no code implementations • EMNLP 2020 • Hui Su, Xiaoyu Shen, Zhou Xiao, Zheng Zhang, Ernie Chang, Cheng Zhang, Cheng Niu, Jie zhou
In this work, we take a close look at the movie domain and present a large-scale high-quality corpus with fine-grained annotations in hope of pushing the limit of movie-domain chatbots.
no code implementations • 22 Jan 2025 • Hanning Zhang, Juntong Song, Juno Zhu, Yuanhao Wu, Tong Zhang, Cheng Niu
Using \textbf{RAG-Reward}, we train reward models and apply reinforcement learning with human feedback (RLHF) to improve LLMs' effectiveness in RAG.
no code implementations • 12 Jun 2024 • Cheng Niu, Yang Guan, Yuanhao Wu, Juno Zhu, Juntong Song, Randy Zhong, Kaihua Zhu, Siliang Xu, Shizhe Diao, Tong Zhang
In response to this challenge, we introduce VeraCT Scan, a novel retrieval-augmented system for fake news detection.
no code implementations • 17 May 2024 • Cheng Niu, Xingguang Wang, Xuxin Cheng, Juntong Song, Tong Zhang
Then a two-stage fine-tuning on LLaMA 2 is performed on the generated data and the real data for the DST prediction.
no code implementations • 10 May 2024 • Elham Ravanbakhsh, Cheng Niu, Yongqing Liang, J. Ramanujam, Xin Li
Weakly-Supervised Semantic Segmentation (WSSS) offers a cost-efficient workaround to extensive labeling in comparison to fully-supervised methods by using partial or incomplete labels.
3 code implementations • 31 Dec 2023 • Cheng Niu, Yuanhao Wu, Juno Zhu, Siliang Xu, Kashun Shum, Randy Zhong, Juntong Song, Tong Zhang
Retrieval-augmented generation (RAG) has become a main technique for alleviating hallucinations in large language models (LLMs).
no code implementations • COLING 2020 • Keqing He, Jinchao Zhang, Yuanmeng Yan, Weiran Xu, Cheng Niu, Jie zhou
In this paper, we propose a Contrastive Zero-Shot Learning with Adversarial Attack (CZSL-Adv) method for the cross-domain slot filling.
no code implementations • ACL 2020 • Yong Shan, Zekang Li, Jinchao Zhang, Fandong Meng, Yang Feng, Cheng Niu, Jie zhou
Recent studies in dialogue state tracking (DST) leverage historical information to determine states which are generally represented as slot-value pairs.
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1 code implementation • ACL 2020 • Hui Su, Xiaoyu Shen, Sanqiang Zhao, Xiao Zhou, Pengwei Hu, Randy Zhong, Cheng Niu, Jie zhou
Neural network-based sequence-to-sequence (seq2seq) models strongly suffer from the low-diversity problem when it comes to open-domain dialogue generation.
no code implementations • 26 Apr 2020 • Zeyang Lei, Zekang Li, Jinchao Zhang, Fandong Meng, Yang Feng, Yujiu Yang, Cheng Niu, Jie zhou
Furthermore, to facilitate the convergence of Gaussian mixture prior and posterior distributions, we devise a curriculum optimization strategy to progressively train the model under multiple training criteria from easy to hard.
no code implementations • 21 Apr 2020 • Canxiang Yan, Jianhao Yan, Yangyin Xu, Cheng Niu, Jie zhou
Static knowledge graph has been incorporated extensively into sequence-to-sequence framework for text generation.
1 code implementation • 1 Feb 2020 • Zekang Li, Zongjia Li, Jinchao Zhang, Yang Feng, Cheng Niu, Jie zhou
Audio-Visual Scene-Aware Dialog (AVSD) is a task to generate responses when chatting about a given video, which is organized as a track of the 8th Dialog System Technology Challenge (DSTC8).
no code implementations • WS 2019 • Qian Li, Hui Su, Cheng Niu, Daling Wang, Zekang Li, Shi Feng, Yifei Zhang
Moreover, pretraining is essential in reinforcement learning models, so we provide a high-quality annotated dataset for question reformulation by sampling a part of QuAC dataset.
2 code implementations • ACL 2019 • Zekang Li, Cheng Niu, Fandong Meng, Yang Feng, Qian Li, Jie zhou
Document Grounded Conversations is a task to generate dialogue responses when chatting about the content of a given document.
1 code implementation • ACL 2019 • Zhi-Qiang Liu, Zuohui Fu, Jie Cao, Gerard de Melo, Yik-Cheung Tam, Cheng Niu, Jie zhou
Rhetoric is a vital element in modern poetry, and plays an essential role in improving its aesthetics.
1 code implementation • ACL 2019 • Hui Su, Xiaoyu Shen, Rongzhi Zhang, Fei Sun, Pengwei Hu, Cheng Niu, Jie zhou
To properly train the utterance rewriter, we collect a new dataset with human annotations and introduce a Transformer-based utterance rewriting architecture using the pointer network.
1 code implementation • 16 Sep 2018 • Baoyu Jing, Chenwei Lu, Deqing Wang, Fuzhen Zhuang, Cheng Niu
To this end, we embed the group alignment and a partial supervision into a cross-domain topic model, and propose a Cross-Domain Labeled LDA (CDL-LDA).