984 citations · 1.3k across the 27 of their papers we have counts for
9 papers · 1 filter
Facilitating NSFW Text Detection in Open-Domain Dialogue Systems via Knowledge Distillation
Huachuan Qiu, Shuai Zhang, Hongliang He +2
NSFW (Not Safe for Work) content, in the context of a dialogue, can have severe side effects on users in open-domain dialogue systems. However, research on detecting NSFW language,…
Latent Jailbreak: A Benchmark for Evaluating Text Safety and Output Robustness of Large Language Models
Huachuan Qiu, Shuai Zhang, Anqi Li +2
Considerable research efforts have been devoted to ensuring that large language models (LLMs) align with human values and generate safe text. However, an excessive focus on sensiti…
A Benchmark for Understanding Dialogue Safety in Mental Health Support
Huachuan Qiu, Tong Zhao, Anqi Li +3
Dialogue safety remains a pervasive challenge in open-domain human-machine interaction. Existing approaches propose distinctive dialogue safety taxonomies and datasets for detectin…
SuperCLUE: A Comprehensive Chinese Large Language Model Benchmark
Liang Xu, Anqi Li, Lei Zhu +7
Large language models (LLMs) have shown the potential to be integrated into human daily lives. Therefore, user preference is the most critical criterion for assessing LLMs' perform…
Understanding Client Reactions in Online Mental Health Counseling
Anqi Li, Lizhi Ma, Yaling Mei +4
Communication success relies heavily on reading participants' reactions. Such feedback is especially important for mental health counselors, who must carefully consider the client'…
Enhancing Grammatical Error Correction Systems with Explanations
Yuejiao Fei, Leyang Cui, Sen Yang +3
Grammatical error correction systems improve written communication by detecting and correcting language mistakes. To help language learners better understand why the GEC system mak…
Instance Smoothed Contrastive Learning for Unsupervised Sentence Embedding
Hongliang He, Junlei Zhang, Zhenzhong Lan +1
Contrastive learning-based methods, such as unsup-SimCSE, have achieved state-of-the-art (SOTA) performances in learning unsupervised sentence embeddings. However, in previous stud…
Contrastive Learning of Sentence Embeddings from Scratch
Junlei Zhang, Zhenzhong Lan, Junxian He
Contrastive learning has been the dominant approach to train state-of-the-art sentence embeddings. Previous studies have typically learned sentence embeddings either through the us…
SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Support
Huachuan Qiu, Hongliang He, Shuai Zhang +2
Developing specialized dialogue systems for mental health support requires multi-turn conversation data, which has recently garnered increasing attention. However, gathering and re…