Split Learning

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Period ending 2026-09-14

4 new papers

A weekly snapshot of new work published in Split Learning.

Period ending 2026-09-07

1 new paper

A weekly snapshot of new work published in Split Learning.

92 papers

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Learned Look-Ahead Splitting Rule for CART
Sep 14, 2026Andrew Gao, Tianlin Liu, Ruichen Han +1Decision Trees Split Learning
LLM-Based Schema-Aware Split Learning for Privacy-Preserving Mental Distress Prediction Across Heterogeneous Surveys
Sep 14, 2026Md Khalid Syfullah, Alvi Ataur KhalilPrivacy-Preserving Framework Mental Health
Privacy-Preserving Split Learning for Federated LLM Fine-Tuning
Sep 9, 2026Heng Jin, Chaoyu Zhang, Hexuan Yu +2Federated Fine-Tuning Large Language Model Fine-Tuning
BAFF: Bid-Aware Filter Family for Mitigating Training Data Interference in RTB A/B Tests
Sep 8, 2026Jeonglyul Oh, Ikkyu Choi, Inseop Youn +1First-Price Auctions Split Learning
ComVLA: Communication-Aware Split Inference for VLA Models in 6G-Connected Robotics
Sep 7, 2026Boliang Liu, Wint Yi Poe, Jingyun Di +2Semantic Communications Vision-Language-Action
Diffusion Language Models for Mobile Edge Agentic AI: Foundations, Applications, and Challenges
Sep 7, 2026Chenqi Li, Minghui Min, Dusit Niyato +1Diffusion Language Models Low-Latency Systems
Contribution-Aware Bandwidth Allocation for Multimodal Split Learning
Sep 1, 2026Iason Ofeidis, Leandros TassiulasMultimodal Learning Wireless Resource Allocation
DCA-MoE: Spatially Adaptive Cross-Layer Fusion and Density-Routed Experts for Crowd Counting
Aug 15, 2026Hao WangMoe-Nd Cross-Layer Interactions
From Atomic Evidence to Logical Composition: Structured Compositional Reasoning over Compound Answer Options
Aug 13, 2026Obed Junias, Maria Leonor PachecoCompositionality Atoms
Interpretable machine learning for predicting splitting strength of asphalt concrete: insights from SHAP analysis
Aug 2, 2026Jianglei Xing, Xiao Tan, Dongzhao Jin +3Shapley Value Interpretable Machine Learning
GQ-FSL: Green Quantized Federated Split Learning
Jul 31, 2026Idan Roth, Lutz LampeEdge Computing Resource-Constrained Devices
Mining Verdict Boundaries for Neural Network Verification
Jul 31, 2026Jiawei Ren, Guanqin Zhang, Zhenya Zhang +1Neural Network Verification Tight Bounds
From Pixels to PCells: A Neurosymbolic Approach to Photonic Component Creation
Jul 29, 2026Aadarsh Agarwal, Kenaish Al Qubaisi, Dirk EnglundPhotonics Pixelloop
Enhancing Automated Machine Learning via Homogeneous Train-Test Splitting Methods
Jul 29, 2026Yearn Tan Yin Tze, Charles GrelloisModel Evaluation Split Learning
Mind the Missing Split: Resolving Feature Heterogeneity in Swarm Learning with Random Forests
Jul 28, 2026Mohammad Tajabadi, Dominik HeiderHeterogeneity Random Forest
BettiSplit: Topology-Guided Privacy-Aware Split Learning Against Feature Inversion and Gradient Leakage
Jul 27, 2026Akarsh K. Nair, Muhammad Arifur Rahman, David Brown +1Heuristic Privacy Metrics Split Learning
Distributional Split Criteria for Random Forests: Extensions, Shrinkage, and the Robustness of Mean Splitting
Jul 26, 2026Silas KoemenRandom Forest Split Learning
When Rates Are Geometric: Rate-Certificate Transfer for Contact Splittings in Optimization
Jul 26, 2026George A KevrekidisHamiltonian Lyapunov Function
Learned Interventions in Lean 4 grind
Jul 25, 2026Evan Wang, Simon Chess, Sophie Szeto +1Theorem Heuristics
Khondo: A Multimodal Benchmark for Document Packet Splitting of Bangla Forms
Jul 23, 2026Abu Tyeb Azad, Fahim Ahmed, Ishita Sur Apan +7End-To-End Document Parsing Document
ADABORD: a novel AdaBoost approach for ordinal classification
Jul 23, 2026Rafael Ayllón-Gavilán, Francisco José Martínez-Estudillo, David Guijo-Rubio +2Gradient Boosted Tree Split Learning
Sentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning
Jul 22, 2026Ahmad Pouramini, Mahsa AfsharizadehNatural Language Processing Knowledge Graph Completion
Where Does Agent Reliability Come From? A Cross-Benchmark Decomposition of Verification Loops, Specialist Models, and Scaffolding in a Production Enterprise Agent
Jul 19, 2026Arunabh DastidarReliability Verification
Scaffold splits hide structural-frontier failures in ADMET models
Jul 12, 2026Jiacheng Zheng, Chang Guo, Zixuan Wang +1Label-Free Frontiers
A Word-Level Digital Reader of the Prasthanatrayi with Sankara's Bhasya: Corpus, Method, and an Open, Offline Reading Aid for the Advaita Vedanta Canon
Jul 8, 2026Tamal MaharajIndian Languages Corpus
Significance-First Splitting: Aligning Treatment Heterogeneity Detection with Honest Estimation
Jul 4, 2026Pantelis Z. Hadjipantelis, Weng Man Chiang, Karthik NageshHeterogeneous Treatment Effects Treatment
JavaVulBench: A Java Vulnerability Benchmark with Realistic Splits, a Unified Multi-Backend Harness, and a Leakage-Aware Evaluation Mode
Jul 2, 2026Norbert Sandor Szolnoki, Gabor AntalVulnerability Detection & Repair Benchmark Datasets
Post-Generation Curation of Synthetic Images via Homogeneous-Heterogeneous Splitting
Jul 2, 2026Disheng Liu, Tuo Liang, Chaoda Song +1Synthetic Data Generative Models
Beyond the Performance Illusion: Structure-Aware Stratified Partitioning and Curriculum Distributionally Robust Optimization for Spatially Correlated Domains
Jul 2, 2026Prathamesh Patil, Arpit Jain, Aswanth KrishnanPartitioning Distributional Learning
SPLIT: Cross-Lingual Empathy and Cultural Grounding in English and Ukrainian LLM Responses
Jul 2, 2026Anna ChornaCross-Lingual Consistency Multilingual
On Optimal Data Splitting for Split Conformal Prediction
Jun 30, 2026Sayan Das, Bahram Yaghooti, Todd A. Kuffner +1Conformal Prediction Split Learning
C $^{2}$ R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse AutoencodersC^{2}R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders
Jun 29, 2026Haoran Jin, Xiting Wang, Shijie Ren +2Sparse Autoencoders Regularization Methods
Optimizing Teacher-Student Partitioning for Scalable Knowledge Distillation on HPC Systems
Jun 26, 2026Adrian P. Dieguez, Victor Conchello Vendrell, Alex Batlle +3Heterogeneous Knowledge Distillation Partitioning
TL++: Accuracy and Privacy Preserving Traversal Learning for Distributed Intelligent Systems
Jun 24, 2026Erdenebileg Batbaatar, Young YoonPrivacy-Preserving Framework Distributional Learning
Retrieval-Augmented Multimodal Learning for Enzyme-Substrate Interaction Prediction Under Low-Homology Shift
Jun 22, 2026Chen Liu, Bingxin Zhou, Xinyuan Wang +3Heterogeneous Catalysis Split Learning
The Art of Mixology: Mixup-based Obfuscation for Privacy-Preserving Split Learning in Large Language Models
Jun 15, 2026Chen Chen, Xiang Gao, Xianshun Wang +6Split Learning Obfuscation
Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference
Jun 15, 2026Alexander Yukhimchuk, Andrey Shulga, Mladen Kolar +1Obfuscation Privacy-Preserving Framework
From Prompts to Responses: Dual-Sided Data Leakage and Defense in Split Large Language Models
Jun 12, 2026Zixuan Gu, Xiaojun Ye, Yang LiuLanguage Model Evasion Attacks Data Leakage
Simultaneous Latent Budget Trees for Stratified Classification
Jun 11, 2026Simultaneous Latent Budget Trees for Stratified Classification Cristian Buoncompagni, Stefano Pellegrino, Giulia Vannucci +2Decision Trees Stratification
Learning Splitting Heuristics for Parallel String Solvers
Jun 9, 2026Chenhao Gao, Peisen YaoHeuristics Split Learning
Probing Token Spaces under Generator Shift in AI-Generated Music Detection
Jun 7, 2026Joonyong Park, Jungwoo Kim, Junyoung Koh +1Machine-Generated Text Detection Generating
Complexity-Balanced Diffusion Splitting
Jun 4, 2026Noam Issachar, Dani Lischinski, Raanan FattalGenerative Models Split Learning
Subspace-Aware Sparse Autoencoders for Effective Mechanistic Interpretability
Jun 4, 2026Seyed Arshan Dalili, Mehrdad MahdaviSparse Autoencoders Mechanistic Interpretability
SplitAdapter: Load-Aware Humanoid Loco-Manipulation via Factorized Adaptation
Jun 2, 2026Jeonguk Kang, Hanbyel Cho, Sanghyun Kang +1Humanoid Loco-Manipulation Generalizable Robot Control
Will Accurate Fields Mislead Photonic Design? FromGlobal Accuracy to Port Readout
Jun 2, 2026Yitian Zhang, Yonghong chen, Youming Chen +6Photonics Neural Fields
Decentralized Instruction Tuning: Conflict-Aware Splitting and Weight Merging
Jun 1, 2026Minsik Choi, Geewook KimInstruction Tuning Split Learning
QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning
Jun 1, 2026Nazmus Shakib Shadin, Xinyue Zhang, Jingyi Wang +1Split Learning Distributional Learning
Correcting Split Selection in Online Decision Trees via Anytime-Valid Inference
May 29, 2026Salim I. Amoukou, Saumitra Mishra, Manuela VelosoDecision Trees Random Forest
Leave a Window Out: Modifying the Jackknife for Predictive Inference in Time Series
May 28, 2026Hanyang Jiang, Rina Foygel Barber, Ashwin Pananjady +1Conformal Prediction Cross Validation
Separate Aggregation of Split Network for Personalized Federated Learning
May 26, 2026Yunseok Kang, Jaeyoung SongHeterogeneity Distributional Learning
StreamSplit: Continuous Audio Representation Learning via Uncertainty-Guided Adaptive Splitting
May 26, 2026Minh K. Quan, Pubudu N. PathiranaEdge Computing Streaming
SplitAvatar: One-shot Head Avatar with Autoregressive Gaussian Splitting
May 25, 2026Hongzhe Liao, Chuhua Xian, Hongmin Cai +2Animatable 3D Human Avatars 3D Gaussian Splatting
When One Point Is Not Enough: Addressing Ambiguous Instances in Dimensionality Reduction by Splitting
May 22, 2026Diede P. M. van der Hoorn, Alessio Arleo, Fernando V. PaulovichDimensionality Reduction High-Dimensional
Hinge Regression Trees and HRT-Boost: Newton-Optimized Oblique Learning for Compact Tabular Models
May 22, 2026Hongyi Li, Jun Xu, Hong YanDecision Trees Random Forest
What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
May 22, 2026Mingyuan Fan, Yu Liu, Fuyi Wang +1LLM Inference Efficiency Heuristic Privacy Metrics
Ternary Decision Trees with Locally-Adaptive Uncertainty Zones
May 21, 2026William SmitsDecision Trees Predictive Uncertainty
Tokenization with Split Trees
May 21, 2026Craig W. Schmidt, Michael Krumdick, Adam Wiemerslage +4Subword Tokenization N$-Grams Features
Towards Large Model Feature Coding
May 20, 2026Youwei Pang, Changsheng Gao, Dong Liu +2Large-Scale Benchmark Large Multimodal Models
Breaking Modality Heterogeneity in Low-Bit Quantization for Large Vision-Language Models
May 19, 2026Yi Zhong, Haotong Qin, Xindong Zhang +2Low-Bit Quantization Quantization
A Two-Phase Adaptive Balanced Penalty Method for Controllable Pareto Front Learning under Split Feasibility Conditions
May 19, 2026Nguyen Viet Hoang, Dung D. Le, Tran Ngoc ThangQuadratic Slack Penalty Pareto Frontier

Sep 14, 2026 · stat.MLJ/K move · Enter open · S save

Learned Look-Ahead Splitting Rule for CART

Andrew Gao, Tianlin Liu, Ruichen Han, Lu Tian

Classification and regression trees are typically constructed using a greedy splitting rule that maximizes the immediate reduction in prediction error at each node. Although this strategy is computationally efficient, it can miss splits that yield small short-term gains but create substantial downstream improvements after further partitioning. We propose a look-ahead tree-building method that evaluates each candidate split by the prediction error reduction achieved after growing a conventional CART subtree below that split. Because the full look-ahead procedure can be computationally expensive, we also describe a smart look-ahead algorithm that learns downstream split values using node-level features. The proposed framework preserves the interpretability of recursive partitioning while improving split selection in hierarchical or interaction-driven settings. We conduct a simulation study comparing conventional, full look-ahead, and smart look-ahead methods under several settings and apply the proposed methods to analyze two real data examples demonstrating the merit of the new methods.

Decision Trees Split Learning

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