Cover Image

ITERTL: An Iterative Framework for Fine-tuning LLMs for RTL Code Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Peiyang, Guo, Nan, Xiao, Xiao, Li, Wenming, Ye, Xiaochun, Fan, Dongrui
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RTLRepoCoder: Repository-Level RTL Code Completion through the Combination of Fine-Tuning and Retrieval Augmentation
by: Wu, Peiyang, et al.
Published: (2025)

Fine-tuned Large Language Models (LLMs): Improved Prompt Injection Attacks Detection
by: Rahman, Md Abdur, et al.
Published: (2024)

Semi-supervised Fine-tuning for Large Language Models
by: Luo, Junyu, et al.
Published: (2024)

In-Context Learning with Iterative Demonstration Selection
by: Qin, Chengwei, et al.
Published: (2023)

Fine-tuning and Utilization Methods of Domain-specific LLMs
by: Jeong, Cheonsu
Published: (2024)

Structure-aware Fine-tuning for Code Pre-trained Models
by: Wu, Jiayi, et al.
Published: (2024)

RobustFT: Robust Supervised Fine-tuning for Large Language Models under Noisy Response
by: Luo, Junyu, et al.
Published: (2024)

LLM-FSM: Scaling Large Language Models for Finite-State Reasoning in RTL Code Generation
by: Wu, Yuheng, et al.
Published: (2026)

Aloe: A Family of Fine-tuned Open Healthcare LLMs
by: Gururajan, Ashwin Kumar, et al.
Published: (2024)

Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation
by: Liu, Peiyang, et al.
Published: (2026)

Enhancing Chain-of-Thought Reasoning with Critical Representation Fine-tuning
by: Huang, Chenxi, et al.
Published: (2025)

A Framework to Implement 1+N Multi-task Fine-tuning Pattern in LLMs Using the CGC-LORA Algorithm
by: Song, Chao, et al.
Published: (2024)

QiMeng-CodeV-SVA: Training Specialized LLMs for Hardware Assertion Generation via RTL-Grounded Bidirectional Data Synthesis
by: Wu, Yutong, et al.
Published: (2026)

When MOE Meets LLMs: Parameter Efficient Fine-tuning for Multi-task Medical Applications
by: Liu, Qidong, et al.
Published: (2023)

DGRC: An Effective Fine-tuning Framework for Distractor Generation in Chinese Multi-choice Reading Comprehension
by: Lin, Runfeng, et al.
Published: (2024)

Affordably Fine-tuned LLMs Provide Better Answers to Course-specific MCQs
by: Raimondi, Bianca, et al.
Published: (2025)

PsyMem: Fine-grained psychological alignment and Explicit Memory Control for Advanced Role-Playing LLMs
by: Cheng, Xilong, et al.
Published: (2025)

KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection
by: Spiegel, Michal, et al.
Published: (2024)

Stage-wise Fine-tuning for Graph-to-Text Generation
by: Wang, Qingyun, et al.
Published: (2021)

ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models
by: Luo, Haoran, et al.
Published: (2023)

A Lightweight Framework for Trigger-Guided LoRA-Based Self-Adaptation in LLMs
by: Wei, Jiacheng, et al.
Published: (2025)

Progtuning: Progressive Fine-tuning Framework for Transformer-based Language Models
by: Ji, Xiaoshuang, et al.
Published: (2025)

Identity Lock: Locking API Fine-tuned LLMs With Identity-based Wake Words
by: Su, Hongyu, et al.
Published: (2025)

FineTuneBench: How well do commercial fine-tuning APIs infuse knowledge into LLMs?
by: Wu, Eric, et al.
Published: (2024)

KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs
by: Xu, Yongqin, et al.
Published: (2024)

Maastricht University at AMIYA: Adapting LLMs for Dialectal Arabic using Fine-tuning and MBR Decoding
by: Alali, Abdulhai, et al.
Published: (2026)

Increasing the Robustness of the Fine-tuned Multilingual Machine-Generated Text Detectors
by: Macko, Dominik, et al.
Published: (2025)

Generation Meets Verification: Accelerating Large Language Model Inference with Smart Parallel Auto-Correct Decoding
by: Yi, Hanling, et al.
Published: (2024)

MTUncertainty: Assessing the Need for Post-editing of Machine Translation Outputs by Fine-tuning OpenAI LLMs
by: Gladkoff, Serge, et al.
Published: (2023)

Multitask Mayhem: Unveiling and Mitigating Safety Gaps in LLMs Fine-tuning
by: Jan, Essa, et al.
Published: (2024)

Federated Co-tuning Framework for Large and Small Language Models
by: Fan, Tao, et al.
Published: (2024)

RLSF: Fine-tuning LLMs via Symbolic Feedback
by: Jha, Piyush, et al.
Published: (2024)

A Comparison of Independent and Joint Fine-tuning Strategies for Retrieval-Augmented Generation
by: Lawton, Neal Gregory, et al.
Published: (2025)

Safety Anchor: Defending Harmful Fine-tuning via Geometric Bottlenecks
by: Lu, Guoxin, et al.
Published: (2026)

60 Data Points are Sufficient to Fine-Tune LLMs for Question-Answering
by: Ye, Junjie, et al.
Published: (2024)

Is Depth All You Need? An Exploration of Iterative Reasoning in LLMs
by: Wu, Zongqian, et al.
Published: (2025)

EpiCoder: Encompassing Diversity and Complexity in Code Generation
by: Wang, Yaoxiang, et al.
Published: (2025)

Breaking Thought Patterns: A Multi-Dimensional Reasoning Framework for LLMs
by: Tang, Xintong, et al.
Published: (2025)

On Active Privacy Auditing in Supervised Fine-tuning for White-Box Language Models
by: Sun, Qian, et al.
Published: (2024)

LinguIUTics at PsyDefDetect: Iterative Imbalance-Aware Fine-tuning of Qwen3-8B for Psychological Defense Mechanism Classification
by: Adib, Shefayat E Shams, et al.
Published: (2026)