research
∙
08/29/2023
When Do Program-of-Thoughts Work for Reasoning?
The reasoning capabilities of Large Language Models (LLMs) play a pivota...
share
research
∙
08/07/2023
From Sky to the Ground: A Large-scale Benchmark and Simple Baseline Towards Real Rain Removal
Learning-based image deraining methods have made great progress. However...
research
∙
05/23/2023
SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres
Event-centric structured prediction involves predicting structured outpu...
research
∙
05/22/2023
Editing Large Language Models: Problems, Methods, and Opportunities
Recent advancements in deep learning have precipitated the emergence of ...
research
∙
12/19/2022
Reasoning with Language Model Prompting: A Survey
Reasoning, as an essential ability for complex problem-solving, can prov...
research
∙
10/19/2022
Schema-aware Reference as Prompt Improves Data-Efficient Relational Triple and Event Extraction
Information Extraction, which aims to extract structural relational trip...
research
∙
10/01/2022
Multimodal Analogical Reasoning over Knowledge Graphs
Analogical reasoning is fundamental to human cognition and holds an impo...
research
∙
10/01/2022
PromptKG: A Prompt Learning Framework for Knowledge Graph Representation Learning and Application
Knowledge Graphs (KGs) often have two characteristics: heterogeneous gra...
research
∙
09/30/2022
Construction and Applications of Open Business Knowledge Graph
Business Knowledge Graph is important to many enterprises today, providi...
research
∙
05/29/2022
Decoupling Knowledge from Memorization: Retrieval-augmented Prompt Learning
Prompt learning approaches have made waves in natural language processin...
research
∙
05/07/2022
Good Visual Guidance Makes A Better Extractor: Hierarchical Visual Prefix for Multimodal Entity and Relation Extraction
Multimodal named entity recognition and relation extraction (MNER and MR...
research
∙
05/04/2022
Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completion
Multimodal Knowledge Graphs (MKGs), which organize visual-text factual k...
research
∙
02/16/2022
Knowledge Extraction in Low-Resource Scenarios: Survey and Perspective
Knowledge Extraction (KE) which aims to extract structural information f...
research
∙
02/04/2022
From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer
Knowledge graph completion aims to address the problem of extending a KG...
research
∙
01/27/2022
Ontology-enhanced Prompt-tuning for Few-shot Learning
Few-shot Learning (FSL) is aimed to make predictions based on a limited ...
research
∙
01/23/2022
OntoProtein: Protein Pretraining With Gene Ontology Embedding
Self-supervised protein language models have proved their effectiveness ...
research
∙
01/14/2022
Reasoning Through Memorization: Nearest Neighbor Knowledge Graph Embeddings
Previous knowledge graph embedding approaches usually map entities to re...
research
∙
01/10/2022
DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population
We present a new open-source and extensible knowledge extraction toolkit...
research
∙
12/02/2021
LOGEN: Few-shot Logical Knowledge-Conditioned Text Generation with Self-training
Natural language generation from structured data mainly focuses on surfa...
research
∙
12/01/2021
Molecular Contrastive Learning with Chemical Element Knowledge Graph
Molecular representation learning contributes to multiple downstream tas...
research
∙
10/01/2021
Learning to Ask for Data-Efficient Event Argument Extraction
Event argument extraction (EAE) is an important task for information ext...
research
∙
08/31/2021
LightNER: A Lightweight Generative Framework with Prompt-guided Attention for Low-resource NER
Most existing NER methods rely on extensive labeled data for model train...
research
∙
08/30/2021
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Large-scale pre-trained language models have contributed significantly t...
research
∙
06/15/2021
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedic...
research
∙
06/07/2021
Document-level Relation Extraction as Semantic Segmentation
Document-level relation extraction aims to extract relations among multi...
research
∙
06/03/2021
AliCG: Fine-grained and Evolvable Conceptual Graph Construction for Semantic Search at Alibaba
Conceptual graphs, which is a particular type of Knowledge Graphs, play ...
research
∙
05/23/2021
OntoED: Low-resource Event Detection with Ontology Embedding
Event Detection (ED) aims to identify event trigger words from a given t...
research
∙
05/20/2021
MLBiNet: A Cross-Sentence Collective Event Detection Network
We consider the problem of collectively detecting multiple events, parti...
research
∙
04/15/2021
AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction
In this paper, we reformulate the relation extraction task as mask langu...
research
∙
04/11/2021
Disentangled Contrastive Learning for Learning Robust Textual Representations
Although the self-supervised pre-training of transformer models has resu...
research
∙
04/06/2021
Text-guided Legal Knowledge Graph Reasoning
Recent years have witnessed the prosperity of legal artificial intellige...
research
∙
04/01/2021
Normal vs. Adversarial: Salience-based Analysis of Adversarial Samples for Relation Extraction
Recent neural-based relation extraction approaches, though achieving pro...
research
∙
02/25/2021
ZJUKLAB at SemEval-2021 Task 4: Negative Augmentation with Language Model for Reading Comprehension of Abstract Meaning
This paper presents our systems for the three Subtasks of SemEval Task4:...
research
∙
10/30/2020
Bridging Text and Knowledge with Multi-Prototype Embedding for Few-Shot Relational Triple Extraction
Current supervised relational triple extraction approaches require huge ...
research
∙
09/15/2020
The Devil is the Classifier: Investigating Long Tail Relation Classification with Decoupling Analysis
Long-tailed relation classification is a challenging problem as the head...
research
∙
09/14/2020
Contrastive Triple Extraction with Generative Transformer
Triple extraction is an essential task in information extraction for nat...
research
∙
09/14/2020
Can Fine-tuning Pre-trained Models Lead to Perfect NLP? A Study of the Generalizability of Relation Extraction
Fine-tuning pre-trained models have achieved impressive performance on s...
research
∙
11/08/2019
Relation Adversarial Network for Low Resource KnowledgeGraph Completion
Knowledge Graph Completion (KGC) has been proposed to improve Knowledge ...
research
∙
10/25/2019
Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection
Event detection (ED), a sub-task of event extraction, involves identifyi...
research
∙
08/22/2019
Transfer Learning for Relation Extraction via Relation-Gated Adversarial Learning
Relation extraction aims to extract relational facts from sentences. Pre...
research
∙
08/22/2019
Improving Few-shot Text Classification via Pretrained Language Representations
Text classification tends to be difficult when the data is deficient or ...
research
∙
03/04/2019
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
We propose a distance supervised relation extraction approach for long-t...
research
∙
12/29/2018
