appli

researcharxiv-cs-ai

Inter-LPCM: Learning-based Inter-Frame Predictive Coding for LiDAR Point Cloud Compression

arXiv:2605.18006v1 Announce Type: cross Abstract: Because LiDAR sensors acquire point clouds with a fixed angular resolution, the resulting data can be systematically parameterized and efficiently com

Agents

Interaction-Breaking Adversarial Learning Framework for Robust Multi-Agent Reinforcement Learning

arXiv:2605.18024v1 Announce Type: cross Abstract: Cooperation is central to multi-agent reinforcement learning (MARL), yet learned coordination can be fragile when external perturbations disrupt inter

agentsarxiv-cs-ai

Agents

Interactive Evaluation Requires a Design Science

arXiv:2605.17829v1 Announce Type: new Abstract: AI evaluation is undergoing a structural change. Large language models (LLMs) are increasingly deployed as systems that act over time through tools, env

agentsarxiv-cs-ai

Internalizing Tool Knowledge in Small Language Models via QLoRA Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2605.17774v1 Announce Type: new Abstract: Large language models are increasingly used as planning components in agentic systems, but current tool-use pipelines often require full tool schemas to

Interpretable epistemic uncertainty decomposition in sequential generative models via polynomial chaos surrogates

arXiv:2510.21523v2 Announce Type: replace Abstract: Sequential generative models conditioned on uncertain rewards are central to AI-driven scientific discovery, yet the epistemic uncertainty they inhe

safetyarxiv-cs-lg

Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025

model-releasesarxiv-cs-cv

arXiv:2305.07152v4 Announce Type: replace Abstract: Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machin

Tutorials

InvDesFlow-AL: active learning-based workflow for inverse design of functional materials

arXiv:2505.09203v2 Announce Type: replace-cross Abstract: Developing inverse design methods for functional materials with specific properties is critical to advancing fields like renewable energy, cat

tutorialsarxiv-cs-ai