:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Liu, Xiaoqian, Jiao, Jianbin, Zhang, Junge
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2401.00031
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Position: Foundation Agents as the Paradigm Shift for Decision Making
by: Liu, Xiaoqian, et al.
Published: (2024)

Multi-level Self-supervised Pretraining on Compositional Hierarchical Graph for Molecular Property Prediction
by: Liu, Xiayu, et al.
Published: (2026)

Diffusion-Guided Pretraining for Brain Graph Foundation Models
by: Wei, Xinxu, et al.
Published: (2026)

UTICA: Multi-Objective Self-Distllation Foundation Model Pretraining for Time Series Classification
by: Moakher, Yessin, et al.
Published: (2026)

HeterCSI: Channel-Adaptive Heterogeneous CSI Pretraining Framework for Generalized Wireless Foundation Models
by: Zhang, Chenyu, et al.
Published: (2026)

Fostering Intrinsic Motivation in Reinforcement Learning with Pretrained Foundation Models
by: Andres, Alain, et al.
Published: (2024)

Pretraining a Foundation Model for Small-Molecule Natural Products
by: Ding, Yuheng, et al.
Published: (2025)

Advancing Financial Engineering with Foundation Models: Progress, Applications, and Challenges
by: Chen, Liyuan, et al.
Published: (2025)

CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data
by: Xie, Shifeng, et al.
Published: (2025)

Understanding the Training and Generalization of Pretrained Transformer for Sequential Decision Making
by: Wang, Hanzhao, et al.
Published: (2024)

Bridging Distribution Gaps in Time Series Foundation Model Pretraining with Prototype-Guided Normalization
by: Gong, Peiliang, et al.
Published: (2025)

Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons
by: Tang, Wei, et al.
Published: (2026)

Ten Challenging Problems in Federated Foundation Models
by: Fan, Tao, et al.
Published: (2025)

From Projection to Prediction: Beyond Logits for Scalable Language Models
by: Dong, Jianbing, et al.
Published: (2025)

IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining
by: Li, Yixiao, et al.
Published: (2025)

FMTK: A Modular Toolkit for Composable Time Series Foundation Model Pipelines
by: Shastri, Hetvi, et al.
Published: (2025)

Towards Open Respiratory Acoustic Foundation Models: Pretraining and Benchmarking
by: Zhang, Yuwei, et al.
Published: (2024)

Self-supervised Synthetic Pretraining for Inference of Stellar Mass Embedded in Dense Gas
by: Hirashima, Keiya, et al.
Published: (2025)

PRISM: Exploring Heterogeneous Pretrained EEG Foundation Model Transfer to Clinical Differential Diagnosis
by: Lahiri, Jeet Bandhu, et al.
Published: (2026)

Unraveling Spatio-Temporal Foundation Models via the Pipeline Lens: A Comprehensive Review
by: Fang, Yuchen, et al.
Published: (2025)

In-Context Decision Making for Optimizing Complex AutoML Pipelines
by: Balef, Amir Rezaei, et al.
Published: (2025)

UniTabE: A Universal Pretraining Protocol for Tabular Foundation Model in Data Science
by: Yang, Yazheng, et al.
Published: (2023)

Foundation Models for Anomaly Detection: Vision and Challenges
by: Ren, Jing, et al.
Published: (2025)

Advances and Open Challenges in Federated Foundation Models
by: Ren, Chao, et al.
Published: (2024)

Unsupervised Graph Neural Architecture Search with Disentangled Self-supervision
by: Zhang, Zeyang, et al.
Published: (2024)

Dual Formulation for Non-Rectangular Lp Robust Markov Decision Processes
by: Kumar, Navdeep, et al.
Published: (2025)

An Interpretable and Scalable Framework for Evaluating Large Language Models
by: Qu, Xinhao, et al.
Published: (2026)

MADCluster: Model-agnostic Anomaly Detection with Self-supervised Clustering Network
by: Lee, Sangyong, et al.
Published: (2025)

Pretraining Strategies and Scaling for ECG Foundation Models: A Systematic Study
by: Al-Masud, M A, et al.
Published: (2026)

Adaptive Spatio-Temporal Graphs with Self-Supervised Pretraining for Multi-Horizon Weather Forecasting
by: Liu, Yao
Published: (2025)

VIGraph: Generative Self-supervised Learning for Class-Imbalanced Node Classification
by: Hu, Yulan, et al.
Published: (2023)

Self-supervised learning on gene expression data
by: Dradjat, Kevin, et al.
Published: (2025)

Foundation Model Self-Play: Open-Ended Strategy Innovation via Foundation Models
by: Dharna, Aaron, et al.
Published: (2025)

FoundObj: Self-supervised Foundation Models as Rewards for Label-free 3D Object Segmentation
by: Zhang, Zihui, et al.
Published: (2026)

HeTa: Relation-wise Heterogeneous Graph Foundation Attack Model
by: Wang, Yuling, et al.
Published: (2025)

AnyAttack: Towards Large-scale Self-supervised Adversarial Attacks on Vision-language Models
by: Zhang, Jiaming, et al.
Published: (2024)

Persistent Backdoor Attacks under Continual Fine-Tuning of LLMs
by: Cui, Jing, et al.
Published: (2025)

Calibration-Aware Policy Optimization for Reasoning LLMs
by: Wang, Ziqi, et al.
Published: (2026)

Self-supervised and Multi-fidelity Learning for Extended Predictive Soil Spectroscopy
by: Sun, Luning, et al.
Published: (2025)

MALLM-GAN: Multi-Agent Large Language Model as Generative Adversarial Network for Synthesizing Tabular Data
by: Ling, Yaobin, et al.
Published: (2024)