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..
Reprogramming Pretrained Language Models for Antibody Sequence Infilling
Authors: Igor Melnyk, Vijil Chenthamarakshan, Pin-Yu Chen, Payel Das, Amit Dhurandhar, Inkit Padhi, Devleena Das
ICML 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Results on antibody design benchmarks show that our model on low-resourced antibody sequence dataset provides highly diverse CDR sequences, up to more than a two-fold increase of diversity over the baselines, without losing structural integrity and naturalness. |
| Researcher Affiliation | Collaboration | 1IBM Research, Yorktown Heights, NY 10598, USA. 2Georgia Institute of Technology, Atlanta, GA 30332, USA. |
| Pseudocode | No | The paper does not contain any pseudocode or clearly labeled algorithm blocks. |
| Open Source Code | Yes | Code is available at https://github. com/IBM/Reprog BERT |
| Open Datasets | Yes | Structural Antibody Database (Sab Dab) (Dunbar et al., 2013) and Rosetta Antibody Design (Rab D) (Jin et al., 2021), and Co V-Ab Dab dataset (Raybould et al., 2021) |
| Dataset Splits | Yes | Table 2. Statistics of the Structural Antibody Database (Sab Dab) for the training, validation and test splits across the three CDRs. |
| Hardware Specification | Yes | We trained all models on a single A100 40GB GPU. |
| Software Dependencies | No | The paper mentions software like BERT, Alpha Fold, Ig Fold, and Pro Gen, but does not provide specific version numbers for these or any other software dependencies. |
| Experiment Setup | Yes | Learning rate 1e-5 Batch size 32 Optimizer Adam |