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..
Targeted Data Acquisition for Evolving Negotiation Agents
Authors: Minae Kwon, Siddharth Karamcheti, Mariano-Florentino Cuellar, Dorsa Sadigh
ICML 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We evaluate Alice subject to these desiderata through experiments against simulated and real-human partners. |
| Researcher Affiliation | Academia | 1Department of Computer Science, Stanford University, Stanford, CA 2School of Law, Stanford University, Stanford, CA. |
| Pseudocode | No | The paper describes methods in text but does not include any explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain an explicit statement about releasing open-source code for the described methodology or a link to a code repository. |
| Open Datasets | Yes | We evaluate our framework on the DEALORNODEAL negotiation task (Lewis et al., 2017) |
| Dataset Splits | No | The paper mentions using specific datasets (DL, DH) for training and evaluation against an expert, and reports results over random seeds, but does not provide explicit numerical train/validation/test splits (e.g., percentages or exact counts) to reproduce the data partitioning. |
| Hardware Specification | No | The paper does not specify the exact GPU/CPU models, processor types, or memory amounts used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for software components or libraries used in the experiments. |
| Experiment Setup | No | The paper states, "Implementation details can be found in the supplementary." (Section 4) but does not provide specific hyperparameters or system-level training settings in the main text. |