Cover Image

Faver: Boosting LLM-based RTL Generation with Function Abstracted Verifiable Middleware

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mu, Jianan, Shi, Mingyu, Wang, Yining, Yang, Tianmeng, Sun, Bin, Hu, Xing, Ye, Jing, Li, Huawei
Format:	Preprint
Published:	2025
Subjects:	Software Engineering Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FormalRTL: Verified RTL Synthesis at Scale
by: Li, Kezhi, et al.
Published: (2026)

Towards Verifiably Safe Tool Use for LLM Agents
by: Doshi, Aarya, et al.
Published: (2026)

Boosting Static Resource Leak Detection via LLM-based Resource-Oriented Intention Inference
by: Wang, Chong, et al.
Published: (2023)

MeltRTL: Multi-Expert LLMs with Inference-time Intervention for RTL Code Generation
by: Mashnoor, Nowfel, et al.
Published: (2026)

UVMarvel: an Automated LLM-aided UVM Machine for Subsystem-level RTL Verification
by: Ye, Junhao, et al.
Published: (2026)

Boosting Pointer Analysis With LLM-Enhanced Allocation Function Detection
by: Cheng, Baijun, et al.
Published: (2025)

Verify Implementation Equivalence of Large Models
by: Zhan, Qi, et al.
Published: (2026)

Exascale Workflow Applications and Middleware: An ExaWorks Retrospective
by: Alsaadi, Aymen, et al.
Published: (2024)

RTLSeek: Boosting the LLM-Based RTL Generation with Multi-Stage Diversity-Oriented Reinforcement Learning
by: Zhang, Xinyu, et al.
Published: (2026)

Enhancing LLM-based Fault Localization with a Functionality-Aware Retrieval-Augmented Generation Framework
by: Shi, Xinyu, et al.
Published: (2025)

MEIC: Re-thinking RTL Debug Automation using LLMs
by: Xu, Ke, et al.
Published: (2024)

Assessing the Impact of Requirement Ambiguity on LLM-based Function-Level Code Generation
by: Yang, Di, et al.
Published: (2026)

ExecVerify: White-Box RL with Verifiable Stepwise Rewards for Code Execution Reasoning
by: Tang, Lingxiao, et al.
Published: (2026)

IncreRTL: Traceability-Guided Incremental RTL Generation under Requirement Evolution
by: Chen, Luanrong, et al.
Published: (2026)

Towards a Middleware for Large Language Models
by: Guran, Narcisa, et al.
Published: (2024)

Type-aware LLM-based Regression Test Generation for Python Programs
by: Liu, Runlin, et al.
Published: (2025)

BugGen: A Self-Correcting Multi-Agent LLM Pipeline for Realistic RTL Bug Synthesis
by: Jasper, Surya, et al.
Published: (2025)

EXPEREPAIR: Dual-Memory Enhanced LLM-based Repository-Level Program Repair
by: Mu, Fangwen, et al.
Published: (2025)

Learning to Debug: LLM-Organized Knowledge Trees for Solving RTL Assertion Failures
by: Bai, Yunsheng, et al.
Published: (2025)

Benchmarking and Studying the LLM-based Code Review
by: Zeng, Zhengran, et al.
Published: (2025)

Vextra: A Unified Middleware Abstraction for Heterogeneous Vector Database Systems
by: Suri, Chandan, et al.
Published: (2026)

Detect Repair Verify for Securing LLM Generated Code: A Multi-Language Empirical Study
by: Cheng, Cheng
Published: (2026)

On Reasoning-Centric LLM-based Automated Theorem Proving
by: Sun, Yican, et al.
Published: (2026)

Detect--Repair--Verify for LLM-Generated Code: A Multi-Language, Multi-Granularity Empirical Study
by: Cheng, Cheng
Published: (2026)

A Comparison of ROS 2 and AUTOSAR Adaptive Platform Against Industry-Elicited Automotive Middleware Requirements
by: Hegerath, Lucas, et al.
Published: (2026)

CodeDPO: Aligning Code Models with Self Generated and Verified Source Code
by: Zhang, Kechi, et al.
Published: (2024)

STALL+: Boosting LLM-based Repository-level Code Completion with Static Analysis
by: Liu, Junwei, et al.
Published: (2024)

Enhancing LLM-based Specification Generation via Program Slicing and Logical Deletion
by: Chen, Zehan, et al.
Published: (2025)

LLM-based Unit Test Generation via Property Retrieval
by: Zhang, Zhe, et al.
Published: (2024)

SlsReuse: LLM-Powered Serverless Function Reuse
by: Wen, Jinfeng, et al.
Published: (2025)

Beyond Basic Specifications? A Systematic Study of Logical Constructs in LLM-based Specification Generation
by: Chen, Zehan, et al.
Published: (2026)

Verifying LLM-Generated Code in the Context of Software Verification with Ada/SPARK
by: Cramer, Marcos, et al.
Published: (2025)

Using LLMs to Facilitate Formal Verification of RTL
by: Orenes-Vera, Marcelo, et al.
Published: (2023)

INSTILLER: Towards Efficient and Realistic RTL Fuzzing
by: Zhang, Gen, et al.
Published: (2024)

VeriCoder: Enhancing LLM-Based RTL Code Generation through Functional Correctness Validation
by: Wei, Anjiang, et al.
Published: (2025)

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

Are They All Good? Evaluating the Quality of CoTs in LLM-based Code Generation
by: Zhang, Binquan, et al.
Published: (2025)

Generating Mitigations for Downstream Projects to Neutralize Upstream Library Vulnerability
by: Chen, Zirui, et al.
Published: (2025)

Talk Less, Verify More: Improving LLM Assistants with Semantic Checks and Execution Feedback
by: Sun, Yan, et al.
Published: (2026)

Boosting LLMs for Mutation Generation
by: Wang, Bo, et al.
Published: (2026)