metadata
language: en
license: apache-2.0
base_model: allenai/scibert_scivocab_uncased
pipeline_tag: text-classification
library_name: transformers
tags:
- scientific-text
- citation-intent
datasets:
- allenai/multicite
- allenai/scicite
widget:
- text: Deep learning has achieved remarkable success in many NLP tasks [1, 2].
example_title: Background citation
- text: We adopt the evaluation protocol proposed by Smith et al. (2020).
example_title: Non-background citation
SciBERT Citation-Background Classifier
allenai/scibert_scivocab_uncased fine-tuned as a binary classifier of citation intent: does a citation sentence cite prior work as background (BACKGROUND) or for any other reason (NOT_BACKGROUND)?
Labels
| id | label | meaning |
|---|---|---|
| 0 | NOT_BACKGROUND | citation used for method, comparison, extension, motivation… |
| 1 | BACKGROUND | citation provides background/context for the citing paper |
How to use
from transformers import pipeline
clf = pipeline("text-classification", model="hongccccccc/scibert-citation-background-classifier")
clf("Deep learning has achieved remarkable success in many NLP tasks [1, 2].")
# [{'label': 'BACKGROUND', 'score': ...}]
Training
- Base model: SciBERT (uncased, scivocab;
BertForSequenceClassification, single-label, 2 classes) - Data: the combined annotated citation contexts of SciCite (Cohan et al., 2019) and MultiCite (Lauscher et al., 2022) — 27,052 instances, 11,635 (43%) labeled
BACKGROUND - Fine-tuned: August 2023,
transformers4.32.0
Evaluation
F1 score of 0.81 on a held-out test set (80-20 train-test split of the combined dataset).