AAP-SQL candidate reranker is the cross-encoder used after the first stage of schema retrieval. It scores the retrieved candidate columns and retains the top 10 core columns for prompt augmentation.

Model details

Base model: cross-encoder/ms-marco-MiniLM-L6-v2
Training objective: BinaryCrossEntropyLoss
Training seed: 42
Training data: schema-ranking examples derived from the BIRD training split and schema descriptions
Expected library: sentence-transformers>=5.1.2

AAP-SQL publication branch

The complete AAP-SQL workflow, research method terminology, BIRD directory layout, and reproduction instructions are maintained in the GitHub publication branch.

Use with AAP-SQL

Download this repository into the path expected by the final runner:

hf download TommyPanLab/AAP-SQL-Candidate-Reranker --local-dir models/cross_encoder_schema_paper_repro

Direct loading:

python

from sentence_transformers import CrossEncoder

model = CrossEncoder("TommyPanLab/AAP-SQL-Candidate-Reranker")
scores = model.predict([ ("user question", "table.column: column description") ])

Data and license notice

The training examples were derived from the BIRD benchmark. Review the BIRD project terms before using the model. No additional license has been declared for these fine-tuned weights; the upstream model and dataset terms still apply.