Teo Nys

Software Engineering · 2022

A researcher in the Science corpus: 1 paper; trusts 1 researcher and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Software Engineering — 12 citations into it
• Code Generation & Program Synthesis — 11 citations into it
• Human-Computer Interaction — 5 citations into it

Whom Teo Nys trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Saki Imai

Papers from Teo Nys's perspective

Ordered by how strongly the researchers Teo Nys trusts endorse each paper. Same corpus, a different order for every researcher.

1. Evaluating Large Language Models Trained on Code (arXiv.org)
2. Language Models are Few-Shot Learners (Neural Information Processing Systems)
3. Language Models are Unsupervised Multitask Learners
4. CodeBERT: A Pre-Trained Model for Programming and Natural Languages
5. Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions
6. A new algorithm for data compression
7. A Conversational Paradigm for Program Synthesis
8. Expectation vs. Experience: Evaluating the Usability of Code Generation Tools Powered by Large Language Models
9. The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming
10. AddressSanitizer: A Fast Address Sanity Checker

Their papers

• Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants (2022) — 184 citations