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Found 7 papers, 3 papers with code
Can Pre-trained Language Models Understand Chinese Humor?
Humor understanding is an important and challenging research in natural language processing.
Enhancing Quantitative Reasoning Skills of Large Language Models through Dimension Perception
Hence, we present a framework to enhance the quantitative reasoning ability of language models based on dimension perception.
HAUSER: Towards Holistic and Automatic Evaluation of Simile Generation
Similes play an imperative role in creative writing such as story and dialogue generation.
Open Set Relation Extraction via Unknown-Aware Training
Inspired by text adversarial attacks, we adaptively apply small but critical perturbations to original training instances and thus synthesizing negative instances that are more likely to be mistaken by the model as known relations.
Farewell to Aimless Large-scale Pretraining: Influential Subset Selection for Language Model
Pretrained language models have achieved remarkable success in various natural language processing tasks.
Learning "O" Helps for Learning More: Handling the Concealed Entity Problem for Class-incremental NER
In this work, we conduct an empirical study on the "Unlabeled Entity Problem" and find that it leads to severe confusion between "O" and entities, decreasing class discrimination of old classes and declining the model's ability to learn new classes.
Context-aware Ensemble of Multifaceted Factorization Models for Recommendation Prediction in Social Networks
This paper describes the solution of Shanda Innovations team to Task 1 of KDD-Cup 2012.
