Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Position: Contextual Integrity is Inadequately Applied to Language Models
Authors: Yan Shvartzshnaider, Vasisht Duddu
ICML 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | This position paper argues that existing literature inadequately applies CI for LLMs without embracing the theory s fundamental tenets. |
| Researcher Affiliation | Academia | 1York University 2University of Waterloo. Correspondence to: Yan Shvartzshnaider <EMAIL>, Vasisht Duddu <EMAIL>. |
| Pseudocode | No | The paper describes theoretical concepts and critiques methodologies, but does not present any structured pseudocode or algorithm blocks. |
| Open Source Code | No | The paper is a position paper and does not describe a methodology for which open-source code would typically be provided or referenced. |
| Open Datasets | No | The paper is a position paper that critiques existing research on Contextual Integrity for LLMs and does not present new experimental results requiring a specific dataset. |
| Dataset Splits | No | As the paper does not present new experimental results, there is no mention of dataset splits for training, validation, or testing. |
| Hardware Specification | No | The paper focuses on theoretical arguments and critiques of existing literature; it does not describe experimental procedures that would require specific hardware specifications. |
| Software Dependencies | No | The paper is a theoretical position paper and does not detail any experimental implementation requiring specific software dependencies or their version numbers. |
| Experiment Setup | No | The paper presents a theoretical position and critique of existing work, rather than conducting new experiments, thus no experimental setup details such as hyperparameters are provided. |