no code implementations • ACL (ECNLP) 2021 • Runze Liang, Ryuichi Takanobu, Feng-Lin Li, Ji Zhang, Haiqing Chen, Minlie Huang
To this end, we formalize the turn-level satisfaction estimation as a reinforcement learning problem, in which the model can be optimized with only session-level satisfaction labels.
1 code implementation • 25 Feb 2024 • Xin Mao, Feng-Lin Li, Huimin Xu, Wei zhang, Anh Tuan Luu
While Reinforcement Learning from Human Feedback (RLHF) significantly enhances the generation quality of Large Language Models (LLMs), recent studies have raised concerns regarding the complexity and instability associated with the Proximal Policy Optimization (PPO) algorithm, proposing a series of order-based calibration methods as viable alternatives.
no code implementations • 13 May 2023 • Qianglong Chen, Feng Ji, Feng-Lin Li, Guohai Xu, Ming Yan, Ji Zhang, Yin Zhang
To support cost-effective language inference in multilingual settings, we propose AMTSS, an adaptive multi-teacher single-student distillation framework, which allows distilling knowledge from multiple teachers to a single student.
no code implementations • 1 Aug 2022 • Qianglong Chen, Feng-Lin Li, Guohai Xu, Ming Yan, Ji Zhang, Yin Zhang
We evaluate our approach on a variety of knowledge driven and language understanding tasks, including NER, relation extraction, CommonsenseQA, OpenBookQA and GLUE.
no code implementations • 22 Sep 2021 • Fu Sun, Feng-Lin Li, Ruize Wang, Qianglong Chen, Xingyi Cheng, Ji Zhang
Knowledge enhanced pre-trained language models (K-PLMs) are shown to be effective for many public tasks in the literature but few of them have been successfully applied in practice.
no code implementations • 13 Sep 2021 • Guohai Xu, Hehong Chen, Feng-Lin Li, Fu Sun, Yunzhou Shi, Zhixiong Zeng, Wei Zhou, Zhongzhou Zhao, Ji Zhang
Live streaming is becoming an increasingly popular trend of sales in E-commerce.
no code implementations • ACL 2021 • Qianglong Chen, Feng Ji, Xiangji Zeng, Feng-Lin Li, Ji Zhang, Haiqing Chen, Yin Zhang
In order to better understand the reason behind model behaviors (i. e., making predictions), most recent works have exploited generative models to provide complementary explanations.
1 code implementation • Findings (ACL) 2021 • Fangkai Jiao, Yangyang Guo, Yilin Niu, Feng Ji, Feng-Lin Li, Liqiang Nie
Pre-trained Language Models (PLMs) have achieved great success on Machine Reading Comprehension (MRC) over the past few years.
no code implementations • 24 Sep 2020 • Feng-Lin Li, Hehong Chen, Guohai Xu, Tian Qiu, Feng Ji, Ji Zhang, Haiqing Chen
Pre-sales customer service is of importance to E-commerce platforms as it contributes to optimizing customers' buying process.
no code implementations • 12 Dec 2019 • Feng-Lin Li, Weijia Chen, Qi Huang, Yikun Guo
With the rise of knowledge graph (KG), question answering over knowledge base (KBQA) has attracted increasing attention in recent years.
no code implementations • 12 Jan 2018 • Feng-Lin Li, Minghui Qiu, Haiqing Chen, Xiongwei Wang, Xing Gao, Jun Huang, Juwei Ren, Zhongzhou Zhao, Weipeng Zhao, Lei Wang, Guwei Jin, Wei Chu
We present AliMe Assist, an intelligent assistant designed for creating an innovative online shopping experience in E-commerce.
no code implementations • ACL 2017 • Minghui Qiu, Feng-Lin Li, Siyu Wang, Xing Gao, Yan Chen, Weipeng Zhao, Haiqing Chen, Jun Huang, Wei Chu
We propose AliMe Chat, an open-domain chatbot engine that integrates the joint results of Information Retrieval (IR) and Sequence to Sequence (Seq2Seq) based generation models.