ACL2023.md

Year	Title	Author	Publication	Code	Tags	Notes	Tasks	Datasets
2023	The Best of Both Worlds: Combining Human and Machine Translations for Multilingual Semantic Parsing with Active Learning	Li et al.	ACL	-	Multilingual Semantic Parsing	Hybrid, BERT-LSTM, None, PT+FT, Hard	GEOQUERY, NLMAP	Most semantically diversified and representative utterances improves the parser performance to the greatest extent.
2023	Counterfactual Active Learning for Out-of-Distribution Generalization	Deng et al.	ACL	-	Dissonance Detection	Uncertainty, RoBERTa-based, Transfer Learning, PT+FT, Hard	build a dissonance dataset
2023	Transfer and Active Learning for Dissonance Detection: Addressing the Rare-Class Challenge	Vasudha Varadarajan et al.	ACL	-	Sentiment Analysis and Natural language Inference	Informative, RoBERTa, Counterfactual thinking, PT+FT, Hard	IMDB,
2023	Deep Active Learning for Morphophonological Processing	Seyed Morteza Mirbostani et al.	ACL	-	morphological processing	informative, DNNs, None, PT+FT, Hard		Arabic morphophonology dataset
2023	On Dataset Transferability in Active Learning for Transformers	Fran Jelenić et al.	ACL	-	text classification	Uncertainty, PLMs, None, PT+FT, Hard	Subjectivity, CoLA, AG-NEWs, and TREC	We investigate how ASM affects dataset transferability and how ASM is affected by other AL variables.
2023	On the Limitations of Simulating Active Learning	Katerina Margatina et al.	ACL	-		Any, LLMs, None, PT+FT, Hard		Simulating,why do ac- tive learning algorithms sometimes fail to out- perform random sampling
2023	D-CALM: A Dynamic Clustering-based Active Learning Approach for Mitigating Bias	Sabit Hassan et al.	ACL	-	text classification tasks	clustering, PLMs, None, PT+FT, Hard	BOOK32, CONAN, CARER, CoLA, HATE, MRDA, Q-Type, Subjectivity	infusing clustering with AL can overcome the bias issue of both AL and traditional annotation methods while exploit- ing AL’s annotation efficiency.
2023	Which Examples Should be Multiply Annotated? Active Learning When Annotators May Disagree	Connor Baumler et al.	ACL	-	Text Classification	disagreement, PLMs, None, PT+FT, Hard	Measuring Hate Speech (MHS) (Sachdeva et al., 2022) and Wikipedia Talk
2023	Reinforced Active Learning for Low-Resource, Domain-Specific, Multi-Label Text Classification	Lukas Wertz et al.	ACL	-	Text classification	Any, BERT, Reinforcement,PT+FT, Hard	ArXiv, EurLex57k, Patents, Yelp,	Reinforced Active Learning for Low-Resource, Domain-Specific, Multi-Label Text Classification