Cover Image

TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Zefang, Quan, Yinzhu
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Temporal Tokenization Strategies for Event Sequence Modeling with Large Language Models
by: Liu, Zefang, et al.
Published: (2025)

InvAgent: A Large Language Model based Multi-Agent System for Inventory Management in Supply Chains
by: Quan, Yinzhu, et al.
Published: (2024)

EconLogicQA: A Question-Answering Benchmark for Evaluating Large Language Models in Economic Sequential Reasoning
by: Quan, Yinzhu, et al.
Published: (2024)

Retrieval of Temporal Event Sequences from Textual Descriptions
by: Liu, Zefang, et al.
Published: (2024)

EconWebArena: Benchmarking Autonomous Agents on Economic Tasks in Realistic Web Environments
by: Liu, Zefang, et al.
Published: (2025)

Communication-Efficient and Tensorized Federated Fine-Tuning of Large Language Models
by: Ghiasvand, Sajjad, et al.
Published: (2024)

SPP: Sparsity-Preserved Parameter-Efficient Fine-Tuning for Large Language Models
by: Lu, Xudong, et al.
Published: (2024)

Byte-token Enhanced Language Models for Temporal Point Processes Analysis
by: Kong, Quyu, et al.
Published: (2025)

Simultaneous Computation and Memory Efficient Zeroth-Order Optimizer for Fine-Tuning Large Language Models
by: Wang, Fei, et al.
Published: (2024)

Crafting Efficient Fine-Tuning Strategies for Large Language Models
by: Oliver, Michael, et al.
Published: (2024)

Dissecting Fine-Tuning Unlearning in Large Language Models
by: Hong, Yihuai, et al.
Published: (2024)

Empirical Analysis of Efficient Fine-Tuning Methods for Large Pre-Trained Language Models
by: Doering, Nigel, et al.
Published: (2024)

Less but Better: Parameter-Efficient Fine-Tuning of Large Language Models for Personality Detection
by: Shen, Lingzhi, et al.
Published: (2025)

L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models
by: Jeon, Hyesung, et al.
Published: (2024)

Personalized Collaborative Fine-Tuning for On-Device Large Language Models
by: Wagner, Nicolas, et al.
Published: (2024)

How Multilingual Are Large Language Models Fine-Tuned for Translation?
by: Richburg, Aquia, et al.
Published: (2024)

Dynamic Adaptation of LoRA Fine-Tuning for Efficient and Task-Specific Optimization of Large Language Models
by: Liao, Xiaoxuan, et al.
Published: (2025)

Hyperbolic Fine-Tuning for Large Language Models
by: Yang, Menglin, et al.
Published: (2024)

Fine-Tuning Large Language Models to Appropriately Abstain with Semantic Entropy
by: Tjandra, Benedict Aaron, et al.
Published: (2024)

Synthetic Data Generation in Low-Resource Settings via Fine-Tuning of Large Language Models
by: Kaddour, Jean, et al.
Published: (2023)

AdaMoLE: Fine-Tuning Large Language Models with Adaptive Mixture of Low-Rank Adaptation Experts
by: Liu, Zefang, et al.
Published: (2024)

A Spatio-Temporal Point Process for Fine-Grained Modeling of Reading Behavior
by: Re, Francesco Ignazio, et al.
Published: (2025)

Comparative Analysis of Different Efficient Fine Tuning Methods of Large Language Models (LLMs) in Low-Resource Setting
by: Srinivasan, Krishna Prasad Varadarajan, et al.
Published: (2024)

LoRA-SP: Streamlined Partial Parameter Adaptation for Resource-Efficient Fine-Tuning of Large Language Models
by: Wu, Yichao, et al.
Published: (2024)

Scaling Sparse Fine-Tuning to Large Language Models
by: Ansell, Alan, et al.
Published: (2024)

Boosting Large Language Models with Mask Fine-Tuning
by: Zhang, Mingyuan, et al.
Published: (2025)

Exploring Parameter-Efficient Fine-Tuning Techniques for Code Generation with Large Language Models
by: Weyssow, Martin, et al.
Published: (2023)

BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models
by: Chang, Aofei, et al.
Published: (2024)

Parameter-Efficient Fine-Tuning of State Space Models
by: Galim, Kevin, et al.
Published: (2024)

Energy-Efficient Split Learning for Fine-Tuning Large Language Models in Edge Networks
by: Li, Zuguang, et al.
Published: (2024)

Improving Large Language Models with Concept-Aware Fine-Tuning
by: Chen, Michael K., et al.
Published: (2025)

LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning
by: Pan, Rui, et al.
Published: (2024)

Efficient Temporal Tokenization for Mobility Prediction with Large Language Models
by: He, Haoyu, et al.
Published: (2025)

DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation
by: Woo, Sunghyeon, et al.
Published: (2024)

Fine-Tuned Large Language Models for Symptom Recognition from Spanish Clinical Text
by: Shaaban, Mai A., et al.
Published: (2024)

SVFit: Parameter-Efficient Fine-Tuning of Large Pre-Trained Models Using Singular Values
by: Sun, Chengwei, et al.
Published: (2024)

Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning
by: Park, Juneyoung, et al.
Published: (2026)

Fine-Tuning Language Models with Just Forward Passes
by: Malladi, Sadhika, et al.
Published: (2023)

Parameter-Efficient Fine-Tuning in Large Models: A Survey of Methodologies
by: Wang, Luping, et al.
Published: (2024)

Parameter-Efficient Tuning Large Language Models for Graph Representation Learning
by: Zhu, Qi, et al.
Published: (2024)