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..
Learning to Compose Soft Prompts for Compositional Zero-Shot Learning
Authors: Nihal V. Nayak, Peilin Yu, Stephen Bach
ICLR 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 5 EXPERIMENTAL EVALUATION In this section, we describe our experiments with CSP . We compare CSP to CLIP-based baselines in the closed-world and open-world settings of compositional zero-shot learning. |
| Researcher Affiliation | Academia | Nihal V. Nayak , Peilin Yu , Stephen H. Bach Department of Computer Science Brown University Providence, RI 02906, USA EMAIL |
| Pseudocode | Yes | F PSEUDOCODE Figure 6 shows the Torch-like pseudocode for inference with CSP. |
| Open Source Code | Yes | The code is available at https://github.com/Bats Research/csp. |
| Open Datasets | Yes | We experiment with three attribute-object composition benchmarks: MIT-states (Isola et al., 2015), UT-Zappos (Yu & Grauman, 2014), and C-GQA (Naeem et al., 2021). |
| Dataset Splits | Yes | Table 1: Summary statistics of the datasets used in our experiments. |
| Hardware Specification | Yes | We use a single NVIDIA RTX 3090 or V100 GPU depending on their availability to train all our models. |
| Software Dependencies | No | The paper mentions 'Py Torch' but does not specify a version number or other key software dependencies with their versions. |
| Experiment Setup | Yes | We train CSP and Co Op by minimizing the cross entropy loss with the Adam optimizer over the seen split in the dataset for 20 epochs. |