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HTPO: Towards Exploration-Exploitation Balanced Policy Optimization via Hierarchical Token-level Objective Control

arXiv:2605.08283v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a pivotal technique for enhancing the reasoning capabilities of Large Language Mo

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HULK: Large-scale Hierarchical Coordination under Continual and Uncertain Temporal Tasks

DGX agent

arXiv:2605.08722v1 Announce Type: new Abstract: Multi-agent systems can be extremely efficient when working concurrently and collaboratively, e.g., for delivery, surveillance, search and rescue. Coord

agentsarxiv-cs-ro

12 May 2026

Human-Inspired Memory Architecture for LLM Agents

arXiv:2605.08538v1 Announce Type: new Abstract: Current LLM agents lack principled mechanisms for managing persistent memory across long interaction horizons. We present a biologically-grounded memory

Human-LLM Dialogue Improves Diagnostic Accuracy in Emergency Care

arXiv:2605.08533v1 Announce Type: new Abstract: Clinical decision-making in emergency medicine demands rapid, accurate diagnoses under uncertainty. Despite benchmark progress, evidence for LLMs as int

Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generation

model-releasesarxiv-cs-cv

arXiv:2501.12202v4 Announce Type: replace Abstract: We present Hunyuan3D 2.0, an advanced large-scale 3D synthesis system for generating high-resolution textured 3D assets. This system includes two fo

HY-Himmel Technical Report: Hierarchical Interleaved Multi-stream Motion Encoding for Long Video Understanding

arXiv:2605.08158v1 Announce Type: cross Abstract: Long-video understanding with multimodal language models suffers from three compounding bottlenecks: heavy decode cost to obtain dense RGB frames, qua

Local Ai

HyDRA Scorpion: A Cost-effective and Modular ROV for Real-Time Underwater Inspection, Intervention, and Object Detection

arXiv:2605.09093v1 Announce Type: new Abstract: A Remotely Operated Vehicle (ROV) is a tethered underwater robot used for tasks like inspection and intervention. While essential tools for underwater s

local-aiarxiv-cs-ro

HyNeuralMap: Hyperbolic Mapping of Visual Semantics to Neural Hierarchies

arXiv:2605.09392v1 Announce Type: new Abstract: Understanding the intricate mappings between visual stimuli and neural responses is a fundamental challenge in cognitive neuroscience. While current app

safetyarxiv-cs-cv

HyPER: Bridging Exploration and Exploitation for Scalable LLM Reasoning with Hypothesis Path Expansion and Reduction

arXiv:2602.06527v2 Announce Type: replace Abstract: Scaling test-time compute with multi-path chain-of-thought improves reasoning accuracy, but its effectiveness depends critically on the exploration-

Hyperbolic Distillation: Geometry-Guided Cross-Modal Transfer for Robust 3D Object Detection

arXiv:2605.09899v1 Announce Type: cross Abstract: Cross-modal knowledge distillation has emerged as an effective strategy for integrating point cloud and image features in 3D perception tasks. However

Hypergraph-Enhanced Training-Free and Language-Free Few-Shot Anomaly Detection

arXiv:2605.10628v1 Announce Type: new Abstract: Few-shot anomaly detection (FSAD) has made significant strides, yet existing methods still face critical challenges: (i) dependence on task- or dataset-

Hyperparameter Transfer for Dense Associative Memories

arXiv:2605.10164v1 Announce Type: new Abstract: Dense Associative Memory (DenseAM) is a promising family of AI architectures that is represented by a neural network performing temporal dynamics on an

HYPERPOSE: Hyperbolic Kinematic Phase-Space Attention for 3D Human Pose Estimation

arXiv:2605.10100v1 Announce Type: cross Abstract: We introduce HYPERPOSE, a novel 3D human pose estimation framework that performs spatio-temporal reasoning entirely within the Lorentz model of hyperb

HyperSpace: A Generalized Framework for Spatial Encoding in Hyperdimensional Representations

arXiv:2604.15113v2 Announce Type: replace Abstract: Vector Symbolic Architectures (VSAs) provide a well-defined algebraic framework for compositional representations in hyperdimensional spaces. We int

Hyperspherical Autoencoder for High-Fidelity Image Reconstruction and Generation

arXiv:2601.22904v2 Announce Type: replace-cross Abstract: Recent studies have explored using pretrained Vision Foundation Models (VFMs) such as DINO for generative autoencoders, showing strong generat

HyperTransport: Amortized Conditioning of T2I Generative Models

arXiv:2605.08254v1 Announce Type: cross Abstract: As foundation models grow in capability, the ability to efficiently and reliably control their behavior becomes critical. Fine-tuning these models can

Hypothesis-Driven Deep Research with Large Language Models: A Structured Methodology for Automated Knowledge Discovery

arXiv:2605.10224v1 Announce Type: new Abstract: Current AI-powered research systems adopt a direct search-then-summarize paradigm that treats hypotheses as end products of scientific discovery. We arg

Hystar: Hypernetwork-driven Style-adaptive Retrieval via Dynamic SVD Modulation

model-releasesarxiv-cs-cv

arXiv:2605.10009v1 Announce Type: new Abstract: Query-based image retrieval (QBIR) requires retrieving relevant images given diverse and often stylistically heterogeneous queries, such as sketches, ar

ICT-NLP at SemEval-2026 Task 3: Less Is More -- Multilingual Encoder with Joint Training and Adaptive Ensemble for Dimensional Aspect Sentiment Regression

arXiv:2605.10560v1 Announce Type: new Abstract: This paper describes our system to SemEval-2026 Task 3 Track A Subtask 1 on Dimensional Aspect Sentiment Regression (DimASR). We propose a lightweight a

researcharxiv-cs-cl

Identified-Set Geometry of Distributional Model Extraction under Top-K Censored API Access

arXiv:2605.10407v1 Announce Type: new Abstract: Modern LLM APIs often reveal only top-K logit scores and censor the remaining vocabulary. We study the per-position distribution-recovery limits of this

Identifying Backdoored Graphs in Graph Neural Network Training: An Explanation-Based Approach with Novel Metrics

arXiv:2403.18136v3 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have gained popularity in numerous domains, yet they are vulnerable to backdoor attacks that can compromise their

Identifying Multi-Hit Cancer Drivers Without Massive Parallelization: A CP, MIP, and Column Generation Framework

model-releasesarxiv-cs-lg

arXiv:2602.22551v2 Announce Type: replace-cross Abstract: Cancer is often driven by specific combinations of an estimated two to nine gene mutations, known as multi-hit combinations. Identifying these

Illusion-Aware Visual Preprocessing and Anti-Illusion Prompting for Classic Illusion Understanding in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.08841v1 Announce Type: new Abstract: Vision-Language Models (VLMs) exhibit systematic bias toward visual illusions, recalling memorized facts rather than perceiving actual visual difference

IMPACT: An Implicit Active-Set Augmented Lagrangian for Fast Contact-Implicit Trajectory Optimization

arXiv:2605.09127v1 Announce Type: new Abstract: Contact-implicit trajectory optimization (CITO) has attracted growing attention as a unified framework for planning and control in contact-rich robotic

researcharxiv-cs-ro

Impact of Connectivity on Laplacian Representations in Reinforcement Learning

arXiv:2603.08558v2 Announce Type: replace Abstract: Learning compact state representations in Markov Decision Processes (MDPs) has proven crucial for addressing the curse of dimensionality in large-sc

Implicit Hypothesis Testing and Divergence Preservation in Neural Network Representations

arXiv:2601.20477v3 Announce Type: replace Abstract: We study the training dynamics of neural classifiers through the lens of binary hypothesis testing. We re-formalize classification as a collection o

Improved Mean Flows: On the Challenges of Fastforward Generative Models

arXiv:2512.02012v2 Announce Type: replace Abstract: MeanFlow (MF) has recently been established as a framework for one-step generative modeling. However, its ``fastforward'' nature introduces key chal

Improving Generalization by Permutation Routing Across Model Copies

arXiv:2605.09256v1 Announce Type: cross Abstract: We introduce a use of the (M)-cover (or (M)-layer) transform for machine learning. The method replicates a model (M) times, but instead of coupling th

Tutorials

Improving Generative Adversarial Networks with Self-Distillation

arXiv:2605.08577v1 Announce Type: new Abstract: In modern GANs, maintaining an Exponential Moving Average (EMA) of the generator's weights is a standard practice, as such an averaged model consistentl

tutorialsarxiv-cs-cv

Improving Human Image Animation via Semantic Representation Alignment

arXiv:2605.10523v1 Announce Type: new Abstract: The field of image-to-video generation has made remarkable progress. However, challenges such as human limb twisting and facial distortion persist, espe

safetyarxiv-cs-cv

Improving Lexical Difficulty Prediction with Context-Aligned Contrastive Learning and Ridge Ensembling

arXiv:2605.08950v1 Announce Type: cross Abstract: Lexical difficulty prediction is a fundamental problem in language learning and readability assessment, requiring models to estimate word difficulty a

Improving Temporal Action Segmentation via Constraint-Aware Decoding

arXiv:2605.10149v1 Announce Type: new Abstract: Temporal action segmentation (TAS) divides untrimmed videos into labeled action segments. While fully supervised methods have advanced the field, challe

Improving Text-to-Image Generation with Intrinsic Self-Confidence Rewards

arXiv:2603.00918v3 Announce Type: replace-cross Abstract: Text-to-image generation powers content creation across design, media, and data augmentation. Post-training of text-to-image generative models

Improving TMS EEG Signal Quality for Closed-Loop Neuro Stimulation via Source-Domain Denoising

arXiv:2605.08184v1 Announce Type: cross Abstract: This research addresses a validated TMS EEG cleaning pipeline and a corresponding benchmark dataset. It evaluates two widely used artifact removal pip

In-Context Fixation: When Demonstrated Labels Override Semantics in Few-Shot Classification

arXiv:2605.08295v1 Announce Type: cross Abstract: While random demonstration labels barely hurt in-context learning (Min et al., 2022), we show that homogeneous labels--even semantically valid ones--c

Incorporating rank-free coupling and external field via an incoherent modulated spatial photonic Ising machine

arXiv:2512.21587v2 Announce Type: replace-cross Abstract: Spatial photonic Ising machines offer a novel optical platform for optimization and spin-model simulation, but existing diffraction-based sche

Increasing the Efficiency of DETR for Maritime High-Resolution Images

arXiv:2605.10269v1 Announce Type: new Abstract: Maritime object detection is critical for the safe navigation of unmanned surface vessels (USVs), requiring accurate recognition of obstacles from small

Incremental Multilingual Text2Cypher with Adapter Combination

model-releasesarxiv-cs-cl

arXiv:2601.16097v2 Announce Type: replace Abstract: Large Language Models enable users to access database using natural language interfaces using tools like Text2SQL, Text2SPARQL, and Text2Cypher, whi

Tutorials

Inductive Entity Representations from Text via Link Prediction

arXiv:2010.03496v4 Announce Type: replace-cross Abstract: Knowledge Graphs (KG) are of vital importance for multiple applications on the web, including information retrieval, recommender systems, and

tutorialsarxiv-cs-ai

IndustryBench: Probing the Industrial Knowledge Boundaries of LLMs

arXiv:2605.10267v1 Announce Type: new Abstract: In industrial procurement, an LLM answer is useful only if it survives a standards check: recommended material must match operating condition, every par

INFANiTE: Implicit Neural representation for high-resolution Fetal brain spatio-temporal Atlas learNing from clinical Thick-slicE MRI

arXiv:2605.09977v1 Announce Type: new Abstract: Spatio-temporal fetal brain atlases are important for characterizing normative neurodevelopment and identifying congenital anomalies. However, existing

Infinite Mask Diffusion for Few-Step Distillation

arXiv:2605.10518v1 Announce Type: cross Abstract: Masked Diffusion Models (MDMs) have emerged as a promising alternative to autoregressive models in language modeling, offering the advantages of paral

Applications

Information Density as a Quantitative Measure for AI-enabled Virtual Sensing: Feasibility and Limits

arXiv:2605.08180v1 Announce Type: cross Abstract: Modern IoT and sensor networks generate vast amounts of data, posing significant challenges for storage, transmission, and real-time processing. Tradi

applicationsarxiv-cs-ai

Applications

Information Filtering via Variational Regularization for Robot Manipulation

arXiv:2601.21926v4 Announce Type: replace Abstract: Diffusion-based visuomotor policies built on 3D visual representations have achieved strong performance in learning complex robotic skills. However,

applicationsarxiv-cs-ro

Agents

Informative Path Planning with Guaranteed Estimation Uncertainty

arXiv:2602.05198v2 Announce Type: replace Abstract: Environmental monitoring robots often need to estimate data fields (e.g., salinity, temperature, bathymetry) under tight resource constraints. Class

agentsarxiv-cs-ro

Local Ai

Initiation of Interaction Detection Framework using a Nonverbal Cue for Human-Robot Interaction

arXiv:2605.10087v1 Announce Type: new Abstract: This paper describes an initiation of interaction(IoI) detection framework without keywords for human-robot interaction(HRI) based on audio and vision s

local-aiarxiv-cs-cv

Local Ai

Inpainting physics: self-supervised learning for context-driven fluid simulation

arXiv:2605.08832v1 Announce Type: new Abstract: Neural surrogate models for computational fluid dynamics (CFD) are typically trained as forward operators that map explicit problem specifications, such

local-aiarxiv-cs-lg

Agents

Insider Attacks in Multi-Agent LLM Consensus Systems

arXiv:2605.08268v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in multi-agent systems where agents communicate in natural language to solve tasks jointly. A k

agentsarxiv-cs-ai