Search Results for author:
Found 19 papers, 12 papers with code
Improving Biomedical Pretrained Language Models with Knowledge
To this end, we propose KeBioLM, a biomedical pretrained language model that explicitly leverages knowledge from the UMLS knowledge bases.
Ranked #1 on
Named Entity Recognition (NER)
on JNLPBA
Lattice-BERT: Leveraging Multi-Granularity Representations in Chinese Pre-trained Language Models
Further analysis shows that Lattice-BERT can harness the lattice structures, and the improvement comes from the exploration of redundant information and multi-granularity representations.
VECO: Variable and Flexible Cross-lingual Pre-training for Language Understanding and Generation
Existing work in multilingual pretraining has demonstrated the potential of cross-lingual transferability by training a unified Transformer encoder for multiple languages.
VECO: Variable Encoder-decoder Pre-training for Cross-lingual Understanding and Generation
Recent studies about learning multilingual representations have achieved significant performance gains across a wide range of downstream cross-lingual tasks.
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network
In this paper, we explore the slot tagging with only a few labeled support sentences (a. k. a.
HIT-SCIR at MRP 2019: A Unified Pipeline for Meaning Representation Parsing via Efficient Training and Effective Encoding
This paper describes our system (HIT-SCIR) for CoNLL 2019 shared task: Cross-Framework Meaning Representation Parsing.
Ranked #1 on
UCCA Parsing
on CoNLL 2019
Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever
Querying the knowledge base (KB) has long been a challenge in the end-to-end task-oriented dialogue system.
Ranked #6 on
Task-Oriented Dialogue Systems
on KVRET
Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing
In this approach, a linear transformation is learned from contextual word alignments to align the contextualized embeddings independently trained in different languages.
Few-Shot Sequence Labeling with Label Dependency Transfer and Pair-wise Embedding
It calculates emission score with similarity based methods and obtains transition score with a specially designed transfer mechanism.
An AMR Aligner Tuned by Transition-based Parser
In this paper, we propose a new rich resource enhanced AMR aligner which produces multiple alignments and a new transition system for AMR parsing along with its oracle parser.
Ranked #2 on
AMR Parsing
on LDC2014T12:
Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation
This paper describes our system (HIT-SCIR) submitted to the CoNLL 2018 shared task on Multilingual Parsing from Raw Text to Universal Dependencies.
Ranked #3 on
Dependency Parsing
on Universal Dependencies
Sequence-to-Sequence Data Augmentation for Dialogue Language Understanding
In this paper, we study the problem of data augmentation for language understanding in task-oriented dialogue system.
Sequence-to-Sequence Learning for Task-oriented Dialogue with Dialogue State Representation
Classic pipeline models for task-oriented dialogue system require explicit modeling the dialogue states and hand-crafted action spaces to query a domain-specific knowledge base.
Ranked #7 on
Task-Oriented Dialogue Systems
on KVRET
Distilling Knowledge for Search-based Structured Prediction
Many natural language processing tasks can be modeled into structured prediction and solved as a search problem.
Parsing Tweets into Universal Dependencies
Nonetheless, using the new treebank, we build a pipeline system to parse raw tweets into UD.
Ranked #2 on
Dependency Parsing
on Tweebank
Exploring Segment Representations for Neural Segmentation Models
Many natural language processing (NLP) tasks can be generalized into segmentation problem.
