Introduction

The model is used to evaluate the quality of a candidate patent claim compared to the gold claim.

Example Usage

from transformers import AutoModel, AutoTokenizer
import torch 

device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
tokenizer = AutoTokenizer.from_pretrained("lj408/PatClaimEval-Quality", trust_remote_code=True)
model = AutoModel.from_pretrained("lj408/PatClaimEval-Quality", trust_remote_code=True).to(device)
gold_claim = "1. A computer-implemented method comprising: identifying a primary code segment; ..."
candidate_claim = "1. A computer-implemented method for managing logger source code segments in a source code development platform, ..."
res = model.score_pair(gold_claim, candidate_claim , tokenizer, device)
print(res)

Note that this evaluation method can serve as a reference, but it may not be accurate in all cases. Users should rely on evaluations by patent professionals for more precise results.

Citation

If you use this model or code, please cite our paper:

@article{jiang2025towards,
  title={Towards Better Evaluation for Generated Patent Claims},
  author={Jiang, Lekang and Scherz, Pascal A and Goetz, Stephan},
  journal={arXiv preprint arXiv:2505.11095},
  year={2025}
}
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