Results 151 to 160 of about 14,560 (254)
AIpom at SemEval-2024 Task 8: Detecting AI-produced Outputs in M4 [PDF]
arXivThis paper describes AIpom, a system designed to detect a boundary between human-written and machine-generated text (SemEval-2024 Task 8, Subtask C: Human-Machine Mixed Text Detection). We propose a two-stage pipeline combining predictions from an instruction-tuned decoder-only model and encoder-only sequence taggers.
arxiv
SNU_IDS at SemEval-2019 Task 3: Addressing Training-Test Class Distribution Mismatch in Conversational Classification [PDF]
arXiv, 2019 We present several techniques to tackle the mismatch in class distributions between training and test data in the Contextual Emotion Detection task of SemEval 2019, by extending the existing methods for class imbalance problem. Reducing the distance between the distribution of prediction and ground truth, they consistently show positive effects on the ...
arxiv
UBC-NLP at SemEval-2019 Task 6:Ensemble Learning of Offensive Content With Enhanced Training Data [PDF]
arXiv, 2019 We examine learning offensive content on Twitter with limited, imbalanced data. For the purpose, we investigate the utility of using various data enhancement methods with a host of classical ensemble classifiers. Among the 75 participating teams in SemEval-2019 sub-task B, our system ranks 6th (with 0.706 macro F1-score).
arxiv
Learning for clinical named entity recognition without manual annotations
Informatics in Medicine Unlocked, 2018 Background: Named entity recognition (NER) systems are commonly built using supervised methods that use machine learning to learn from corpora manually annotated with named entities.
Omid Ghiasvand, Rohit J. Kate
doaj
UTH_CCB: A report for SemEval 2014 – Task 7 Analysis of Clinical Text [PDF]
, 2014 Yaoyun Zhang +6 more
openalex +1 more source
SemEval 2015 Task 18: Broad-Coverage Semantic Dependency Parsing [PDF]
, 2015 Stephan Oepen +7 more
openalex +1 more source
SENTENCE REPRESENTATION USING LSTM FOR FINDING QUESTION
Tạp chí Khoa họcLearning sentence representation with the full semantics of a document is a challenge in natural language processing problems because if the semantic representation vector of the sentence is suitable, it will increase the performance of finding similar ...
Dinh Khanh Linh, Tran Quang Huy
doaj +1 more source
SemEval-2015 Task 1: Paraphrase and Semantic Similarity in Twitter (PIT) [PDF]
, 2015 Wei Xu, Chris Callison-Burch, Bill Dolan
openalex +1 more source