1 code implementation • Findings (NAACL) 2022 • Jin Qian, Bowei Zou, Mengxing Dong, Xiao Li, AiTi Aw, Yu Hong
Conversational Question Answering (ConvQA) is required to answer the current question, conditioned on the observable paragraph-level context and conversation history.
no code implementations • Findings (EMNLP) 2021 • Xin Huang, Jung-jae Kim, Bowei Zou
Complex question answering over knowledge base remains as a challenging task because it involves reasoning over multiple pieces of information, including intermediate entities/relations and other constraints.
no code implementations • NAACL (BEA) 2022 • Bowei Zou, Pengfei Li, Liangming Pan, Ai Ti Aw
In field of teaching, true/false questioning is an important educational method for assessing students’ general understanding of learning materials.
no code implementations • CCL 2020 • Jin Qian, Rongtao Huang, Bowei Zou, Yu Hong
生成式阅读理解是机器阅读理解领域一项新颖且极具挑战性的研究。与主流的抽取式阅读理解相比, 生成式阅读理解模型不再局限于从段落中抽取答案, 而是能结合问题和段落生成自然和完整的表述作为答案。然而, 现有的生成式阅读理解模型缺乏对答案在段落中的边界信息以及对问题类型信息的理解。为解决上述问题, 本文提出一种基于多任务学习的生成式阅读理解模型。该模型在训练阶段将答案生成任务作为主任务, 答案抽取和问题分类任务作为辅助任务进行多任务学习, 同时学习和优化模型编码层参数;在测试阶段加载模型编码层进行解码生成答案。实验结果表明, 答案抽取模型和问题分类模型能够有效提升生成式阅读理解模型的性能。
no code implementations • Findings (EMNLP) 2021 • Yeqiu Li, Bowei Zou, Zhifeng Li, Ai Ti Aw, Yu Hong, Qiaoming Zhu
However, the current reasoning models suffer from the noises in the retrieved knowledge.
no code implementations • 10 Dec 2023 • Xin Tan, Bowei Zou, Ai Ti Aw
Universal fact-checking systems for real-world claims face significant challenges in gathering valid and sufficient real-time evidence and making reasoned decisions.
1 code implementation • 25 May 2023 • Zhifeng Li, Yifan Fan, Bowei Zou, Yu Hong
UFO turns LLMs into knowledge sources and produces relevant facts (knowledge statements) for the given question.
1 code implementation • 15 May 2023 • Yanling Li, Bowei Zou, Yifan Fan, Mengxing Dong, Yu Hong
The corresponding solutions contribute to the answer-oriented reasoning on a series of well-organized and thread-aware conversational contexts.
1 code implementation • 15 May 2023 • Zhifeng Li, Bowei Zou, Yifan Fan, Yu Hong
Within the experimental models, the T5-based GenCQA with KEPR obtains the best performance, which is up to 60. 91% at the primary canonical metric Inc@3.
1 code implementation • 4 May 2023 • Xuan Long Do, Bowei Zou, Shafiq Joty, Anh Tai Tran, Liangming Pan, Nancy F. Chen, Ai Ti Aw
In addition, we propose Conv-Distinct, a novel evaluation metric for CQG, to evaluate the diversity of the generated conversation from a context.
1 code implementation • COLING 2022 • Xuan Long Do, Bowei Zou, Liangming Pan, Nancy F. Chen, Shafiq Joty, Ai Ti Aw
While previous studies mainly focus on how to model the flow and alignment of the conversation, there has been no thorough study to date on which parts of the context and history are necessary for the model.
no code implementations • 28 Feb 2022 • Weiwen Xu, Bowei Zou, Wai Lam, Ai Ti Aw
Recent techniques in Question Answering (QA) have gained remarkable performance improvement with some QA models even surpassed human performance.
no code implementations • COLING 2020 • Chen Gong, Zhenghua Li, Bowei Zou, Min Zhang
Detailed evaluation shows that our proposed model with weakly labeled data significantly outperforms the state-of-the-art MWS model by 1. 12 and 5. 97 on NEWS and BAIKE data in F1.
1 code implementation • COLING 2020 • Rongtao Huang, Bowei Zou, Yu Hong, Wei zhang, AiTi Aw, Guodong Zhou
Most existing RC models are developed on formal datasets such as news articles and Wikipedia documents, which severely limit their performances when directly applied to the noisy and informal texts in social media.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Peng Wu, Bowei Zou, Ridong Jiang, AiTi Aw
As an essential component of task-oriented dialogue systems, Dialogue State Tracking (DST) takes charge of estimating user intentions and requests in dialogue contexts and extracting substantial goals (states) from user utterances to help the downstream modules to determine the next actions of dialogue systems.
Dialogue State Tracking Multi-domain Dialogue State Tracking +1
no code implementations • ACL 2020 • Zhenkai Wei, Yu Hong, Bowei Zou, Meng Cheng, Jianmin Yao
The current aspect extraction methods suffer from boundary errors.
Ranked #2 on Aspect Extraction on SemEval 2015 Task 12
no code implementations • IJCNLP 2019 • Longxiang Shen, Bowei Zou, Yu Hong, Guodong Zhou, Qiaoming Zhu, AiTi Aw
For the sake of understanding a negated statement, it is critical to precisely detect the negative focus in context.
no code implementations • COLING 2018 • Yu Hong, Yang Xu, Huibin Ruan, Bowei Zou, Jianmin Yao, Guodong Zhou
In particular, we incorporate image processing into the acquisition of similar event instances, including the utilization of images for visually representing event scenes, and the use of the neural network based image matching for approximate calculation between events.
1 code implementation • COLING 2018 • Bowei Zou, Zengzhuang Xu, Yu Hong, Guodong Zhou
In this paper, we come up with a feature adaptation approach for cross-lingual relation classification, which employs a generative adversarial network (GAN) to transfer feature representations from one language with rich annotated data to another language with scarce annotated data.