Search Results for author:
Found 20 papers, 15 papers with code
damo_nlp at MEDIQA 2021: Knowledge-based Preprocessing and Coverage-oriented Reranking for Medical Question Summarization
Medical question summarization is an important but difficult task, where the input is often complex and erroneous while annotated data is expensive to acquire.
Overview of the PromptCBLUE Shared Task in CHIP2023
Many teams from both the industry and academia participated in the shared tasks, and the top teams achieved amazing test results.
PromptCBLUE: A Chinese Prompt Tuning Benchmark for the Medical Domain
Biomedical language understanding benchmarks are the driving forces for artificial intelligence applications with large language model (LLM) back-ends.
Construction and Applications of Billion-Scale Pre-Trained Multimodal Business Knowledge Graph
We release all the open resources (OpenBG benchmarks) derived from it for the community and report experimental results of KG-centric tasks.
From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer
Knowledge graph completion aims to address the problem of extending a KG with missing triples.
Ranked #49 on
Link Prediction
on FB15k-237
LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with Self-training
Previous works leverage logical forms to facilitate logical knowledge-conditioned text generation.
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice.
Ranked #1 on
Semantic Similarity
on CHIP-STS
Document-level Relation Extraction as Semantic Segmentation
Specifically, we leverage an encoder module to capture the context information of entities and a U-shaped segmentation module over the image-style feature map to capture global interdependency among triples.
Ranked #4 on
Relation Extraction
on GDA
DiaKG: an Annotated Diabetes Dataset for Medical Knowledge Graph Construction
In order to accelerate the research for domain-specific knowledge graphs in the medical domain, we introduce DiaKG, a high-quality Chinese dataset for Diabetes knowledge graph, which contains 22, 050 entities and 6, 890 relations in total.
OntoED: Low-resource Event Detection with Ontology Embedding
Most of current methods to ED rely heavily on training instances, and almost ignore the correlation of event types.
Noisy-Labeled NER with Confidence Estimation
This work studies NER under a noisy labeled setting with calibrated confidence estimation.
Probing BERT in Hyperbolic Spaces
We introduce a Poincare probe, a structural probe projecting these embeddings into a Poincare subspace with explicitly defined hierarchies.
Normal vs. Adversarial: Salience-based Analysis of Adversarial Samples for Relation Extraction
Recent neural-based relation extraction approaches, though achieving promising improvement on benchmark datasets, have reported their vulnerability towards adversarial attacks.
Biomedical Question Answering: A Survey of Approaches and Challenges
Automatic Question Answering (QA) has been successfully applied in various domains such as search engines and chatbots.
Nested Named Entity Recognition with Partially-Observed TreeCRFs
With the TreeCRF we achieve a uniform way to jointly model the observed and the latent nodes.
Ranked #11 on
Nested Named Entity Recognition
on ACE 2005
Latent Template Induction with Gumbel-CRFs
Learning to control the structure of sentences is a challenging problem in text generation.
Predicting Clinical Trial Results by Implicit Evidence Integration
In the CTRP framework, a model takes a PICO-formatted clinical trial proposal with its background as input and predicts the result, i. e. how the Intervention group compares with the Comparison group in terms of the measured Outcome in the studied Population.
OpenUE: An Open Toolkit of Universal Extraction from Text
We introduce a prototype model and provide an open-source and extensible toolkit called OpenUE for various extraction tasks.
Ranked #3 on
Joint Entity and Relation Extraction
on WebNLG
Contrastive Triple Extraction with Generative Transformer
In this paper, we revisit the end-to-end triple extraction task for sequence generation.
Ranked #9 on
Relation Extraction
on WebNLG
NLP\_HZ at SemEval-2018 Task 9: a Nearest Neighbor Approach
Hypernym discovery aims to discover the hypernym word sets given a hyponym word and proper corpus.
Ranked #3 on
Hypernym Discovery
on General
