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From Guessing to Placeholding: A Cost-Theoretic Framework for Uncertainty-Aware Code Completion

arXiv:2604.01849v2 Announce Type: replace Abstract: While Large Language Models (LLMs) have demonstrated exceptional proficiency in code completion, they typically adhere to a Hard Completion (HC) par

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From Hallucination to Grounding: Diagnosing Visual Spatial Intelligence via CRISP

DGX agent

arXiv:2606.26535v1 Announce Type: cross Abstract: Current VLM evaluations often conflate language priors with genuine spatial reasoning. To address this, we introduce CRISP, a novel structural-diagnos

safetyarxiv-cs-ai

26 Jun 2026

From Lexicon to AI: A Structured-Data Pipeline for Specialized Conversational Systems in Low-Resource Languages

arXiv:2606.26112v1 Announce Type: cross Abstract: Low-resource languages face a critical challenge in AI development: creating specialized conversational systems without access to massive training cor

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models

arXiv:2606.26196v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have recently made remarkable progress in unifying vision-language understanding and reasoning, especially fo

From Vajrayana Tara to Bengali Baul: A Computational Study of Lexical Transmission Across Buddhist, Shakta, and Vaishnava Traditions in Bengal

arXiv:2606.26803v1 Announce Type: new Abstract: We present a computational corpus study of vocabulary relationships across eight tradition layers of Bengali and Sanskrit devotional literature spanning

researcharxiv-cs-cl

From Weights to Features: SAE-Guided Activation Regularization for LLM Continual Learning

arXiv:2606.26629v1 Announce Type: cross Abstract: Weight-space regularization methods such as Elastic Weight Consolidation (EWC) are the standard approach to catastrophic forgetting in continual learn

fTNN: a tensor neural network for fractional PDEs

arXiv:2606.27140v1 Announce Type: new Abstract: We develop the fTNN, a deterministic tensor neural network subspace method for problems involving the fractional Laplacian on bounded domains, taking th

Full spectrum Unlearnable Examples via Spectral Equalization

arXiv:2606.26719v1 Announce Type: new Abstract: Unlearnable examples (UEs) protect training data by injecting imperceptible perturbations so that models fail to extract exploitable representations. In

researcharxiv-cs-cv

GAVEL: Grounded Caption Error Verification and Localization

arXiv:2606.26923v1 Announce Type: new Abstract: Vision-language models (VLMs) often produce hallucinated or inconsistent outputs, where text and images are not properly aligned. Addressing this issue

GeMoE: Gating Entropy is All You Need for Uncertainty-aware Adaptive Routing in MoE-based Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2606.26287v1 Announce Type: new Abstract: With the increase in model parameters and training data, the instruction following and generalization capabilities of Large VisionLanguage Models (LVLMs

Tutorials

Generating a Paracosm for Training-Free Zero-Shot Composed Image Retrieval

arXiv:2602.00813v5 Announce Type: replace Abstract: Composed Image Retrieval (CIR) is the task of retrieving a target image from a database using a multimodal query, which consists of a reference imag

tutorialsarxiv-cs-cv

Generating Special Triangulations with Transformers

arXiv:2606.26660v1 Announce Type: cross Abstract: Triangulations, i.e., well-structured decompositions of geometric objects into triangle-like pieces, are central objects in many domains of mathematic

Generative AI and Copyright Infringement: A Legal-Technical Analysis of AI Music Generation Systems Under 17 U.S.C. Title 17

arXiv:2606.26111v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) has enabled users to synthesize music with text prompts, combining copyrighted lyrics, AI-composed melodies

Generative Models on Analog Hardware with Dynamics

arXiv:2606.27294v1 Announce Type: cross Abstract: Analog hardware platforms such as coupled oscillators and Analog Ising Machines naturally solve differential equations at a fraction of the energy cos

Generative Retrieval via Diffusion Transformer with Metric-Ordered Sequence Training and Hybrid-Policy Preference Optimization

arXiv:2606.26899v1 Announce Type: new Abstract: Embedding-based retrieval ranks items by their similarity to a query in a shared vector space and usually aims to return the highest-scoring items. In m

Applications

GenRecal: Generation after Recalibration from Large to Small Vision-Language Models

arXiv:2506.15681v4 Announce Type: replace Abstract: Recent advancements in vision-language models (VLMs) have leveraged large language models (LLMs) to achieve performance on par with closed-source sy

applicationsarxiv-cs-cl

GEOALIGN: Geometric Rollout Curation for Robust LLM Reinforcement Learning

arXiv:2606.26917v1 Announce Type: cross Abstract: Online reinforcement learning is widely used to align large language models (LLMs) with reward signals, yet training can be unstable under noisy or mi

Geometric Fairness-Aware Routing for Federated Edge Networks

arXiv:2606.26125v1 Announce Type: cross Abstract: Emerging 6G and edge-intelligent networks require effective and balanced routing algorithms among varied and spatially distributed devices. Existing f

Geometric Gradient Rectification for Safe Open-Set Semi-Supervised Learning

arXiv:2606.26973v1 Announce Type: new Abstract: Open-set semi-supervised learning aims to leverage unlabeled data that may contain out-of-distribution outliers while maintaining performance on in-dist

researcharxiv-cs-cv

Geometry-Aware MCTS for Extremal Problems in Combinatorial Geometry

arXiv:2606.26399v1 Announce Type: new Abstract: We study certain extremal problems in combinatorial geometry that ask about configurations of points in an n imes n grid that satisfy strict, global geo

researcharxiv-cs-ai

Geometry-Aware Superpixel Graph Transformer with Metadata for Skin Lesion Classification

arXiv:2606.20390v2 Announce Type: replace Abstract: Automated skin cancer classification from dermoscopic images remains challenging due to heterogeneous lesion structure, strong intra-class variabili

researcharxiv-cs-cv

Governing Actions, Not Agents: Institutional Attestation as a Governance Model for Autonomous AI Systems

arXiv:2606.26298v1 Announce Type: new Abstract: Autonomous AI agents may begin to perform consequential, irreversible actions such as clinical prescribing and production software deployment. This pape

Gradient Testing and Estimation by Comparisons

arXiv:2405.11454v3 Announce Type: replace Abstract: We study gradient testing and gradient estimation of smooth functions using only a comparison oracle that, given two points, indicates which one has

Graph Neural Networks Applications Across Domains: All Insights You Need

arXiv:2606.27202v1 Announce Type: new Abstract: Graph neural networks have moved from a niche representation-learning technique to the default model class wherever data carry relational structure. The

safetyarxiv-cs-lg

Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing

arXiv:2606.12816v3 Announce Type: replace-cross Abstract: Quantum circuit routing is a key step in compiling programs for noisy intermediate-scale quantum processors. Routes that appear efficient by s

safetyarxiv-cs-lg

Hallucination in World Models is Predictable and Preventable

model-releasesarxiv-cs-cv

arXiv:2606.27326v1 Announce Type: cross Abstract: Modern generative world models render increasingly realistic action-controllable futures, yet they frequently hallucinate: rollouts remain visually fl

Hardware Design for Table Tennis Robot Capable of Beating Professional Players

arXiv:2606.26643v1 Announce Type: new Abstract: This paper focuses on the hardware specifications required for a table tennis robot to beat professional players. After analyzing the motions of elite p

safetyarxiv-cs-ro

HarmVideoBench: Benchmarking Harmful Video Understanding in Large Multimodal Models

arXiv:2606.27187v1 Announce Type: cross Abstract: Large vision-language models (LVLMs) have recently shown immense potential in automated content moderation, sparking growing interest in developing ha

HauntAttack: When Attack Follows Reasoning as a Shadow

arXiv:2506.07031v5 Announce Type: replace-cross Abstract: Emerging Large Reasoning Models (LRMs) consistently excel in mathematical and reasoning tasks, showcasing remarkable capabilities. However, th

Heavy-Ball Q-Learning with Residual Weighting Correction

arXiv:2606.27112v1 Announce Type: cross Abstract: This paper proposes a corrected heavy-ball Q-learning method for reinforcement learning (RL) and establishes its convergence. It also identifies condi

researcharxiv-cs-ai

Helpfulness Hurts: Domain-Dependent Degradation of Mid-Trained Compassion Values Under Post-Training

arXiv:2606.26102v1 Announce Type: cross Abstract: Standard post-training pipelines apply supervised fine-tuning (SFT) and reinforcement learning (RL) to make language models helpful, but these process

Local Ai

Heterogeneous Neural Predictivity from Language Models During Naturalistic Comprehension

arXiv:2606.26880v1 Announce Type: new Abstract: Language-model representations provide structured, high-dimensional annotations of naturalistic language stimuli and can serve as informative neural pre

local-aiarxiv-cs-cl

Hardware

Hierarchical Muon: Tiled Newton-Schulz Updates for Efficient Muon Optimization

arXiv:2606.27216v1 Announce Type: cross Abstract: Muon-type optimizers construct update directions for dense neural-network weights by applying a finite Newton-Schulz map to momentum-gradient matrices

hardwarearxiv-cs-lg

HierBias: Context-Conditioned Hierarchical Media Bias Detection with Multi-Task Type Classification

arXiv:2606.26100v1 Announce Type: new Abstract: Media bias detection is a critical task for ensuring fair and balanced information dissemination, yet existing sentence-level approaches classify each s

safetyarxiv-cs-cl

High-Probability PL-SGD with Markovian Noise: Optimal Mixing and Tail Dependence

arXiv:2606.26316v1 Announce Type: new Abstract: We study first-order methods for smooth objectives satisfying the Polyak-L{}ojasiewicz (PL) condition when gradient samples are generated by an exogenou

safetyarxiv-cs-lg

Agents

HiLSVA: Design and Evaluation of a Human-in-the-Loop Agentic System for Scientific Visualization

arXiv:2606.26614v1 Announce Type: cross Abstract: Large language model (LLM) agents enable natural language interaction for scientific visualization (SciVis). Still, prior systems have essentially pri

agentsarxiv-cs-ai

hisao{}: A GPU-Native Parallel Optimizer for Multimodal Black-Box Functions via Convergence-Anticonvergence Oscillation

model-releasesarxiv-cs-lg

arXiv:2606.26164v1 Announce Type: new Abstract: Finding all modes of a multimodal black-box function is a fundamental challenge in optimization, Bayesian inference, and scientific computing. Existing

Applications

History-Conditioned Spatio-Temporal Visual Token Pruning for Efficient Vision-Language Navigation

arXiv:2603.06480v2 Announce Type: replace Abstract: Vision-Language Navigation (VLN) enables robots to follow natural-language instructions in visually grounded environments, serving as a key capabili

applicationsarxiv-cs-ro

HOB: A Holistically Optimized Bidding Strategy under Heterogeneous Bidding Environments

model-releasesarxiv-cs-lg

arXiv:2510.15238v2 Announce Type: replace-cross Abstract: Optimizing a single advertising campaign across heterogeneous channels is a central challenge in industrial autobidding. Auction mechanisms va

How Do Tool-Augmented LLM Agents Perform on Real-World Energy Analytics Tasks?

arXiv:2606.26346v1 Announce Type: new Abstract: Agentic benchmarks have emerged across general-purpose and domain-specific settings, including finance, coding, law, and drug discovery, yet energy-doma

How Good Can Linear Models Be for Time-Series Forecasting?

arXiv:2606.27282v1 Announce Type: new Abstract: Time-series forecasting research has been moving steadily toward larger architectures, from specialized transformers to general-purpose foundation model

Applications

How Surprising Is Historical Italian to Language Models? Tokenization Tax, Comprehension Tax, and a Simple Mitigation

arXiv:2606.27275v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly critical to digital library workflows, yet their ability to process historical language remains poorly und

applicationsarxiv-cs-cl

Tutorials

How to evaluate clustering with ground truth?

arXiv:2606.27061v1 Announce Type: new Abstract: External indexes can be used for cluster evaluation when ground truth is available. We review the most common external validity indexes focusing on set-

tutorialsarxiv-cs-ai

Human-AI Complementarity: A Goal for Amplified Oversight

arXiv:2510.26518v2 Announce Type: replace Abstract: Human feedback is critical for aligning AI systems to human values. As AI capabilities improve and AI is used to tackle more challenging tasks, veri

Humanoid-DART: Humanoid Loco-Manipulation using Diffusion-guided Augmentation through Relabeling and Tracking

arXiv:2606.26855v1 Announce Type: new Abstract: Imitating human demonstrations has emerged as a dominant paradigm for learning humanoid loco-manipulation policies. However, scaling these approaches re

safetyarxiv-cs-ro

HumanoidUMI: Bridging Robot-Free Demonstrations and Humanoid Whole-Body Manipulation

arXiv:2606.27239v1 Announce Type: new Abstract: High-quality demonstration data are essential for humanoid robot skill learning, especially for whole-body behaviors that require coordinated perception

safetyarxiv-cs-ro

Humans Disengage, Reasoning Models Persist: Separating Difficulty Registration from Deliberation Allocation

arXiv:2606.26502v1 Announce Type: new Abstract: Large reasoning models (LRMs) take longer on harder problems, just as humans do. This surface similarity hides an opposite pattern within items. When an

Huracan: A skillful end-to-end data-driven system for ensemble data assimilation and weather prediction

arXiv:2508.18486v2 Announce Type: replace-cross Abstract: Over the past few years, machine learning-based data-driven weather prediction has been transforming operational weather forecasting by provid