0xtotem / automated-audit-papers

Compiling deep learning research papers applied to smart contract analysis

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You will find below a list of papers related to static code analysis done by deep learning models (especially LLM). You are welcome to contribute.


Title Org Thread / Article / Video / Podcasts Date
Mistral 7B Mistral AI Official blog post 10-2023
Retrieval meets Long Context Large Language Models NVIDIA @omarsar0 10-2023
CodePlan: Repository-level Coding using LLMs and Planning Microsoft Research 09-2023
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models CHUK, MIT 09-2023
XGen-7B Technical Report Salesforce Salesforce's blog post 09-2023
Code Llama: Open Foundation Models for Code Meta Meta's blog post 08-2023
Simple synthetic data reduces sycophancy in large language models DeepMind 0xtotem 08-2023
PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback Huawei Cloud, Chinese Academy Of Science, Peking 07-2023
Predicting Code Coverage Execution Microsoft 07-2023
PUMA: Secure Inference of LLaMA-7B in Five Minutes Ant Group (private, Alibaba) Feral Machine 07-2023
On the Origin of LLMs: An Evolutionary Tree and Graph for 15,821 Large Language Models Canyon Crest Academy, Stanford 07-2023
Lost in the Middle: How Language Models Use Long Contexts Stanford, Berkeley Deep Papers 07-2023
Focused Transformer: Contrastive Training for Context Scaling IDEAS NCBR, Deep Mind 07-2023
LongNet: Scaling Transformers to 1,000,000,000 Tokens Microsoft Research 07-2023
Textbooks are all you need Microsoft Research 0xtotem 06-2023
RepoFusion: Training Code Models to Understand Your Repository ServiceNow Research DishaShrivasta9 06-2023
Do you still need a manual smart contract audit? Imperial College London HatforceSec 06-2023
Towards Automated Security Analysis of Smart Contracts based on Execution Property Graph Imperial College London, Berkeley 05-2023
DAppSCAN: Building Large-Scale Datasets for Smart Contract Weaknesses in DApp Projects Sun Yat-sen University 05-2023

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Compiling deep learning research papers applied to smart contract analysis