Hierarchical

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Period ending 2026-09-14

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Period ending 2026-09-07

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132 papers

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Compact Geometric Representations of Hierarchies
Jun 16, 2026Prashant Gokhale, Piotr Indyk, Yuhao Liu +3Hyperspherical Embedding Geometry Hierarchical
Hierarchical Modeling of ICD Codes in EHR Foundation Models
Jun 13, 2026Megha Thukral, Dong Gyun Kang, Rudra Pratap Singh +3International Classification Of Disease Codes Electronic Health Record Foundation Models
DTVEM-RE: A Hierarchical Random-Effects Extension of the Differential Time-Varying Effect Model for Person-Specific Multi-Lag Estimation in Intensive Longitudinal Data
Jun 12, 2026Amartya BhattacharyaLongitudinal Data Generalized Linear Model
Model-Based and Data-Driven Hierarchical Control and Topology Co-Design for Robust Networked Systems
Jun 10, 2026Shirantha Welikala, Zihao Song, Hai Lin +1Smart Grids Communication Topologies
Measuring language complexity from hierarchical reuse of recurring patterns
Jun 10, 2026Junyi Zhou, Rui Liu, Pengyu Liu +1Linguistics Ladder
Learning Dynamics Reveal a Hierarchy of Weight-Induced Layerwise Gram Metrics
Jun 8, 2026Claudio NordioRectified Linear Unit Networks Hierarchical
Aperon Technical Report: Hierarchical No-Pointer Tangent-Local Search for High-Dimensional Approximate Nearest Neighbors
Jun 7, 2026Yong FuApproximate Nearest-Neighbor Search Vector Database
Sigma-Branch: Hierarchical Single-Path Network Reconstruction for Dynamic Inference with Reduced Active Parameters
Jun 7, 2026Kohga Tanaka, Hiroaki NishiConvolutional Neural Network Compression Graph Neural Network Inference
Neural Field Tokenizations with Hierarchy and Spatial Locality Priors
Jun 6, 2026Alonso Urbano, David W. Romero, Max Zimmer +1Neural Fields Rich Spatial Priors
Hierarchical Semantic-Constrained Heterogeneous Graph for Audio-Visual Event Localization
Jun 5, 2026Zhe Yang, Ruyi Zhang, Hongtao Chen +4Sequential Visual Localization Visual Representation Learning
Hierarchies of Calibration: Classification meets Regression
Jun 2, 2026Johannes Resin, Lu Yang, Tilmann GneitingProbability Posterior
Hierarchically Decoupled Mixture-of-Experts for Robust Traffic Sign Recognition in Complex Driving Scenarios
Jun 1, 2026Mingxiao Wang, Xiaozhen Qu, Bolin Gao +2Traffic Sign Recognition Traffic
A Framework for Graph-Conditioned Hierarchical Shapley Attribution in Patent Valuation
Jun 1, 2026Joy BoseShapley Value Patent
Hierarchical Semantic-Augmented Navigation: Optimal Transport and Graph-Driven Reasoning for Vision-Language Navigation
Jun 1, 2026Xiang Fang, Wanlong Fang, Changshuo WangVision-And-Language Navigation 3D Scene Graphs
Semi-Supervised Hyperbolic Hierarchical Clustering with Set-Level Structural Priors
Jun 1, 2026Junjing Zheng, Xinyu Zhang, Xiangfeng Qiu +2Hyperbolic Learning Semi-Supervised Learning
Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation
May 31, 2026Xinze ZhangAtmospheric Correction Cross-Modal Fusion
Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling
May 30, 2026Petr NyomaEfficient Long-Context Inference State Space Models
Enhancing Protein-Protein Interaction Prediction with Hierarchical Motif-based Multimodal Protein Embedding
May 30, 2026Zaifei Yang, Samuel Ping-Man Choi, James KwokProtein Unimodal Encoders
HiGS: A Hierarchical Rendering Architecture for Real-Time 3D Gaussian Splatting
May 29, 2026Dawid Pająk, Martin Bisson, Rodolfo LimaRasterization 3D Gaussian Splatting
HiERO-StepG @ Ego4D Step Grounding Challenge: hierarchical activity understanding enables zero-shot step grounding
May 29, 2026Andrea Zenotto, Simone Alberto Peirone, Francesca Pistilli +1Fine-Grained Actions Zero-Shot Benchmark
HTAM: Hierarchical Transition-Attended Memory for Operator Optimization
May 28, 2026Yining Zhang, Mingyang Yi, Chen Wang +5Code Optimization Large Language Model Serving
Misalignment Between Backpropagation and the Hierarchy of Brain Responses to Images
May 27, 2026Joséphine Raugel, Maximilian Seitzer, Marc Szafraniec +6Backpropagation Human Visual Cortex
Hierarchical Prompt-Domain Control and Learning for Resource-Constrained Agentic Language Models
May 26, 2026Joan Vendrell Gallart, Russell Bent, Michael GrosskopfAgentic AI Systems Hierarchical
Beyond Binary: Speech Representations Across the Cognitive Score Hierarchy
May 26, 2026Serli Kopar, Roshan Prakash Rane, Christian Mychajliw +619-Metric Five-Dimensional Cognitive Profile Hierarchical
Bridging the 2D-3D Gap: A Hierarchical Semantic-Geometric Map for Vision Language Navigation
May 25, 2026Kailing Li, Tianwen Qian, Lijin Yang +4Vision-And-Language Navigation 3D Spatial Reasoning
HCL-FF: Hierarchical and Contrastive Learning for Forward-Forward Algorithm
May 24, 2026Jie-En Yao, Hong-En Chen, C. -C. Jay KuoSingle Forward Pass Contrastive Learning
Hierarchical Concept Geometry in Language Models Emerges from Word Co-occurrence
May 22, 2026Andres Nava, Matthieu WyartCo-Occurrence Vector Embeddings
Maestro: Reinforcement Learning to Orchestrate Hierarchical Model-Skill Ensembles
May 21, 2026Jinyang Wu, Guocheng Zhai, Ruihan Jin +7Multi-Agent Large Language Model Systems Multimodal Agents
From Automated to Autonomous: Hierarchical Agent-native Network Architecture (HANA)
May 20, 2026Binghan Wu, Shoufeng Wang, Yunxin Liu +3Software-Defined Networking Mobile Networks
Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction
May 19, 2026Dominique Briechle, Raj Chanchad, Tobias Geger +5Hierarchical Software
HAVEN: Hierarchically Aligned Multimodal Benchmark for Unified Video Understanding
May 19, 2026Mengqi Shi, Haopeng ZhangMultimodal Benchmarks Summarization
Efficient coding along the visual hierarchy
May 18, 2026Ananya Passi, Brian S. Robinson, Michael F. BonnerHuman Visual Cortex Visual Representation Learning
Self-supervised local learning rules learn the hidden hierarchical structure of high-dimensional data
May 18, 2026Ariane Delrocq, Wu S. Zihan, Guillaume Bellec +1Singular Learning Theory Synaptic Plasticity
A Hierarchical Language Model with Predictable Scaling Laws and Provable Benefits of Reasoning
May 13, 2026Jason Gaitonde, Frederic Koehler, Elchanan Mossel +2Autoregressive Language Models Autoregressive Model
Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas
May 13, 2026Lukas Stähelin, Veronika Solopova, Max Upravitelev +6Text Classifier Taxonomy
Inducing Overthink: Hierarchical Genetic Algorithm-based DoS Attack on Black-Box Large Language Reasoning Models
May 13, 2026Shuqiang Wang, Wei Cao, Jiaqi Weng +4LLM Reasoning Methods Large Reasoning Models
Switching Successor Measures for Hierarchical Zero-shot Reinforcement Learning
May 13, 2026Stefan Stojanovic, Alexandre ProutiereHierarchical Reinforcement Learning Goal-Conditioned Reinforcement Learning
When Does Hierarchy Help? Benchmarking Agent Coordination in Event-Driven Industrial Scheduling
May 13, 2026Ziqi Wang, Yuhao Yang, Zhiwei Ling +2Global Coordination Coordination
To Whom Do Language Models Align? Measuring Principal Hierarchies Under High-Stakes Competing Demands
May 12, 2026Fangyi Yu, Nabeel Seedat, Jonathan Richard Schwarz +1High-Stakes Decision Social Norms
Online Continual Learning with Dynamic Label Hierarchies
May 12, 2026Xinrui Wang, Shao-Yuan Li, Bartłomiej Twardowski +2Efficient Continual Learning Continual Learning
Not All Thoughts Need HBM: Semantics-Aware Memory Hierarchy for LLM Reasoning
May 10, 2026Aojie Yuan, Tianqi Shen, Dajun ZhangLLM Reasoning Methods Key-Value Cache
Hierarchical Attention-based Graph Neural Network with Relevance-driven Pruning
May 10, 2026Seungwoo KumGraph Neural Networks Multi-View Gated Graph Attention Network
Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations
May 9, 2026Shizhong Zhou, Haifeng Liu, Zheng Zhang +3Traffic Hierarchical Reinforcement Learning
Hierarchical Prompting with Dual LLM Modules for Robotic Task and Motion Planning
May 8, 2026Karolina Źróbek, Tessa Pulli, Paweł Gajewski +2Robotic Manipulation Human-Robot Interaction
Tree SAE: Learning Hierarchical Feature Structures in Sparse Autoencoders
May 8, 2026Tue M. Cao, Hoang X. Nhat, Raed Alharbi +2Improving Sparse Autoencoders Sparse Autoencoders
FS-I2P:A Hierarchical Focus-Sweep Registration Network with Dynamically Allocated Depth
May 8, 2026Zhixin Cheng, Yujia Chen, Xujing Tao +4Rgb-Depth Cameras Scaling
Classification Fields: Arbitrarily Fine Recursive Hierarchical Clustering From Few Examples
May 8, 2026Yicen Li, Ruiyang Hong, Anastasis Kratsios +2Clustering Cluster
SAGE: Hierarchical LLM-Based Literary Evaluation through Ontology-Grounded Interpretive Dimensions
May 8, 2026Tianyu Wang, Nianjun ZhouLiterature Large Language Model Evaluation
When Labels Have Structure: Improving Image Classification with Hierarchy-Aware Cross-Entropy
May 7, 2026April Chan, Davide D'Ascenzo, Sebastiano Cultrera di MontesanoCross-Entropy Losses Image Classification
PhysForge: Generating Physics-Grounded 3D Assets for Interactive Virtual World
May 6, 2026Yunhan Yang, Chunshi Wang, Junliang Ye +73D Assets Physics Simulation
The Causal Description Gap: Information-Theoretic Separations Across Pearl's Hierarchy
May 4, 2026Seyed Morteza EmadiCausal Structure and Reasoning Computable
Learning Coarse-to-Fine Osteoarthritis Representations under Noisy Hierarchical Labels
May 1, 2026Tongxu ZhangKnee Osteoarthritis Severity
Hierarchical Federated Learning for Networked AI: From Communication Saving to Architecture-Aware Design
May 1, 2026Seyed Mohammad Azimi-Abarghouyi, Mehdi Bennis, Leandros TassiulasFederated Learning Framework Hierarchical
Three-Step Nav: A Hierarchical Global-Local Planner for Zero-Shot Vision-and-Language Navigation
Apr 29, 2026Wanrong Zheng, Yunhao Ge, Laurent IttiVision-And-Language Navigation Vop-Nav
One Refiner to Unlock Them All: Inference-Time Reasoning Elicitation via Reinforcement Query Refinement
Apr 28, 2026Yixiao Zhou, Dongzhou Cheng, zhiliang wu +3LLM Reasoning Methods Elicitation
Hierarchical Prototype-based Domain Priors for Multiple Instance Learning in Multimodal Histopathology Analysis
Apr 27, 2026Xuemei Qiu, Dawei Fan, Yebin Huang +2Digital Pathology Multiple Instance Learning
From Edges to Depth: Probing the Spatial Hierarchy in Vision Transformers
Apr 25, 2026Jainum SanghaviSelf-Supervised Vision Transformers Vision Transformer
INSIGHT: Indoor Scene Intelligence from Geometric-Semantic Hierarchy Transfer for Public~Safety
Apr 25, 2026Alexander Nikitas Dimopoulos, Joseph Grasso, John Beltz3D Scene Graphs Insights
Cross-Stage Coherence in Hierarchical Driving VQA: Explicit Baselines and Learned Gated Context Projectors
Apr 24, 2026Gautam Kumar Jain, Carsten Markgraf, Julian StählerAutonomous Driving Vision-Language Model Reasoning
Mango: Multi-Agent Web Navigation via Global-View Optimization
Apr 20, 2026Weixi Tong, Yifeng Di, Tianyi ZhangWeb Agents Web

Jun 16, 2026 · stat.MLJ/K move · Enter open · S save

Compact Geometric Representations of Hierarchies

Prashant Gokhale, Piotr Indyk, Yuhao Liu, Sandeep Silwal+2

Computing geometric representations of data is a cornerstone of modern machine learning, typically achieved by training dual encoders which map queries and documents into a shared embedding space. Recent work of You et al. [NeurIPS '25] has extended this approach to hierarchical retrieval, where relevance is determined by the ancestor-descendant relationships in a Directed Acyclic Graph (DAG). While previous work has shown that valid embeddings exist when the number of descendants is small, these bounds degrade significantly for deep hierarchies, requiring dimensions as large as the total number of nodes. In this paper, we investigate compact reachability embeddings for more general graph classes and provide theoretical guarantees for representing hierarchies using embeddings whose dimension depends on structural graph parameters. We prove that for any directed tree, there exists a reachability embedding in constant dimension 3, independent of the tree's size or depth. We generalize this result to graphs characterized by treewidth

t

, constructing embeddings of dimension

O(t \log n)

, where

n

is the number of nodes. Complementing these upper bounds, we provide matching or near-matching lower bounds, showing that dimension

Ω(n)

is necessary for general DAGs and

Ω(t/\log(n/t))

is required for graphs of treewidth

t

. We also obtain upper and lower bounds parameterized by the number of cross-edges in the DAG. We additionally show that our embeddings can be constructed on real world datasets, and that they give much smaller dimensions in high recall regimes compared to prior embeddings with theoretical guarantees.

Hyperspherical Embedding Geometry Hierarchical Validity

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