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08/29/2023
When Do Program-of-Thoughts Work for Reasoning?
The reasoning capabilities of Large Language Models (LLMs) play a pivota...
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10/20/2022
Tele-Knowledge Pre-training for Fault Analysis
In this work, we share our experience on tele-knowledge pre-training for...
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05/22/2022
Relphormer: Relational Graph Transformer for Knowledge Graph Representation
Transformers have achieved remarkable performance in widespread fields, ...
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04/09/2022
Contrastive Demonstration Tuning for Pre-trained Language Models
Pretrained language models can be effectively stimulated by textual prom...
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01/23/2022
OntoProtein: Protein Pretraining With Gene Ontology Embedding
Self-supervised protein language models have proved their effectiveness ...
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12/08/2021
Improving Knowledge Graph Representation Learning by Structure Contextual Pre-training
Representation learning models for Knowledge Graphs (KG) have proven to ...
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10/01/2021
Learning to Ask for Data-Efficient Event Argument Extraction
Event argument extraction (EAE) is an important task for information ext...
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08/30/2021
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Large-scale pre-trained language models have contributed significantly t...
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06/15/2021
CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedic...
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04/20/2021
Interventional Aspect-Based Sentiment Analysis
Recent neural-based aspect-based sentiment analysis approaches, though a...
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04/11/2021
Disentangled Contrastive Learning for Learning Robust Textual Representations
Although the self-supervised pre-training of transformer models has resu...
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04/06/2021