Chen, Qianglong

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

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 to break: Knowledge-enhanced reasoning in multi-agent debate system

Wang, H., Du, X., Yu, W., Chen, Q., Zhu, K., Chu, Z., Yan, L., & Guan, Y. (2025) · Neurocomputing

Multi-Agent Systems and NegotiationTopic Modeling

Cited by 36

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

Beamaggr: Beam aggregation reasoning over multi-source knowledge for multi-hop question answering

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

Topic ModelingMultimodal Machine Learning Applications

Cited by 11

Mixed Distillation Helps Smaller Language Models Reason Better

Chenglin, L., Chen, Q., Li, L., Wang, C., Tao, F., Li, Y., Chen, Z., & Zhang, Y. (2024) · Findings of the Association for Computational Linguistics: EMNLP 2024

Topic ModelingNatural Language Processing Techniques

Cited by 3