Qin, Bing

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Huang, L., Yu, W., Ma, W., Zhong, W., Feng, Z., Wang, H., Chen, Q., Peng, W., Feng, X., Qin, B., et al. (2025) · ACM Transactions on Information Systems

Topic ModelingInformation Retrieval and Search Behavior

Cited by 4,688

CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Feng, Z., Guo, D., Tang, D., Duan, N., Feng, X., Gong, M., Shou, L., Qin, B., Liu, T., Jiang, D., et al. (2020) · Findings of the Association for Computational Linguistics: EMNLP 2020

Software Engineering ResearchTopic Modeling

Cited by 2,824

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Huang, L., Yu, W., Ma, W., Zhong, W., Feng, Z., Wang, H., Chen, Q., Peng, W., Feng, X., Qin, B., et al. (2023) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 2,516

Learning Sentiment-Specific Word Embedding for Twitter Sentiment Classification

Tang, D., Wei, F., Yang, N., Zhou, M., Liu, T., & Qin, B. (2014) · Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 1,181

CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Feng, Z., Guo, D., Tang, D., Duan, N., Feng, X., Gong, M., Shou, L., Qin, B., Liu, T., Jiang, D., et al. (2020) · arXiv

Software Engineering ResearchTopic Modeling

Cited by 243

A Text-Centered Shared-Private Framework via Cross-Modal Prediction for Multimodal Sentiment Analysis

Wu, Y., Lin, Z., Zhao, Y., Qin, B., & Zhu, L.-N. (2021) · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021

Sentiment Analysis and Opinion MiningEmotion and Mood Recognition

Cited by 129

HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge

Wang, H., Liu, C., Xi, N., Qiang, Z., Zhao, S., Qin, B., & Liu, T. (2023) · arXiv

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 115

Is ChatGPT Equipped with Emotional Dialogue Capabilities?

Zhao, W., Zhao, Y., Lu, X., Wang, S., Tong, Y., & Qin, B. (2023) · arXiv

Speech and dialogue systemsEmotion and Mood Recognition

Cited by 92

Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate

Xiong, K., Ding, X., Cao, Y., Liu, T., & Qin, B. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Topic ModelingMultimodal Machine Learning Applications

Cited by 66

The Factual Inconsistency Problem in Abstractive Text Summarization: A Survey

Huang, Y., Feng, X., Feng, X., & Qin, B. (2021) · arXiv

Topic ModelingAdvanced Text Analysis Techniques

Cited by 62

Examining Inter-Consistency of Large Language Models Collaboration: An In-depth Analysis via Debate

Xiong, K., Ding, X., Cao, Y., Liu, T., & Qin, B. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 45

Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese

Wang, H., Zhao, S., Qiang, Z., Li, Z., Xi, N., Du, Y., Cai, M., Guo, H., Chen, Y., Xu, H., et al. (2023) · arXiv

Topic ModelingArtificial Intelligence in Healthcare and Education

Cited by 26

Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future

Chu, Z., Chen, J., Chen, Q., Yu, W., He, T., Wang, H., Peng, W., Liu, M., Qin, B., & Liu, T. (2023) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 25

TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models

Chu, Z., Chen, J., Chen, Q., Yu, W., Wang, H., Liu, M., & Qin, B. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 20

Learning Fine-Grained Grounded Citations for Attributed Large Language Models

Huang, L., Feng, X., Ma, W., Gu, Y., Zhong, W., Feng, X., Yu, W., Peng, W., Tang, D., Tu, D., et al. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 12

Improving Controllable Text Generation with Position-Aware Weighted Decoding

Gu, Y., Feng, X., Ma, S., Wu, J., Gong, H., & Qin, B. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Topic ModelingNatural Language Processing Techniques

Cited by 12

Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning

Zhao, Y., Du, L., Ding, X., Xiong, K., Sun, Z., Jun, S., Liu, T., & Qin, B. (2024) · Findings of the Association for Computational Linguistics ACL 2024

Topic ModelingNatural Language Processing Techniques

Cited by 5

Self-Critique Guided Iterative Reasoning for Multi-hop Question Answering

Chu, Z., Fan, H., Chen, J., Wang, Q., Yang, M., Liang, J., Wang, Z., Li, H., Tang, G., Liu, M., et al. (2025) · Findings of the Association for Computational Linguistics: ACL 2025

Topic ModelingMultimodal Machine Learning Applications

Cited by 2

KwaiAgents: Generalized Information-seeking Agent System with Large Language Models

Pan, H., Zhai, Z., Yuan, H., Lv, Y., Fu, R., Liu, M., Wang, Z., & Qin, B. (2023) · arXiv

Information Retrieval and Search BehaviorAI-based Problem Solving and Planning

Cited by 1