Nasser Giacaman
Information Systems · 2022
A researcher in the Science corpus: 1 paper; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Information Systems — 10 citations into it
- Large Language Models — 8 citations into it
- Code Generation & Program Synthesis — 6 citations into it
Whom Nasser Giacaman trusts
Their strongest outbound trust, strongest first, inferred from their citations.
- Paul Denny (in Computer Science Applications)
- Juho Leinonen (in Computer Science Applications)
- Arto Hellas (in Computer Science Applications)
- Sami Sarsa (in Computer Science Applications)
Papers from Nasser Giacaman's perspective
Ordered by how strongly the researchers Nasser Giacaman trusts endorse each paper. Same corpus, a different order for every researcher.
- Evaluating Large Language Models Trained on Code (arXiv.org)
- Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm
- On the Opportunities and Risks of Foundation Models
- The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming
- Program Synthesis with Large Language Models
- Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models
- Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing
- Robosourcing Educational Resources - Leveraging Large Language Models for Learnersourcing
- On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜
- Understanding the Capabilities, Limitations, and Societal Impact of Large Language Models