Fetching the paper…
Reading the bibliography…
Generating code via a LLM (rather than writing code from scratch), has exploded in popularity.
A complexity measure
Thomas J. McCabe · 1976
Earlier work this paper cites.
Reinforcement learning: A survey
L. P. Kaelbling, M. L. Littman, and A. W. Moore · 1996
Earlier work this paper cites.
Code completion with statistical language models
V. Raychev, M. Vechev, and E. Yahav · 2014
Earlier work this paper cites.
Deep reinforcement learning from human preferences
P. F. Christiano, J. Leike, T. Brown, M. Martic, S. Legg, and D. Amodei · 2017
Earlier work this paper cites.
Communication-efficient learning of deep networks from decentralized data
B. McMahan, E. Moore, D. Ramage, S. Hampson, and B. A. y Arcas · 2017
Earlier work this paper cites.
Reinforcement learning: an introduction
R. S. Sutton and A. G. Barto · 2018
Earlier work this paper cites.
https://github.com/google/AFL , 2021
american fuzzy lop · 2021
Earlier work this paper cites.
Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing, 2021
P. Liu, W. Yuan, J. Fu, Z. Jiang, H. Hayashi, and G. Neubig · 2021
Earlier work this paper cites.
You autocomplete me: Poisoning vulnerabilities in neural code completion
R. Schuster, C Song, E Tromer, and V Shmatikov · 2021
Earlier work this paper cites.
Differential privacy for text analytics via natural text sanitization
X. Yue, M. Du, T. Wang, Y. Li, H. Sun, and S. S. M. Chow · 2021
Earlier work this paper cites.
https://github.blog/2022-09-07-research-quantifying-github -copilots-impact-on-developer-productivity -and-happiness , 2022
Research: quantifying GitHub Copilot’s impact on developer productivity and happiness · 2022
Earlier work this paper cites.
Asleep at the keyboard? assessing the security of github copilot’s code contributions
H. Pearce, B. Ahmad, B. Tan, B. Dolan-Gavitt, and R. Karri · 2022
Earlier work this paper cites.
Expectation vs. experience: Evaluating the usability of code generation tools powered by large language models
P. Vaithilingam, T. Zhang, and E. L. Glassman · 2022
Earlier work this paper cites.
https://www.whitehouse.gov/briefing-room/presidential-actions/2023/10/30/executive-order-on-the-safe-secure-and- trustworthy-development-and-use-of -artificial-intelligence/ , 2023
Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence · 2023
Earlier work this paper cites.
https://www.freethink.com/robots-ai/github-copilot , 2023
GitHub CEO says Copilot will write 80% of code “sooner than later” · 2023
Earlier work this paper cites.
https://github.blog/ai-and-ml/github-copilot/github-copilot-now-has-a-better-ai-model -and-new-capabilities , 2023
GitHub Copilot now has a better AI model and new capabilities · 2023
Earlier work this paper cites.
Purple llama cyberseceval: A secure coding benchmark for language models, 2023
M. Bhatt, S Chennabasappa, C. Nikolaidis, S Wan, I Evtimov, D. Gabi, D. Song, F. Ahmad, C. Aschermann, L. Fontana, S. Frolov, R. P. Giri, D. Kapil, Y Kozyrakis, D. LeBlanc, J. Milazzo, A. Straumann, G. Synnaeve, V. Vontimitta, S. Whitman, and J. Saxe · 2023
Earlier work this paper cites.
Fully autonomous programming with large language models
V. Liventsev, A. Grishina, A. Härmä, and L. Moonen · 2023
Earlier work this paper cites.
Do users write more insecure code with ai assistants?
N. Perry, M. Srivastava, D. Kumar, and D. Boneh · 2023
Cited alongside, same era.
https://aws.amazon.com/q/developer , 2024
AI Coding Assistant - Amazon Q Developer · 2024
Cited alongside, same era.
https://www.anthropic.com/news/claude-3-5-sonnet , 2024
Anthropic Claude 3.5 Sonnet · 2024
Cited alongside, same era.
https://cunit.sourceforge.net/index.html , 2024
CUnit · 2024
Cited alongside, same era.
https://www.nist.gov/artificial-intelligence/executive-order-safe-secure-and-trustworthy -artificial-intelligence , 2024
EXECUTIVE ORDER ON SAFE, SECURE, AND TRUSTWORTHY ARTIFICIAL INTELLIGENCE | NIST · 2024
Cited alongside, same era.
https://github.com/fragglet/c-algorithms , 2024
fragglet/c-algorithms · 2024
Cited alongside, same era.
https://github.com/openbsd/src , 2024
OpenBSD · 2024
Closest in time.
https://github.com/petewarden/c_hashmap , 2024
petewarden/c_hashmap · 2024
Closest in time.
https://github.com/boyter/scc , 2024
SCC · 2024
Closest in time.
https://github.blog/news-insights/research/survey-reveals-ais-impact-on-the-developer -experience , 2024
Survey reveals AI’s impact on the developer experience · 2024
Closest in time.
https://github.com/TheAlgorithms/C , 2024
The Algorithms/C · 2024
Closest in time.
Casper: Prompt sanitization for protecting user privacy in web-based large language models, 2024
C. J. Chong, C. Hou, Z. Yao, and S. M. Seyed Talebi · 2024
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
https://cloud.google.com/products/gemini/code-assist , 2024
Gemini Code Assist · 2024
Cited alongside, same era.
https://github.com/features/copilot , 2024
GitHub Copilot - Your AI pair programmer · 2024
Cited alongside, same era.
https://akvelon.com/github-copilot-efficiency-survey-data- revealed-akvelon/ , 2024
GitHub Copilot Efficiency Explored: Key Takeaways from Akvelon’s Survey · 2024
Cited alongside, same era.
https://github.blog/changelog/2024-07-05-github-copilot-enterprise-on-gpt-4o , 2024
GitHub Copilot Enterprise on GPT-4o · 2024
Cited alongside, same era.
https://githubnext.com/projects/copilot-voice , 2024
GitHub Copilot Voice - Write code without the keyboard · 2024
Cited alongside, same era.
https://openai.com/index/hello-gpt-4o/ , 2024
Hello GPT-4o · 2024
Cited alongside, same era.
Unprecedented code change automation: The fusion of llms and transformation by example
M. Dilhara, A. Bellur, T. Bryksin, and D. Dig · 2024
Closest in time.
Formalizing and benchmarking prompt injection attacks and defenses
Y. Liu, Y. Jia, R. Geng, J. Jia, and N. Z. Gong · 2024
Closest in time.
Llm critics help catch llm bugs
Nat McAleese, Rai Michael Pokorny, Juan Felipe Ceron Uribe, Evgenia Nitishinskaya, Maja Trebacz, and Jan Leike · 2024
Closest in time.
Lost in translation: A study of bugs introduced by large language models while translating code
R. Pan, A. R. Ibrahimzada, R. Krishna, D. Sankar, L. P. Wassi, M. Merler, B. Sobolev, R. Pavuluri, S. Sinha, and R. Jabbarvand · 2024
Closest in time.
Jatmo: Prompt injection defense by task-specific finetuning, 2024
J. Piet, M. Alrashed, C. Sitawarin, S. Chen, Z. Wei, E. Sun, B Alomair, and D. Wagner · 2024
Closest in time.
Mathematical discoveries from program search with large language models
B. Romera-Paredes, M. Barekatain, A. Novikov, M. Balog, M. P. Kumar, E. Dupont, F. J. R. Ruiz, J. S. Ellenberg, P. Wang, O. Fawzi, et al · 2024
Closest in time.
The fire thief is also the keeper: Balancing usability and privacy in prompts
Z. Shen, Z. Xi, Y. He, W. Tong, J. Hua, and S. Zhong · 2024
Closest in time.
Investigating and designing for trust in ai-powered code generation tools
R. Wang, R. Cheng, D. Ford, and T. Zimmermann · 2024
Closest in time.
An llm-assisted easy-to-trigger backdoor attack on code completion models: Injecting disguised vulnerabilities against strong detection, 2024
S. Yan, S Wang, Y Duan, H Hong, K. Lee, D. Kim, and Y. Hong · 2024
Closest in time.
Rectifier: Code translation with corrector via llms
X. Yin, C. Ni, T. N. Nguyen, S. Wang, and X. Yang · 2024
Closest in time.
Cybench: A framework for evaluating cybersecurity capabilities and risk of language models
A. K. Zhang, N. Perry, R. Dulepet, E. Jones, J. W. Lin, J. Ji, C. Menders, G. Hussein, S. Liu, D. Jasper, et al · 2024
Closest in time.