Notice: This website is continuously updated as new conference proceedings and journal volumes are published. Consequently, the figures presented here may differ from those reported in our publications.
A brief overview of our methodology is provided on the Methods page, along with references to publications documenting our approach and links to the code and data used in each study.
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.
High-Dimensional Calibration from Swap Regret
Authors: Maxwell Fishelson, Noah Golowich, Mehryar Mohri, Jon Schneider
NeurIPS 2025 | Venue PDF | LLM Run Details | Input Tokens: 30,471 Total number of tokens sent to the LLM as input for this paper's analysis. | Output Tokens: 3,059 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 | Answer: [Yes] Justiļ¬cation: We prove all theorems and lemmas. Guidelines: The answer NA means that the paper does not include theoretical results. All the theorems, formulas, and proofs in the paper should be numbered and crossreferenced. |
| Researcher Affiliation | Collaboration | Maxwell Fishelson EMAIL Noah Golowich EMAIL Mehryar Mohri EMAIL Jon Schneider EMAIL MIT. MIT. Supported by a NSF Graduate Research Fellowship and a Fannie & Hertz Foundation Graduate Fellowship. Google Research and Courant Institute of Mathematical Sciences, New York. Google Research. |
| Pseudocode | Yes | Algorithm 1 Tree Cal(P, T, H, L) [...] Algorithm 2 Tree Swap.Alg(P, L, T, H, L), labeled variant (see Appendix C.1) |
| Open Source Code | No | Answer: [NA] Justiļ¬cation: The paper does not include experiments requiring code. |
| Open Datasets | No | Answer: [NA] Justiļ¬cation: The paper does not include experiments. |
| Dataset Splits | No | Answer: [NA] Justiļ¬cation: The paper does not include experiments. |
| Hardware Specification | No | Answer: [NA] Justiļ¬cation: The paper does not include experiments. |
| Software Dependencies | No | Answer: [NA] Justiļ¬cation: The paper does not include experiments. |
| Experiment Setup | No | Answer: [NA] Justiļ¬cation: The paper does not include experiments. |