Cover Image

Your Simulation Runs but Solves the Wrong Physics: PDE-Grounded Intent Verification for LLM-Generated Multiphysics Simulation Code

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Song, Zhenghan, Liu, Yulong, Wan, Cheng, Li, Chenjun, Liu, Lingfu, Li, Yunyi, Yuan, Congcong
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Computation and Language Software Engineering
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Prefix-Safe Bayesian Belief Tracking for LLM Reasoning Reliability:Separating Calibration from Ranking
by: Song, Zhenghan, et al.
Published: (2026)

What's Wrong with Your Code Generated by Large Language Models? An Extensive Study
by: Dou, Shihan, et al.
Published: (2024)

From Context to Intent: Reasoning-Guided Function-Level Code Completion
by: Li, Yanzhou, et al.
Published: (2025)

Articulate but Wrong: Self-Review Failures in LLM-Based Code Modernization
by: Reddy, Gokul Chandra Purnachandra, et al.
Published: (2026)

Choose Your Simulator Wisely: A Review on Open-source Simulators for Autonomous Driving
by: Li, Yueyuan, et al.
Published: (2023)

Demystifying Errors in LLM Reasoning Traces: An Empirical Study of Code Execution Simulation
by: Abdollahi, Mohammad, et al.
Published: (2025)

PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing
by: Zhang, Yuwei, et al.
Published: (2025)

IntentCoding: Amplifying User Intent in Code Generation
by: Fang, Zheng, et al.
Published: (2026)

NeuroSync: Intent-Aware Code-Based Problem Solving via Direct LLM Understanding Modification
by: Zhang, Wenshuo, et al.
Published: (2025)

Bridging the Gap between User Intent and LLM: A Requirement Alignment Approach for Code Generation
by: Li, Jia, et al.
Published: (2026)

Intention is All You Need: Refining Your Code from Your Intention
by: Guo, Qi, et al.
Published: (2025)

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length
by: Cheng, Junhang, et al.
Published: (2025)

AdapTrack: Constrained Decoding without Distorting LLM's Output Intent
by: Li, Yongmin, et al.
Published: (2025)

InteractScience: Programmatic and Visually-Grounded Evaluation of Interactive Scientific Demonstration Code Generation
by: Chen, Qiaosheng, et al.
Published: (2025)

Beyond Function-Level Search: Repository-Aware Dual-Encoder Code Retrieval with Adversarial Verification
by: Liu, Aofan, et al.
Published: (2025)

Structural Anchors and Reasoning Fragility:Understanding CoT Robustness in LLM4Code
by: Liu, Yang, et al.
Published: (2026)

KVerus: Scalable and Resilient Formal Verification Proof Generation for Rust Code
by: Liu, Yuwei, et al.
Published: (2026)

Agentic Scientific Simulation: Execution-Grounded Model Construction and Reconstruction
by: Lie, Knut-Andreas, et al.
Published: (2026)

Synergizing Code Coverage and Gameplay Intent: Coverage-Aware Game Playtesting with LLM-Guided Reinforcement Learning
by: Mu, Enhong, et al.
Published: (2025)

Agents4PLC: Automating Closed-loop PLC Code Generation and Verification in Industrial Control Systems using LLM-based Agents
by: Liu, Zihan, et al.
Published: (2024)

Is Your Benchmark (Still) Useful? Dynamic Benchmarking for Code Language Models
by: Guan, Batu, et al.
Published: (2025)

InfCode-C++: Intent-Guided Semantic Retrieval and AST-Structured Search for C++ Issue Resolution
by: Dong, Qingao, et al.
Published: (2025)

Verification Limits Code LLM Training
by: Gureja, Srishti, et al.
Published: (2025)

A Vulnerability Code Intent Summary Dataset
by: Huang, Yifan, et al.
Published: (2025)

ZeroCoder: Can LLMs Improve Code Generation Without Ground-Truth Supervision?
by: Fan, Lishui, et al.
Published: (2026)

On Simulation-Guided LLM-based Code Generation for Safe Autonomous Driving Software
by: Nouri, Ali, 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)

Does Your Neural Code Completion Model Use My Code? A Membership Inference Approach
by: Wan, Yao, et al.
Published: (2024)

CodeGrad: Integrating Multi-Step Verification with Gradient-Based LLM Refinement
by: Zhang, Yueke, et al.
Published: (2025)

CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging
by: Islam, Md. Ashraful, et al.
Published: (2025)

Framework and Methodology for Verification of a Complex Scientific Simulation Software, Flash-X
by: Dhruv, Akash, et al.
Published: (2023)

Intent Preserving Generation of Diverse and Idiomatic (Code-)Artifacts
by: Westphal, Oliver
Published: (2025)

ReVeal: Self-Evolving Code Agents via Reliable Self-Verification
by: Jin, Yiyang, et al.
Published: (2025)

SolSearch: An LLM-Driven Framework for Efficient SAT-Solving Code Generation
by: Sheng, Junjie, et al.
Published: (2025)

DCE-LLM: Dead Code Elimination with Large Language Models
by: Chen, Minyu, et al.
Published: (2025)

SpecSyn: LLM-based Synthesis and Refinement of Formal Specifications for Real-world Program Verification
by: Ma, Lezhi, et al.
Published: (2026)

Decoding Human-LLM Collaboration in Coding: An Empirical Study of Multi-Turn Conversations in the Wild
by: Zhang, Binquan, et al.
Published: (2025)

SGCR: A Specification-Grounded Framework for Trustworthy LLM Code Review
by: Wang, Kai, et al.
Published: (2025)

CodeMirage: Hallucinations in Code Generated by Large Language Models
by: Agarwal, Vibhor, et al.
Published: (2024)

Designing a Framework for Solving Multiobjective Simulation Optimization Problems
by: Chang, Tyler H., et al.
Published: (2023)