no code implementations • SemEval (NAACL) 2022 • Ze Chen, Kangxu Wang, Jiewen Zheng, Zijian Cai, Jiarong He, Jin Gao
This article describes the OPDAI submission to SemEval-2022 Task 11 on Chinese complex NER.
no code implementations • 20 Feb 2024 • Chengcheng Wei, Ze Chen, Songtan Fang, Jiarong He, Max Gao
This paper mainly describes a unified system for hallucination detection of LLMs, which wins the second prize in the model-agnostic track of the SemEval-2024 Task 6, and also achieves considerable results in the model-aware track.
no code implementations • 14 Feb 2023 • Qi Zhang, Zijian Yang, Yilun Huang, Ze Chen, Zijian Cai, Kangxu Wang, Jiewen Zheng, Jiarong He, Jin Gao
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/}.
no code implementations • 7 Nov 2022 • Ze Chen, Kangxu Wang, Zijian Cai, Jiewen Zheng, Jiarong He, Max Gao, Jason Zhang
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.
no code implementations • 8 Aug 2022 • Heng Cong, Lingzhi Fu, Rongyu Zhang, Yusheng Zhang, Hao Wang, Jiarong He, Jin Gao
In this work, we introduce Gradient Siamese Network (GSN) for image quality assessment.
no code implementations • 8 Aug 2022 • Heng Cong, Rongyu Zhang, Jiarong He, Jin Gao
Face anti-spoofing researches are widely used in face recognition and has received more attention from industry and academics.
no code implementations • 5 Aug 2022 • Qi Zhang, Zijian Yang, Yilun Huang, Ze Chen, Zijian Cai, Kangxu Wang, Jiewen Zheng, Jiarong He, Jin Gao
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.
1 code implementation • 2 Mar 2022 • Qi Zhang, Zijian Yang, Yilun Huang, Jiarong He, Lixiang Wang
The Cross-Market Recommendation task of WSDM CUP 2022 is about finding solutions to improve individual recommendation systems in resource-scarce target markets by leveraging data from similar high-resource source markets.