Прати
Hongliang He
Hongliang He
Ph.D. student, Zhejiang University
Верификована је имејл адреса на westlake.edu.cn
Наслов
Навело
Навело
Година
WebVoyager: Building an End-to-End Web Agent with Large Multimodal Models
H He, W Yao, K Ma, W Yu, Y Dai, H Zhang, Z Lan, D Yu
ACL 2024 (main), 2024
94*2024
Latent jailbreak: A benchmark for evaluating text safety and output robustness of large language models
H Qiu, S Zhang, A Li, H He, Z Lan
arXiv preprint arXiv:2307.08487, 2023
652023
Smile: Single-turn to multi-turn inclusive language expansion via chatgpt for mental health support
H Qiu, H He, S Zhang, A Li, Z Lan
Findings of EMNLP 2024, 2023
482023
Understanding Client Reactions in Online Mental Health Counseling
A Li, L Ma, Y Mei, H He, S Zhang, H Qiu, Z Lan
Proceedings of the 61st Annual Meeting of the Association for Computational …, 2023
212023
A benchmark for understanding dialogue safety in mental health support
H Qiu, T Zhao, A Li, S Zhang, H He, Z Lan
CCF International Conference on Natural Language Processing and Chinese …, 2023
122023
Towards automated real-time evaluation in text-based counseling
A Li, J Ma, L Ma, P Fang, H He, Z Lan
arXiv preprint arXiv:2203.03442, 2022
62022
Uni-encoder: A fast and accurate response selection paradigm for generation-based dialogue systems
C Song, H He, H Yu, P Fang, L Cui, Z Lan
Findings of ACL 2023, 2021
52021
Facilitating Pornographic Text Detection for Open-Domain Dialogue Systems via Knowledge Distillation of Large Language Models
H Qiu, S Zhang, H He, A Li, Z Lan
CSCWD 2024, 2024
3*2024
Instance smoothed contrastive learning for unsupervised sentence embedding
H He, J Zhang, Z Lan, Y Zhang
Proceedings of the AAAI Conference on Artificial Intelligence 37 (11), 12863 …, 2023
32023
PsyBench: a balanced and in-depth Psychological Chinese Evaluation Benchmark for Foundation Models.
J Zhang, H He, N Song, S He, S Zhang, H Qiu, A Li, L Ma, Z Lan
arXiv preprint arXiv:2311.09861, 2023
22023
Openwebvoyager: Building multimodal web agents via iterative real-world exploration, feedback and optimization
H He, W Yao, K Ma, W Yu, H Zhang, T Fang, Z Lan, D Yu
arXiv preprint arXiv:2410.19609, 2024
12024
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