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Found 7 papers, 2 papers with code
OPDAI at SemEval-2022 Task 11: A hybrid approach for Chinese NER using outside Wikipedia knowledge
This article describes the OPDAI submission to SemEval-2022 Task 11 on Chinese complex NER.
MMoE: Robust Spoiler Detection with Multi-modal Information and Domain-aware Mixture-of-Experts
For instance, the metadata and the corresponding user's information of a review could be helpful.
LMBot: Distilling Graph Knowledge into Language Model for Graph-less Deployment in Twitter Bot Detection
For datasets without graph structure, we simply replace the GNN with an MLP, which has also shown strong performance.
Enhancing Model Performance in Multilingual Information Retrieval with Comprehensive Data Engineering Techniques
In this paper, we present our solution to the Multilingual Information Retrieval Across a Continuum of Languages (MIRACL) challenge of WSDM CUP 2023\footnote{https://project-miracl. github. io/}.
Using Deep Mixture-of-Experts to Detect Word Meaning Shift for TempoWiC
This paper mainly describes the dma submission to the TempoWiC task, which achieves a macro-F1 score of 77. 05% and attains the first place in this task.
A Semantic Alignment System for Multilingual Query-Product Retrieval
Our models are all trained with cross-entropy loss to classify the query-product pairs into ESCI 4 categories at first, and then we use weighted sum with the 4-class probabilities to get the score for ranking.
TwiBot-22: Towards Graph-Based Twitter Bot Detection
Twitter bot detection has become an increasingly important task to combat misinformation, facilitate social media moderation, and preserve the integrity of the online discourse.
