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 Shift Toward Open and Reproducible AI Research," Under Review, 2026. doi: 10.48550/arXiv.2606.16974..
The Burden of Interactive Alignment with Inconsistent Preferences
Authors: Ali Shirali
NeurIPS 2025 | Venue PDF | LLM Run Details | Input Tokens: 30,473 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 1,888 Total number of tokens produced by the LLM (including reasoning/thinking tokens) for this paper's analysis.
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | Justification: This is a theory paper. |
| Researcher Affiliation | Academia | Ali Shirali UC Berkeley |
| Pseudocode | No | The paper primarily presents mathematical models, theorems, proofs, and theoretical analysis, without including any explicitly labeled pseudocode or algorithm blocks. The methods are described through equations and logical steps in paragraph form. |
| Open Source Code | No | Answer: [NA] Justification: This is a theory paper. |
| Open Datasets | No | Answer: [NA] Justification: This is a theory paper. |
| Dataset Splits | No | Answer: [NA] Justification: This is a theory paper. |
| Hardware Specification | No | Answer: [NA] Justification: This is a theory paper. |
| Software Dependencies | No | Answer: [NA] Justification: This is a theory paper. |
| Experiment Setup | No | Answer: [NA] Justification: This is a theory paper. |