:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Lei, Zhang, Yuge, Ren, Kan, Li, Dongsheng, Yang, Yuqing
Format:	Preprint
Published:	2023
Subjects:	Machine Learning Artificial Intelligence
Online Access:	https://arxiv.org/abs/2304.14979
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Agent Lightning: Train ANY AI Agents with Reinforcement Learning
by: Luo, Xufang, et al.
Published: (2025)

Learning to Select In-Context Demonstration Preferred by Large Language Model
by: Zhang, Zheng, et al.
Published: (2025)

Power Plays: Unleashing Machine Learning Magic in Smart Grids
by: Rashid, Abdur, et al.
Published: (2024)

Unleashing the Denoising Capability of Diffusion Prior for Solving Inverse Problems
by: Zhang, Jiawei, et al.
Published: (2024)

CogGPT: Unleashing the Power of Cognitive Dynamics on Large Language Models
by: Lv, Yaojia, et al.
Published: (2024)

Unleashing The Power of Pre-Trained Language Models for Irregularly Sampled Time Series
by: Zhang, Weijia, et al.
Published: (2024)

Large Language Models Explore by Latent Distilling
by: Zeng, Yuanhao, et al.
Published: (2026)

Towards Harnessing the Collaborative Power of Large and Small Models for Domain Tasks
by: Liu, Yang, et al.
Published: (2025)

ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling
by: Chen, Yuqi, et al.
Published: (2024)

Exploratory Memory-Augmented LLM Agent via Hybrid On- and Off-Policy Optimization
by: Liu, Zeyuan, et al.
Published: (2026)

Unleashing the Power of Imbalanced Modality Information for Multi-modal Knowledge Graph Completion
by: Zhang, Yichi, et al.
Published: (2024)

Polynomial Composition Activations: Unleashing the Dynamics of Large Language Models
by: Zhuo, Zhijian, et al.
Published: (2024)

On Predictability of Reinforcement Learning Dynamics for Large Language Models
by: Cai, Yuchen, et al.
Published: (2025)

Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras
by: Yu, Jun, et al.
Published: (2024)

OR-Toolformer: Modeling and Solving Operations Research Problems with Tool Augmented Large Language Models
by: Zhang, Jianzhang, et al.
Published: (2025)

Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models
by: Wang, Xin, et al.
Published: (2025)

Quantum Architecture Search for Solving Quantum Machine Learning Tasks
by: Kölle, Michael, et al.
Published: (2025)

Unlock the Potential of Large Language Models for Predictive Tabular Tasks in Data Science with Table-Specific Pretraining
by: Yang, Yazheng, et al.
Published: (2024)

SATURN: SAT-based Reinforcement Learning to Unleash LLMs Reasoning
by: Liu, Huanyu, et al.
Published: (2025)

Understanding Reasoning in LLMs through Strategic Information Allocation under Uncertainty
by: Kim, Jeonghye, et al.
Published: (2026)

GWT: Scalable Optimizer State Compression for Large Language Model Training
by: Wen, Ziqing, et al.
Published: (2025)

EEGFormer: Towards Transferable and Interpretable Large-Scale EEG Foundation Model
by: Chen, Yuqi, et al.
Published: (2024)

FD-LLM: Large Language Model for Fault Diagnosis of Machines
by: Qaid, Hamzah A. A. M., et al.
Published: (2024)

LLMExplainer: Large Language Model based Bayesian Inference for Graph Explanation Generation
by: Zhang, Jiaxing, et al.
Published: (2024)

SortedRL: Accelerating RL Training for LLMs through Online Length-Aware Scheduling
by: Zhang, Yiqi, et al.
Published: (2026)

Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
by: Jiang, Jinyang, et al.
Published: (2024)

Solving General Natural-Language-Description Optimization Problems with Large Language Models
by: Zhang, Jihai, et al.
Published: (2024)

FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients
by: Wen, Tian, et al.
Published: (2026)

MaZO: Masked Zeroth-Order Optimization for Multi-Task Fine-Tuning of Large Language Models
by: Zhang, Zhen, et al.
Published: (2025)

AIGC for Industrial Time Series: From Deep Generative Models to Large Generative Models
by: Ren, Lei, et al.
Published: (2024)

OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement
by: Li, Qinglun, et al.
Published: (2024)

How Do Large Language Models Understand Graph Patterns? A Benchmark for Graph Pattern Comprehension
by: Dai, Xinnan, et al.
Published: (2024)

Data-centric Federated Graph Learning with Large Language Models
by: Yan, Bo, et al.
Published: (2025)

Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving
by: Srinivas, Sakhinana Sagar, et al.
Published: (2024)

Large Language Models for Constructing and Optimizing Machine Learning Workflows: A Survey
by: Gu, Yang, et al.
Published: (2024)

Leveraging Large Language Models for Solving Rare MIP Challenges
by: Wang, Teng, et al.
Published: (2024)

Omni-DNA: A Unified Genomic Foundation Model for Cross-Modal and Multi-Task Learning
by: Li, Zehui, et al.
Published: (2025)

SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training
by: Zhang, Gengwei, et al.
Published: (2024)

Synergizing Large Language Models and Task-specific Models for Time Series Anomaly Detection
by: Chen, Feiyi, et al.
Published: (2025)

PowerPM: Foundation Model for Power Systems
by: Tu, Shihao, et al.
Published: (2024)