Papers with online system
CogKTR: A Knowledge-Enhanced Text Representation Toolkit for Natural Language Understanding (2022.emnlp-demos)
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Zhuoran Jin, Tianyi Men, Hongbang Yuan, Yuyang Zhou, Pengfei Cao, Yubo Chen, Zhipeng Xue, Kang Liu, Jun Zhao
| Challenge: | Existing knowledge-enhanced methods are limited to knowledge-intensive tasks. |
| Approach: | They propose a knowledge-enhanced text representation toolkit for natural language understanding . it combines knowledge acquisition, knowledge representation, knowledge injection and knowledge application . |
| Outcome: | The proposed toolkit supports knowledge acquisition, knowledge representation, knowledge injection, and knowledge application. |
OpenUE: An Open Toolkit of Universal Extraction from Text (2020.emnlp-demos)
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Ningyu Zhang, Shumin Deng, Zhen Bi, Haiyang Yu, Jiacheng Yang, Mosha Chen, Fei Huang, Wei Zhang, Huajun Chen
| Challenge: | a large number of natural language processing tasks focus on token-level or sentence-level understandings. |
| Approach: | They propose an open-source and extensible toolkit for various extraction tasks . they deploy an online demo with restful APIs to support real-time extraction . |
| Outcome: | The proposed model can be used to extract information from text without training and deployment. |
ClaimRank: Detecting Check-Worthy Claims in Arabic and English (N18-5)
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| Challenge: | ClaimRank is an online system for detecting check-worthy claims . it can be used to prioritize the claims fact-checkers should consider first . |
| Approach: | ClaimRank is an online system for detecting check-worthy claims . it is originally trained on political debates, but can work for any kind of text . authors propose to make automated fact-checking easier by prioritizing claims based on annotations from reputable fact- checking organizations. |
| Outcome: | ClaimRank is an online system for detecting check-worthy claims . it can mimic the sentence selection strategies of reputable fact-checking organizations . |
EasyEdit: An Easy-to-use Knowledge Editing Framework for Large Language Models (2024.acl-demos)
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Peng Wang, Ningyu Zhang, Bozhong Tian, Zekun Xi, Yunzhi Yao, Ziwen Xu, Mengru Wang, Shengyu Mao, Xiaohan Wang, Siyuan Cheng, Kangwei Liu, Yuansheng Ni, Guozhou Zheng, Huajun Chen
| Challenge: | Large Language Models (LLMs) suffer from knowledge cutoff or fallacy issues, which means they are unaware of unseen events or generate text with incorrect facts owing to outdated/noisy data. |
| Approach: | They propose an easy-to-use knowledge editing framework for Large Language Models that allows users to easily edit updated knowledge and adjust undesired behavior while minimizing the impact on unrelated inputs. |
| Outcome: | The proposed framework surpasses traditional fine-tuning in terms of reliability and generalization. |
CogKGE: A Knowledge Graph Embedding Toolkit and Benchmark for Representing Multi-source and Heterogeneous Knowledge (2022.acl-demo)
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Zhuoran Jin, Tianyi Men, Hongbang Yuan, Zhitao He, Dianbo Sui, Chenhao Wang, Zhipeng Xue, Yubo Chen, Jun Zhao
| Challenge: | Existing methods focus on entity-centric knowledge, but CogKGE supports heterogeneous knowledge. |
| Approach: | They propose a knowledge graph embedding toolkit to represent multi-source and heterogeneous knowledge. |
| Outcome: | The proposed toolkit provides a unified programming framework for KGE tasks and a series of knowledge representations for downstream tasks. |
FPI: Failure Point Isolation in Large-scale Conversational Assistants (2022.naacl-industry)
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| Challenge: | Large-scale conversational assistants can cause errors in their modules . a machine learning system can analyze large volumes of data and isolate the source of error . |
| Approach: | They propose a machine learning system that embeds incoming request and context using pre-trained transformer models and encodes additional metadata features to output failure point predictions. |
| Outcome: | The proposed system obtains 92.2% of human performance while scaling to analyze the entire traffic in 8 different languages of a large-scale conversational assistant. |
BENNERD: A Neural Named Entity Linking System for COVID-19 (2020.emnlp-demos)
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| Challenge: | a biomedical entity linking system is available for COVID-19 research. |
| Approach: | They propose a biomedical entity linking system that detects named enti- ties in text and links them to the UMLS knowledge base. |
| Outcome: | The proposed system detects named enti- ties in text and links them to the unified medical language system (UMS) knowledge base entries. |
OpenNRE: An Open and Extensible Toolkit for Neural Relation Extraction (D19-3)
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| Challenge: | OpenNRE provides a framework to implement neural relation extraction (RE) . the toolkit provides various functional modules based on TensorFlow and PyTorch . |
| Approach: | OpenNRE is an open-source framework to implement neural relation extraction models. they also release an online system to meet real-time extraction without any training and deployment. |
| Outcome: | OpenNRE provides a framework to implement neural models for relation extraction (RE) the toolkit also includes an online system to meet real-time extraction without training and deployment . |
Clinical-Coder: Assigning Interpretable ICD-10 Codes to Chinese Clinical Notes (2020.acl-demos)
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| Challenge: | Existing methods of automatic coding prediction have been successful, but the interpretability of predicted codes is a challenge. |
| Approach: | They propose an online system that can predict ICD codes for Chinese clinical notes by using a Dilated Convolutional Attention network with N-gram Matching mechanism. |
| Outcome: | The proposed system is able to provide supporting information in clinical decision making. |
Disease Network Constructor: a Pathway Extraction and Visualization (2023.acl-demo)
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Mohammad Golam Sohrab, Khoa Duong, Goran Topić, Masami Ikeda, Nozomi Nagano, Yayoi Natsume-Kitatani, Masakata Kuroda, Mari Itoh, Hiroya Takamura
| Challenge: | In the human body, various substances (entities) such as proteins and compounds interact and regulate each other, forming huge pathway networks. |
| Approach: | They present a system that extracts and visualizes a disease network derived through regulation events found in scientific articles on idiopathic pulmonary fibrosis. |
| Outcome: | The proposed system extracts and visualizes a disease network from biomedical articles on idiopathic pulmonary fibrosis (IPF) it includes two-dimensional (2D) and 3D visualizations of the constructed disease network. |
Online Near-Duplicate Detection of News Articles (2020.lrec-1)
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| Challenge: | Near-duplicate documents are prevalent in news corpora and cost significant . bloating corporata with redundant information and computational costs are among the costs . |
| Approach: | They propose an online system which flags a near-duplicate document by finding its most likely original. |
| Outcome: | The proposed system can be used in many real-world applications. |
SpanNER: Named Entity Re-/Recognition as Span Prediction (2021.acl-long)
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| Challenge: | Recent years have seen the paradigm shift of Named Entity Recognition (NER) systems from sequence labeling to span prediction. |
| Approach: | They experimentally implement 154 named entity recognition models on 11 datasets and show that span prediction can serve as a system combiner to re-recognize named entities from different systems’ outputs. |
| Outcome: | The proposed model can be used to re-recognize named entities from different systems’ outputs. |