149 citations · 226 across the 29 of their papers we have counts for
29 papers
Do PLMs Know and Understand Ontological Knowledge?
Weiqi Wu, Chengyue Jiang, Yong Jiang +2
Ontological knowledge, which comprises classes and properties and their relationships, is integral to world knowledge. It is significant to explore whether Pretrained Language Mode…
EcomGPT: Instruction-tuning Large Language Models with Chain-of-Task Tasks for E-commerce
Yangning Li, Shirong Ma, Xiaobin Wang +6
Recently, instruction-following Large Language Models (LLMs) , represented by ChatGPT, have exhibited exceptional performance in general Natural Language Processing (NLP) tasks. Ho…
SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding
Tianyu Yu, Chengyue Jiang, Chao Lou +12
Large language models (LLMs) have shown impressive ability for open-domain NLP tasks. However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which…
Improving Social Media Popularity Prediction with Multiple Post Dependencies
Zhizhen Zhang, Xiaohui Xie, Mengyu Yang +3
Social Media Popularity Prediction has drawn a lot of attention because of its profound impact on many different applications, such as recommendation systems and multimedia adverti…
Improving Text Matching in E-Commerce Search with A Rationalizable, Intervenable and Fast Entity-Based Relevance Model
Jiong Cai, Yong Jiang, Yue Zhang +10
Discovering the intended items of user queries from a massive repository of items is one of the main goals of an e-commerce search system. Relevance prediction is essential to the…
Bidirectional End-to-End Learning of Retriever-Reader Paradigm for Entity Linking
Yinghui Li, Yong Jiang, Yangning Li +4
Entity Linking (EL) is a fundamental task for Information Extraction and Knowledge Graphs. The general form of EL (i.e., end-to-end EL) aims to first find mentions in the given inp…
DAMO-NLP at SemEval-2023 Task 2: A Unified Retrieval-augmented System for Multilingual Named Entity Recognition
Zeqi Tan, Shen Huang, Zixia Jia +8
The MultiCoNER \RNum{2} shared task aims to tackle multilingual named entity recognition (NER) in fine-grained and noisy scenarios, and it inherits the semantic ambiguity and low-c…
From Retrieval to Generation: Efficient and Effective Entity Set Expansion
Shulin Huang, Shirong Ma, Yangning Li +2
Entity Set Expansion (ESE) is a critical task aiming at expanding entities of the target semantic class described by seed entities. Most existing ESE methods are retrieval-based fr…
COMBO: A Complete Benchmark for Open KG Canonicalization
Chengyue Jiang, Yong Jiang, Weiqi Wu +3
Open knowledge graph (KG) consists of (subject, relation, object) triples extracted from millions of raw text. The subject and object noun phrases and the relation in open KG have…
ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT
Xiang Wei, Xingyu Cui, Ning Cheng +9
Zero-shot information extraction (IE) aims to build IE systems from the unannotated text. It is challenging due to involving little human intervention. Challenging but worthwhile,…
One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER
Xiang Chen, Lei Li, Shuofei Qiao +5
Cross-domain NER is a challenging task to address the low-resource problem in practical scenarios. Previous typical solutions mainly obtain a NER model by pre-trained language mode…
Recall, Expand and Multi-Candidate Cross-Encode: Fast and Accurate Ultra-Fine Entity Typing
Chengyue Jiang, Wenyang Hui, Yong Jiang +3
Ultra-fine entity typing (UFET) predicts extremely free-formed types (e.g., president, politician) of a given entity mention (e.g., Joe Biden) in context. State-of-the-art (SOTA) m…
Named Entity and Relation Extraction with Multi-Modal Retrieval
Xinyu Wang, Jiong Cai, Yong Jiang +3
Multi-modal named entity recognition (NER) and relation extraction (RE) aim to leverage relevant image information to improve the performance of NER and RE. Most existing efforts l…
Modeling Label Correlations for Ultra-Fine Entity Typing with Neural Pairwise Conditional Random Field
Chengyue Jiang, Yong Jiang, Weiqi Wu +2
Ultra-fine entity typing (UFET) aims to predict a wide range of type phrases that correctly describe the categories of a given entity mention in a sentence. Most recent works infer…
Entity-to-Text based Data Augmentation for various Named Entity Recognition Tasks
Xuming Hu, Yong Jiang, Aiwei Liu +5
Data augmentation techniques have been used to alleviate the problem of scarce labeled data in various NER tasks (flat, nested, and discontinuous NER tasks). Existing augmentation…
DAMO-NLP at NLPCC-2022 Task 2: Knowledge Enhanced Robust NER for Speech Entity Linking
Shen Huang, Yuchen Zhai, Xinwei Long +4
Speech Entity Linking aims to recognize and disambiguate named entities in spoken languages. Conventional methods suffer gravely from the unfettered speech styles and the noisy tra…
Domain-Specific NER via Retrieving Correlated Samples
Xin Zhang, Yong Jiang, Xiaobin Wang +4
Successful Machine Learning based Named Entity Recognition models could fail on texts from some special domains, for instance, Chinese addresses and e-commerce titles, where requir…
DAMO-NLP at SemEval-2022 Task 11: A Knowledge-based System for Multilingual Named Entity Recognition
Xinyu Wang, Yongliang Shen, Jiong Cai +9
The MultiCoNER shared task aims at detecting semantically ambiguous and complex named entities in short and low-context settings for multiple languages. The lack of contexts makes…
Eliciting Knowledge from Pretrained Language Models for Prototypical Prompt Verbalizer
Yinyi Wei, Tong Mo, Yongtao Jiang +2
Recent advances on prompt-tuning cast few-shot classification tasks as a masked language modeling problem. By wrapping input into a template and using a verbalizer which constructs…
ITA: Image-Text Alignments for Multi-Modal Named Entity Recognition
Xinyu Wang, Min Gui, Yong Jiang +6
Recently, Multi-modal Named Entity Recognition (MNER) has attracted a lot of attention. Most of the work utilizes image information through region-level visual representations obta…
DeepCC: Bridging the Gap Between Congestion Control and Applications via Multi-Objective Optimization
Lei Zhang, Yong Cui, Mowei Wang +3
The increasingly complicated and diverse applications have distinct network performance demands, e.g., some desire high throughput while others require low latency. Traditional con…
Second-Order Unsupervised Neural Dependency Parsing
Songlin Yang, Yong Jiang, Wenjuan Han +1
Most of the unsupervised dependency parsers are based on first-order probabilistic generative models that only consider local parent-child information. Inspired by second-order sup…
Automated Concatenation of Embeddings for Structured Prediction
Xinyu Wang, Yong Jiang, Nguyen Bach +4
Pretrained contextualized embeddings are powerful word representations for structured prediction tasks. Recent work found that better word representations can be obtained by concat…
Structure-Level Knowledge Distillation For Multilingual Sequence Labeling
Xinyu Wang, Yong Jiang, Nguyen Bach +3
Multilingual sequence labeling is a task of predicting label sequences using a single unified model for multiple languages. Compared with relying on multiple monolingual models, us…