Seth Bernstein

Computer Science Applications · 2022–2023

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Seth Bernstein trusts overall

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

  1. Philip J. Guo
  2. Paul Denny

Papers from Seth Bernstein's perspective

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

  1. Evaluating Large Language Models Trained on Code (arXiv.org)
  2. Further evidence of a relationship between explaining, tracing and writing skills in introductory programming
  3. Program Synthesis with Large Language Models
  4. Going SOLO to assess novice programmers
  5. An Australasian study of reading and comprehension skills in novice programmers, using the bloom and SOLO taxonomies
  6. Automatic Generation of Programming Exercises and Code Explanations Using Large Language Models
  7. The Robots Are Coming: Exploring the Implications of OpenAI Codex on Introductory Programming
  8. Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language
  9. Code comprehension problems as learning events
  10. Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Their papers