2 citations · 4 across the 3 of their papers we have counts for
5 papers · 1 filter
Self-Knowledge Guided Retrieval Augmentation for Large Language Models
Yile Wang, Peng Li, Maosong Sun +1
Large language models (LLMs) have shown superior performance without task-specific fine-tuning. Despite the success, the knowledge stored in the parameters of LLMs could still be i…
Can Offline Reinforcement Learning Help Natural Language Understanding?
Ziqi Zhang, Yile Wang, Yue Zhang +1
Pre-training has been a useful method for learning implicit transferable knowledge and it shows the benefit of offering complementary features across different modalities. Recent w…
Pre-Training a Graph Recurrent Network for Language Representation
Yile Wang, Linyi Yang, Zhiyang Teng +2
Transformer-based pre-trained models have gained much advance in recent years, becoming one of the most important backbones in natural language processing. Recent work shows that t…
Does Chinese BERT Encode Word Structure?
Yile Wang, Leyang Cui, Yue Zhang
Contextualized representations give significantly improved results for a wide range of NLP tasks. Much work has been dedicated to analyzing the features captured by representative…
How Can BERT Help Lexical Semantics Tasks?
Yile Wang, Leyang Cui, Yue Zhang
Contextualized embeddings such as BERT can serve as strong input representations to NLP tasks, outperforming their static embeddings counterparts such as skip-gram, CBOW and GloVe.…