mlsanityData to 7 Oct 2026

Toward best research practices in AI Psychology

arXiv 2312.01276 ↗First posted 3 Dec 2023cs.AI cs.CLcited by 8

Not on the map. Why?

Abstract (arXiv)

Language models have become an essential part of the burgeoning field of AI Psychology. I discuss 14 methodological considerations that can help design more robust, generalizable studies evaluating the cognitive abilities of language-based AI systems, as well as to accurately interpret the results of these studies.

Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 3 of its 14 references that are in the map. First posted on arXiv 3 Dec 2023.

Builds on

3 of 14 references.

References · 3

  1. 2022Can language models handle recursively nested grammatical structures? A case study on comparing models and humanscited by 41
  2. 2021Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schemacited by 32
  3. 2018How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAGcited by 18

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 6; 2025: 1; 2026: 1.

8 papers.

  1. 2024Evaluating the Robustness of Analogical Reasoning in Large Language Modelscited by 31
  2. 2024How Can LLM Guide RL? A Value-Based Approachcited by 13
  3. 2024What is it for a Machine Learning Model to Have a Capability?cited by 10
  4. 2024Incremental Comprehension of Garden-Path Sentences by Large Language Models: Semantic Interpretation, Syntactic Re-Analysis, and Attentioncited by 10
  5. 2024Leaving the barn door open for Clever Hans: Simple features predict LLM benchmark answerscited by 9
  6. 2024Do Large Language Models Solve ARC Visual Analogies Like People Do?cited by 7
  7. 2026On the Context Sensitivity of LLM Moral Judgmentcited by 3
  8. 2025What Makes an Evaluation Useful? Common Pitfalls and Best Practicescited by 1