2 citations · 7 across the 8 of their papers we have counts for
8 papers
Model Fusion with Multi-LoRA Inference for Tool-Enhanced Game Dialogue Agents
Kangxu Wang, Ze Chen, Chengcheng Wei +3
This paper presents the opdainlp team's solution for the GPU track of the CPDC 2025 challenge. The challenge consists of three tasks, aiming to build an in-game conversational AI t…
Sentence-Level Relation Extraction via Contrastive Learning with Descriptive Relation Prompts
Jiewen Zheng, Ze Chen
Sentence-level relation extraction aims to identify the relation between two entities for a given sentence. The existing works mostly focus on obtaining a better entity representat…
Enhancing Model Performance in Multilingual Information Retrieval with Comprehensive Data Engineering Techniques
Qi Zhang, Zijian Yang, Yilun Huang +6
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…
OPD@NL4Opt: An ensemble approach for the NER task of the optimization problem
Kangxu Wang, Ze Chen, Jiewen Zheng
In this paper, we present an ensemble approach for the NL4Opt competition subtask 1(NER task). For this task, we first fine tune the pretrained language models based on the competi…
Using Deep Mixture-of-Experts to Detect Word Meaning Shift for TempoWiC
Ze Chen, Kangxu Wang, Zijian Cai +4
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. We first explore the impact…
A Semantic Alignment System for Multilingual Query-Product Retrieval
Qi Zhang, Zijian Yang, Yilun Huang +6
This paper mainly describes our winning solution (team name: www) to Amazon ESCI Challenge of KDD CUP 2022, which achieves a NDCG score of 0.9043 and wins the first place on task 1…
Integrating Human Linguistic Insights into AI: Theory-Driven Representation for Multilingual Text-to-Speech
Cong Zhang, Huinan Zeng, Huang Liu +1
This paper explores the integration of human linguistic insights into multilingual text-to-speech (TTS) systems by evaluating the Featurally Underspecified Lexicon (FUL) as a theor…
Applying Phonological Features in Multilingual Text-To-Speech
Cong Zhang, Huinan Zeng, Huang Liu +1
This study investigates whether phonological features can be applied in text-to-speech systems to generate native and non-native speech in English and Mandarin. We present a mappin…