257 citations · 469 across the 45 of their papers we have counts for
13 papers · 1 filter
From Dense to Sparse: Contrastive Pruning for Better Pre-trained Language Model Compression
Runxin Xu, Fuli Luo, Chengyu Wang +4
Pre-trained Language Models (PLMs) have achieved great success in various Natural Language Processing (NLP) tasks under the pre-training and fine-tuning paradigm. With large quanti…
Hierarchical Curriculum Learning for AMR Parsing
Peiyi Wang, Liang Chen, Tianyu Liu +4
Abstract Meaning Representation (AMR) parsing aims to translate sentences to semantic representation with a hierarchical structure, and is recently empowered by pretrained sequence…
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning
Runxin Xu, Fuli Luo, Zhiyuan Zhang +4
Recent pretrained language models extend from millions to billions of parameters. Thus the need to fine-tune an extremely large pretrained model with a limited training corpus aris…
An Enhanced Span-based Decomposition Method for Few-Shot Sequence Labeling
Peiyi Wang, Runxin Xu, Tianyu Liu +4
Few-Shot Sequence Labeling (FSSL) is a canonical paradigm for the tagging models, e.g., named entity recognition and slot filling, to generalize on an emerging, resource-scarce dom…
Behind the Scenes: An Exploration of Trigger Biases Problem in Few-Shot Event Classification
Peiyi Wang, Runxin Xu, Tianyu Liu +3
Few-Shot Event Classification (FSEC) aims at developing a model for event prediction, which can generalize to new event types with a limited number of annotated data. Existing FSEC…
Explicit Interaction Network for Aspect Sentiment Triplet Extraction
Peiyi Wang, Tianyu Liu, Damai Dai +3
Aspect Sentiment Triplet Extraction (ASTE) aims to recognize targets, their sentiment polarities and opinions explaining the sentiment from a sentence. ASTE could be naturally divi…
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Ningyu Zhang, Mosha Chen, Zhen Bi +20
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice. With the development of biomedical langua…
Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker
Runxin Xu, Tianyu Liu, Lei Li +1
Document-level event extraction aims to recognize event information from a whole piece of article. Existing methods are not effective due to two challenges of this task: a) the tar…
Premise-based Multimodal Reasoning: Conditional Inference on Joint Textual and Visual Clues
Qingxiu Dong, Ziwei Qin, Heming Xia +9
It is a common practice for recent works in vision language cross-modal reasoning to adopt a binary or multi-choice classification formulation taking as input a set of source image…
Problems and Countermeasures in Natural Language Processing Evaluation
Qingxiu Dong, Zhifang Sui, Weidong Zhan +1
Evaluation in natural language processing guides and promotes research on models and methods. In recent years, new evalua-tion data sets and evaluation tasks have been continuously…
Knowledge Neurons in Pretrained Transformers
Damai Dai, Li Dong, Yaru Hao +3
Large-scale pretrained language models are surprisingly good at recalling factual knowledge presented in the training corpus. In this paper, we present preliminary studies on how f…
Incorporating Connections Beyond Knowledge Embeddings: A Plug-and-Play Module to Enhance Commonsense Reasoning in Machine Reading Comprehension
Damai Dai, Hua Zheng, Zhifang Sui +1
Conventional Machine Reading Comprehension (MRC) has been well-addressed by pattern matching, but the ability of commonsense reasoning remains a gap between humans and machines. Pr…
Towards Faithfulness in Open Domain Table-to-text Generation from an Entity-centric View
Tianyu Liu, Xin Zheng, Baobao Chang +1
In open domain table-to-text generation, we notice that the unfaithful generation usually contains hallucinated content which can not be aligned to any input table record. We thus…