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+Distilbert finetuned for Aspect-Based Sentiment Analysis (ABSA) with auxiliary sentence.
+
+```bibtex
+@inproceedings{sun-etal-2019-utilizing,
+    title = "Utilizing {BERT} for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence",
+    author = "Sun, Chi  and
+      Huang, Luyao  and
+      Qiu, Xipeng",
+    booktitle = "Proceedings of the 2019 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)",
+    month = jun,
+    year = "2019",
+    address = "Minneapolis, Minnesota",
+    publisher = "Association for Computational Linguistics",
+    url = "https://www.aclweb.org/anthology/N19-1035",
+    doi = "10.18653/v1/N19-1035",
+    pages = "380--385",
+    abstract = "Aspect-based sentiment analysis (ABSA), which aims to identify fine-grained opinion polarity towards a specific aspect, is a challenging subtask of sentiment analysis (SA). In this paper, we construct an auxiliary sentence from the aspect and convert ABSA to a sentence-pair classification task, such as question answering (QA) and natural language inference (NLI). We fine-tune the pre-trained model from BERT and achieve new state-of-the-art results on SentiHood and SemEval-2014 Task 4 datasets. The source codes are available at https://github.com/HSLCY/ABSA-BERT-pair.",
+}
+```