1 code implementation • 25 Oct 2023 • Chao-Hong Tan, Jia-Chen Gu, Zhen-Hua Ling
Large Language Models (LLMs) have emerged as influential instruments within the realm of natural language processing; nevertheless, their capacity to handle multi-party conversations (MPCs) -- a scenario marked by the presence of multiple interlocutors involved in intricate information exchanges -- remains uncharted.
1 code implementation • 22 May 2023 • Jia-Chen Gu, Chao-Hong Tan, Caiyuan Chu, Zhen-Hua Ling, Chongyang Tao, Quan Liu, Cong Liu
Given an MPC with a few addressee labels missing, existing methods fail to build a consecutively connected conversation graph, but only a few separate conversation fragments instead.
no code implementations • 19 May 2023 • Chao-Hong Tan, Jia-Chen Gu, Zhen-Hua Ling
In fact, the encoder-decoder architecture is naturally more flexible for its detachable encoder and decoder modules, which is extensible to multilingual and multimodal generation tasks for conditions and target texts.
1 code implementation • Findings (ACL) 2022 • Chao-Hong Tan, Jia-Chen Gu, Chongyang Tao, Zhen-Hua Ling, Can Xu, Huang Hu, Xiubo Geng, Daxin Jiang
To address the problem, we propose augmenting TExt Generation via Task-specific and Open-world Knowledge (TegTok) in a unified framework.
1 code implementation • ACL 2022 • Jia-Chen Gu, Chao-Hong Tan, Chongyang Tao, Zhen-Hua Ling, Huang Hu, Xiubo Geng, Daxin Jiang
To address these challenges, we present HeterMPC, a heterogeneous graph-based neural network for response generation in MPCs which models the semantics of utterances and interlocutors simultaneously with two types of nodes in a graph.
1 code implementation • 26 Jan 2022 • Lu Dong, Zhi-Qiang Guo, Chao-Hong Tan, Ya-Jun Hu, Yuan Jiang, Zhen-Hua Ling
Neural network models have achieved state-of-the-art performance on grapheme-to-phoneme (G2P) conversion.
1 code implementation • ICLR 2022 • Chao-Hong Tan, Qian Chen, Wen Wang, Qinglin Zhang, Siqi Zheng, Zhen-Hua Ling
We propose a novel Pooling Network (PoNet) for token mixing in long sequences with linear complexity.
1 code implementation • 22 Dec 2020 • Chao-Hong Tan, Xiaoyu Yang, Zi'ou Zheng, Tianda Li, Yufei Feng, Jia-Chen Gu, Quan Liu, Dan Liu, Zhen-Hua Ling, Xiaodan Zhu
Task-oriented conversational modeling with unstructured knowledge access, as track 1 of the 9th Dialogue System Technology Challenges (DSTC 9), requests to build a system to generate response given dialogue history and knowledge access.