1 code implementation • 20 Mar 2024 • Huachuan Qiu, Shuai Zhang, Hongliang He, Anqi Li, Zhenzhong Lan
Pornographic content occurring in human-machine interaction dialogues can cause severe side effects for users in open-domain dialogue systems.
1 code implementation • 25 Jan 2024 • Hongliang He, Wenlin Yao, Kaixin Ma, Wenhao Yu, Yong Dai, Hongming Zhang, Zhenzhong Lan, Dong Yu
The rapid advancement of large language models (LLMs) has led to a new era marked by the development of autonomous applications in real-world scenarios, which drives innovation in creating advanced web agents.
no code implementations • 16 Nov 2023 • Junlei Zhang, Hongliang He, Nirui Song, Shuyuan He, Shuai Zhang, Huachuan Qiu, Anqi Li, Lizhi Ma, Zhenzhong Lan
As Large Language Models (LLMs) are becoming prevalent in various fields, there is an urgent need for improved NLP benchmarks that encompass all the necessary knowledge of individual discipline.
1 code implementation • 18 Sep 2023 • Huachuan Qiu, Shuai Zhang, Hongliang He, Anqi Li, Zhenzhong Lan
NSFW (Not Safe for Work) content, in the context of a dialogue, can have severe side effects on users in open-domain dialogue systems.
1 code implementation • 31 Jul 2023 • Huachuan Qiu, Tong Zhao, Anqi Li, Shuai Zhang, Hongliang He, Zhenzhong Lan
Our study reveals that ChatGPT struggles to detect safety categories with detailed safety definitions in a zero- and few-shot paradigm, whereas the fine-tuned model proves to be more suitable.
1 code implementation • 17 Jul 2023 • Huachuan Qiu, Shuai Zhang, Anqi Li, Hongliang He, Zhenzhong Lan
We present a systematic analysis of the safety and robustness of LLMs regarding the position of explicit normal instructions, word replacements (verbs in explicit normal instructions, target groups in malicious instructions, cue words for explicit normal instructions), and instruction replacements (different explicit normal instructions).
1 code implementation • 27 Jun 2023 • Anqi Li, Lizhi Ma, Yaling Mei, Hongliang He, Shuai Zhang, Huachuan Qiu, Zhenzhong Lan
Communication success relies heavily on reading participants' reactions.
1 code implementation • 12 May 2023 • Hongliang He, Junlei Zhang, Zhenzhong Lan, Yue Zhang
Contrastive learning-based methods, such as unsup-SimCSE, have achieved state-of-the-art (SOTA) performances in learning unsupervised sentence embeddings.
1 code implementation • 30 Apr 2023 • Huachuan Qiu, Hongliang He, Shuai Zhang, Anqi Li, Zhenzhong Lan
Furthermore, we implement an expert evaluation and the results demonstrate that the dialogues generated with our proposed method are of higher quality than those generated with other baseline methods.
no code implementations • 28 Feb 2023 • Xiao Tang, Hongliang He, Limeng Dong, Lixin Li, Qinghe Du, Zhu Han
The security gain with aerial reflection and jamming is further improved with the optimized deployment of the aerial platform.
no code implementations • ICCV 2023 • Hongliang He, Jun Wang, Pengxu Wei, Fan Xu, Xiangyang Ji, Chang Liu, Jie Chen
Experiments on three nuclear instance segmentation datasets justify the superiority of TopoSeg, which achieves state-of-the-art performance.
no code implementations • 7 Mar 2022 • Anqi Li, Jingsong Ma, Lizhi Ma, Pengfei Fang, Hongliang He, Zhenzhong Lan
However, these methods often demand large scale and high quality counseling data, which are difficult to collect.
1 code implementation • 2 Jun 2021 • Chiyu Song, Hongliang He, Haofei Yu, Pengfei Fang, Leyang Cui, Zhenzhong Lan
The current state-of-the-art ranking methods mainly use an encoding paradigm called Cross-Encoder, which separately encodes each context-candidate pair and ranks the candidates according to their fitness scores.
Ranked #1 on Conversational Response Selection on Persona-Chat
1 code implementation • ICCV 2021 • Hongliang He, Zhongyi Huang, Yao Ding, Guoli Song, Lin Wang, Qian Ren, Pengxu Wei, Zhiqiang Gao, Jie Chen
Specifically, we define the centripetal direction feature as a class of adjacent directions pointing to the nuclear center to represent the spatial relationship between pixels within the nucleus.
no code implementations • 6 Dec 2017 • Le Hui, Xiang Li, Jiaxin Chen, Hongliang He, Chen Gong, Jian Yang
Unsupervised Image-to-Image Translation achieves spectacularly advanced developments nowadays.