335 citations · 1.7k across the 86 of their papers we have counts for
7 papers · 2 filters
Ensemble Distillation for Unsupervised Constituency Parsing
Behzad Shayegh, Yanshuai Cao, Xiaodan Zhu +2
We investigate the unsupervised constituency parsing task, which organizes words and phrases of a sentence into a hierarchical structure without using linguistically annotated data…
Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
Zijun Wu, Yongkang Wu, Lili Mou
Prompt tuning in natural language processing (NLP) has become an increasingly popular method for adapting large language models to specific tasks. However, the transferability of t…
Weakly Supervised Reasoning by Neuro-Symbolic Approaches
Xianggen Liu, Zhengdong Lu, Lili Mou
Deep learning has largely improved the performance of various natural language processing (NLP) tasks. However, most deep learning models are black-box machinery, and lack explicit…
Search and Learning for Unsupervised Text Generation
Lili Mou
With the advances of deep learning techniques, text generation is attracting increasing interest in the artificial intelligence (AI) community, because of its wide applications and…
The Emergence of Chunking Structures with Hierarchical RNN
Zijun Wu, Anup Anand Deshmukh, Yongkang Wu +2
In Natural Language Processing (NLP), predicting linguistic structures, such as parsing and chunking, has mostly relied on manual annotations of syntactic structures. This paper in…
f-Divergence Minimization for Sequence-Level Knowledge Distillation
Yuqiao Wen, Zichao Li, Wenyu Du +1
Knowledge distillation (KD) is the process of transferring knowledge from a large model to a small one. It has gained increasing attention in the natural language processing commun…