Credit Attribution and Stable Compression
Authors: Roi Livni, Shay Moran, Kobbi Nissim, Chirag Pabbaraju
NeurIPS 2024 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | The paper does not include experiments. |
| Researcher Affiliation | Collaboration | Tel Aviv University. rlivni@tauex.tau.ac.il. Technion and Google Research. smoran@technion.ac.il. Georgetown University and Google Research. kobbi.nissim@georgetown.edu. Stanford University. cpabbara@cs.stanford.edu. |
| Pseudocode | Yes | Definition 7 (Randomized response). Let RR : {0, 1}π [π]πbe the randomized response selection mechanism defined as follows. Given π₯ {0, 1}π, RR flips each bit of π₯independently with probability 1 1+πΞ΅ to obtain π₯. Let π= {π [π] : π₯π= 1} and π = [π] π. Further, let |π| = π‘. If π‘ π, then RR outputs a uniformly random subset of πindices from π, ordered arbitrarily. Otherwise, it arbitrarily orders π, and outputs π π, where πis a uniformly random subset of π π‘indices chosen from π (and ordered arbitrarily), and denotes concatenation. |
| Open Source Code | No | The paper states in its NeurIPS checklist that it 'does not include experiments requiring code', implying no open-source code for the described methodology is provided. |
| Open Datasets | No | The paper is theoretical and does not report on experiments that would use a training dataset. |
| Dataset Splits | No | The paper is theoretical and does not report on experiments that would use a validation dataset. |
| Hardware Specification | No | The paper is theoretical and does not report on experiments, thus no hardware specifications are provided. |
| Software Dependencies | No | The paper is theoretical and does not report on experiments, thus no specific software dependencies with version numbers are listed. |
| Experiment Setup | No | The paper is theoretical and does not describe any experimental setup or hyperparameters for empirical evaluation. |