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Heuristic Pathologies and Further Variance Reduction via Uncertainty Propagation in the AIVAT Family of Techniques

arXiv:2605.14261v1 Announce Type: new Abstract: How should an agent's performance in a multiagent environment be evaluated when there is a limited sample size or a high cost of running a trial? The AI

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Model Releases

Hidden State Poisoning Attacks against Mamba-based Language Models

DGX agent

arXiv:2601.01972v4 Announce Type: cross Abstract: State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language models, with linear time complexity. Yet, their advers

model-releasesarxiv-cs-ai

15 May 2026

Hierarchical Image Tokenization for Multi-Scale Image Super Resolution

arXiv:2605.14891v1 Announce Type: new Abstract: We introduce a multi-scale Image Super Resolution (ISR) method building on recent advances in Visual Auto-Regressive (VAR) modeling. VAR models break im

safetyarxiv-cs-cv

HiSem: Hierarchical Semantic Disentangling for Remote Sensing Image Change Captioning

model-releasesarxiv-cs-cv

arXiv:2605.15024v1 Announce Type: new Abstract: Remote sensing image change captioning (RSICC) aims to achieve high-level semantic understanding of genuine changes occurring between bi-temporal images

HodgeCover: Higher-Order Topological Coverage Drives Compression of Sparse Mixture-of-Experts

arXiv:2605.13997v1 Announce Type: cross Abstract: Sparse Mixture-of-Experts (MoE) layers route tokens through a handful of experts, and learning-free compression of these layers reduces inference cost

Holistic Evaluation and Failure Diagnosis of AI Agents

arXiv:2605.14865v1 Announce Type: new Abstract: AI agents execute complex multi-step processes, but current evaluation falls short: outcome metrics report success or failure without explaining why, an

How Sensitive Are Radiomic AI Models to Acquisition Parameters?

arXiv:2605.14667v1 Announce Type: new Abstract: A main barrier for the deployment of AI radiomic systems in clinical routine is their drop in performance under heterogeneous multicentre acquisition pr

Tutorials

How to Evaluate and Refine your CAM

arXiv:2605.14641v1 Announce Type: cross Abstract: Class attribution maps (CAMs) provide local explanations for the decisions of convolutional neural networks. While widely used in practice, the evalua

tutorialsarxiv-cs-ai

Tutorials

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization

arXiv:2605.14200v1 Announce Type: new Abstract: Recent frontier large language models predominantly rely on Mixture-of-Experts (MoE) architectures. Despite empirical progress, there is still no princi

tutorialsarxiv-cs-lg

How well behaved is finite dimensional Diffusion Maps?

arXiv:2412.03992v3 Announce Type: replace-cross Abstract: Under a set of assumptions on a family of submanifolds subset {mathbb R}^D, we derive a series of geometric properties that remain valid after

researcharxiv-cs-lg

Hyperbolic Graph Neural Networks Under the Microscope: The Role of Geometry-Task Alignment

arXiv:2602.01828v2 Announce Type: replace Abstract: Many complex networks exhibit hierarchical, tree-like structures, making hyperbolic space a natural candidate wherein to learn representations of th

safetyarxiv-cs-lg

Hypergraph Enterprise Agentic Reasoner over Heterogeneous Business Systems

arXiv:2605.14259v1 Announce Type: new Abstract: Applying Large Language Models (LLMs) to heterogeneous enterprise systems is hindered by hallucinations and failures in multi-hop, n-ary reasoning. Exis

Hyperspectral Image Land Cover Captioning Dataset for Vision Language Models

model-releasesarxiv-cs-cv

arXiv:2505.12217v2 Announce Type: replace Abstract: We introduce HyperCap, the first large-scale hyperspectral captioning dataset designed to enhance model performance and effectiveness in remote sens

ICED: Concept-level Machine Unlearning via Interpretable Concept Decomposition

arXiv:2605.14309v1 Announce Type: cross Abstract: Machine unlearning in Vision-Language Models (VLMs) is typically performed at the image or instance level, making it difficult to precisely remove tar

safetyarxiv-cs-ai

Identifying Culprits Through Deep Deterministic Policy Gradient Deep Learning Investigation

arXiv:2605.14774v1 Announce Type: new Abstract: In the world of AI and advanced technologies investigation aspects identification of a crime or criminal plays a major problem. In this research we focu

safetyarxiv-cs-ai

Ideology Prediction of German Political Texts

arXiv:2605.14352v1 Announce Type: new Abstract: Elections represent a crucial milestone in a nation's ongoing development. To better understand the political rhetoric from various movements, ranging f

safetyarxiv-cs-cl

IFPV: An Integrated Multi-Agent Framework for Generative Operational Planning and High-Fidelity Plan Verification

arXiv:2605.14851v1 Announce Type: cross Abstract: Operational plan generation and verification are critical for modern complex and rapidly changing battlefield environments, yet traditional generation

Tutorials

IG-Diff: Complex Night Scene Restoration with Illumination-Guided Diffusion Model

arXiv:2605.14337v1 Announce Type: new Abstract: In nighttime circumstances, it is challenging for individuals and machines to perceive their surroundings. While prevailing image restoration methods ad

tutorialsarxiv-cs-cv

Image Restoration via Diffusion Models with Dynamic Resolution

arXiv:2605.14267v1 Announce Type: cross Abstract: Diffusion models (DMs) have exhibited remarkable efficacy in various image restoration tasks. However, existing approaches typically operate within th

Applications

ImmuVis: Hyperconvolutional Foundation Model for Imaging Mass Cytometry

arXiv:2602.04585v2 Announce Type: replace Abstract: We present ImmuVis, a family of efficient foundation models for imaging mass cytometry (IMC), a high-throughput multiplex imaging technology that ha

applicationsarxiv-cs-cv

Implicit spatial-frequency fusion of hyperspectral and lidar data via kolmogorov-arnold networks

arXiv:2605.14239v1 Announce Type: new Abstract: Hyperspectral image (HSI) classification is challenging in complex scenes due to spectral ambiguity, spatial heterogeneity, and the strong coupling betw

Improving Multi-turn Dialogue Consistency with Self-Recall Thinking

arXiv:2605.15102v1 Announce Type: cross Abstract: Large language model (LLM) based multi-turn dialogue systems often struggle to track dependencies across non-adjacent turns, undermining both consiste

In-Context Learning for Data-Driven Censored Inventory Control

arXiv:2605.14840v1 Announce Type: new Abstract: We study inventory control with decision-dependent censoring, focusing on the censored or repeated newsvendor (R-NV), where each order quantity determin

In-IDE Toolkit for Developers of AI-Based Features

arXiv:2605.14612v1 Announce Type: cross Abstract: AI-enabled features built on LLMs and agentic workflows are difficult to test, debug, and reproduce, especially for product-focused software engineers

Indian Wedding System Optimization (IWSO): A Novel Socially Inspired Metaheuristic with Operational Design and Analysis

arXiv:2605.13871v1 Announce Type: cross Abstract: This paper presents a novel population-based metaheuristic, Indian Wedding System Optimization (IWSO), inspired by the socio-cultural dynamics of trad

InfoSFT: Learn More and Forget Less with Information-Aware Token Weighting

arXiv:2605.14967v1 Announce Type: new Abstract: Supervised fine-tuning (SFT) provides the standard approach for teaching LLMs new behaviors from offline expert demonstrations. However, standard SFT un

safetyarxiv-cs-lg

InsightTok: Improving Text and Face Fidelity in Discrete Tokenization for Autoregressive Image Generation

arXiv:2605.14333v1 Announce Type: new Abstract: Text and faces are among the most perceptually salient and practically important patterns in visual generation, yet they remain challenging for autoregr

Intelligence Impact Quotient (IIQ): A Framework for Measuring Organizational AI Impact

arXiv:2605.14455v1 Announce Type: new Abstract: The Intelligence Impact Quotient (IIQ) is a composite metric intended to quantify the depth to which AI systems are integrated into organizational work

IntentVLA: Short-Horizon Intent Modeling for Aliased Robot Manipulation

arXiv:2605.14712v1 Announce Type: cross Abstract: Robot imitation data are often multimodal: similar visual-language observations may be followed by different action chunks because human demonstrators

Interestingness as an Inductive Heuristic for Future Compression Progress

arXiv:2605.14831v1 Announce Type: new Abstract: One of the bottlenecks on the way towards recursively self-improving systems is the challenge of interestingness: the ability to prospectively identify

Invisible Orchestrators Suppress Protective Behavior and Dissociate Power-Holders: Safety Risks in Multi-Agent LLM Systems

arXiv:2605.13851v1 Announce Type: new Abstract: Multi-agent orchestration -- in which a hidden coordinator manages specialized worker agents -- is becoming the default architecture for enterprise AI d

IPR-1: Interactive Physical Reasoner

arXiv:2511.15407v3 Announce Type: replace Abstract: Humans learn by observing, interacting with environments, and internalizing physics and causality. Here, we aim to ask whether an agent can similarl

Is Grep All You Need? How Agent Harnesses Reshape Agentic Search

model-releasesarxiv-cs-cl

arXiv:2605.15184v1 Announce Type: new Abstract: Recent advances in Large Language Model (LLM) agents have enabled complex agentic workflows where models autonomously retrieve information, call tools,

Iskra: A System for Inverse Geometry Processing

arXiv:2602.12105v2 Announce Type: replace-cross Abstract: We propose a system for differentiating through solutions to geometry processing problems. Our system differentiates a broad class of geometri

IsoNet: Spatially-aware audio-visual target speech extraction in complex acoustic environments

arXiv:2605.14736v1 Announce Type: cross Abstract: Target speech extraction remains difficult for compact devices because monaural neural models lack spatial evidence and classical beamformers lose res

researcharxiv-cs-lg

It Takes Two: Your GRPO Is Secretly DPO

arXiv:2510.00977v3 Announce Type: replace-cross Abstract: GRPO has emerged as a prominent reinforcement learning algorithm for post-training LLMs. Unlike critic-based methods, GRPO computes advantages

researcharxiv-cs-cl

JointAVBench: A Benchmark for Joint Audio-Visual Reasoning Evaluation

model-releasesarxiv-cs-cv

arXiv:2512.12772v2 Announce Type: replace-cross Abstract: Understanding videos inherently requires reasoning over both visual and auditory information. To properly evaluate Omni-Large Language Models

K-Models: a Flexible and Interpretable Method for Ordinal Clustering with Application to Antigen-Antibody Interaction Profiles

arXiv:2605.14828v1 Announce Type: cross Abstract: Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaning

Kairos: Toward Adaptive and Parameter-Efficient Time Series Foundation Models

arXiv:2509.25826v3 Announce Type: replace Abstract: Inherent temporal heterogeneity, such as varying sampling densities and periodic structures, has posed substantial challenges in zero-shot generaliz

Keyed Nonlinear Transform: Lightweight Privacy-Enhancing Feature Sharing for Medical Image Analysis

arXiv:2605.14123v1 Announce Type: cross Abstract: Feature sharing via split inference offers a lightweight alternative to federated learning for resource-constrained hospitals, but transmitted feature

Local Ai

KGPFN: Unlocking the Potential of Knowledge Graph Foundation Model via In-Context Learning

arXiv:2605.14907v1 Announce Type: new Abstract: Knowledge graph (KG) foundation models aim to generalize across graphs with unseen entities and relations by learning transferable relational structure.

local-aiarxiv-cs-ai

Know When To Fold 'Em: Token-Efficient LLM Synthetic Data Generation via Multi-Stage In-Flight Rejection

arXiv:2605.14062v1 Announce Type: new Abstract: While synthetic data generation with large language models (LLMs) is widely used in post-training pipelines, existing approaches typically generate full

safetyarxiv-cs-ai

Knowledge Beyond Language: Bridging the Gap in Multilingual Machine Unlearning Evaluation

arXiv:2605.14404v1 Announce Type: new Abstract: While LLMs are increasingly used in commercial services, they pose privacy risks such as leakage of sensitive personally identifiable information (PII).

researcharxiv-cs-cl

Known By Their Actions: Fingerprinting LLM Browser Agents via UI Traces

arXiv:2605.14786v1 Announce Type: cross Abstract: As LLM-based agents increasingly browse the web on users' behalf, a natural question arises: can websites passively identify which underlying model po

Kolmogorov-Arnold Chemical Reaction Neural Networks for learning pressure-dependent kinetic rate laws

arXiv:2511.07686v2 Announce Type: replace-cross Abstract: Chemical Reaction Neural Networks (CRNNs) have emerged as an interpretable machine learning framework for discovering reaction kinetics direct

Krause Synchronization Transformers

arXiv:2602.11534v3 Announce Type: replace-cross Abstract: Self-attention in Transformers relies on globally normalized softmax weights, causing all tokens to compete for influence at every layer. When

KVPO: ODE-Native GRPO for Autoregressive Video Alignment via KV Semantic Exploration

arXiv:2605.14278v1 Announce Type: new Abstract: Aligning streaming autoregressive (AR) video generators with human preferences is challenging. Existing reinforcement learning methods predominantly rel

safetyarxiv-cs-cv

L2R: Low-Rank and Lipschitz-Controlled Routing for Mixture-of-Experts

arXiv:2601.21349v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models scale neural networks by conditionally activating a small subset of experts, where the router plays a central