1 code implementation • 20 Mar 2024 • Hongzhan Chen, Hehong Chen, Ming Yan, Wenshen Xu, Xing Gao, Weizhou Shen, Xiaojun Quan, Chenliang Li, Ji Zhang, Fei Huang, Jingren Zhou
In this paper, we introduce RoleInteract, the first benchmark designed to systematically evaluate the sociality of role-playing conversational agents at both individual and group levels of social interactions.
1 code implementation • 29 Jan 2024 • Junyang Wang, Haiyang Xu, Jiabo Ye, Ming Yan, Weizhou Shen, Ji Zhang, Fei Huang, Jitao Sang
To assess the performance of Mobile-Agent, we introduced Mobile-Eval, a benchmark for evaluating mobile device operations.
1 code implementation • 14 Jan 2024 • Weizhou Shen, Chenliang Li, Hongzhan Chen, Ming Yan, Xiaojun Quan, Hehong Chen, Ji Zhang, Fei Huang
Each component is implemented by a single LLM that focuses on a specific capability and collaborates with others to accomplish the task.
1 code implementation • 13 Oct 2023 • Weizhou Shen, Yingqi Gao, Canbin Huang, Fanqi Wan, Xiaojun Quan, Wei Bi
The results demonstrate that when combined with meta knowledge, the response generator can effectively leverage high-quality knowledge records from the retriever and enhance the quality of generated responses.
1 code implementation • 2 Sep 2023 • Chenliang Li, Hehong Chen, Ming Yan, Weizhou Shen, Haiyang Xu, Zhikai Wu, Zhicheng Zhang, Wenmeng Zhou, Yingda Chen, Chen Cheng, Hongzhu Shi, Ji Zhang, Fei Huang, Jingren Zhou
Large language models (LLMs) have recently demonstrated remarkable capabilities to comprehend human intentions, engage in reasoning, and design planning-like behavior.
1 code implementation • 17 May 2023 • Fanqi Wan, Weizhou Shen, Ke Yang, Xiaojun Quan, Wei Bi
Retrieving proper domain knowledge from an external database lies at the heart of end-to-end task-oriented dialog systems to generate informative responses.
1 code implementation • 21 Feb 2023 • Weizhou Shen, Xiaojun Quan, Ke Yang
To model the dependencies between utterances in multi-party conversations, we propose a simple and generic framework based on the dependency parsing results of utterances.
2 code implementations • 28 Jun 2022 • Weizhou Shen, Yeyun Gong, Yelong Shen, Song Wang, Xiaojun Quan, Nan Duan, Weizhu Chen
Generate-then-rank is a widely used mechanism for text generation, where a generator produces multiple text candidates and a ranker chooses the best one among the text candidates.
1 code implementation • ACL 2021 • Weizhou Shen, Siyue Wu, Yunyi Yang, Xiaojun Quan
In this paper, we put forward a novel idea of encoding the utterances with a directed acyclic graph (DAG) to better model the intrinsic structure within a conversation, and design a directed acyclic neural network, namely DAG-ERC, to implement this idea.
Ranked #10 on Emotion Recognition in Conversation on DailyDialog
4 code implementations • 16 Dec 2020 • Weizhou Shen, Junqing Chen, Xiaojun Quan, Zhixian Xie
Specifically, we first modify the recurrence mechanism of XLNet from segment-level to utterance-level in order to better model the conversational data.
Ranked #2 on Emotion Recognition in Conversation on CPED
1 code implementation • COLING 2020 • Yunyi Yang, Kun Li, Xiaojun Quan, Weizhou Shen, Qinliang Su
One of the remaining challenges for aspect term extraction in sentiment analysis resides in the extraction of phrase-level aspect terms, which is non-trivial to determine the boundaries of such terms.
Aspect Term Extraction and Sentiment Classification Sentence +1
1 code implementation • ACL 2020 • Kai Wang, Weizhou Shen, Yunyi Yang, Xiaojun Quan, Rui Wang
Then, we propose a relational graph attention network (R-GAT) to encode the new tree structure for sentiment prediction.
Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2