He, Junxian

Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs

Xiong, M., Hu, Z., Lu, X., Li, Y., Fu, J., He, J., & Hooi, B. (2023) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 618

On the Sentence Embeddings from Pre-trained Language Models

Li, B., Zhou, H., He, J., Wang, M., Yang, Y., & Li, L. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 593

C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models

Huang, Y., Bai, Y., Zhu, Z., Zhang, J., Zhang, J., Su, T., Liu, J., Lv, C., Zhang, Y., Lei, J., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 373

Efficient Nearest Neighbor Language Models

He, J., Neubig, G., & Berg-Kirkpatrick, T. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 97

Neuro-Symbolic Language Modeling with Automaton-augmented Retrieval

Alon, U., Xu, F. F., He, J., Sengupta, S., Roth, D., & Neubig, G. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 32

FacTool: Factuality Detection in Generative AI - A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

Chern, I.-C., Chern, S., Chen, S., Yuan, W., Feng, K., Zhou, C., He, J., Neubig, G., & Liu, P. (2023) · arXiv

Topic ModelingMisinformation and Its Impacts

Cited by 29

Self-Evaluation Guided Beam Search for Reasoning

Xie, Y., Kawaguchi, K., Zhao, Y., Zhao, J. X., Kan, M.-Y., He, J., & Xie, M. (2023) · Advances in Neural Information Processing Systems 36

AI-based Problem Solving and PlanningLogic, Reasoning, and Knowledge

Cited by 27

AgentBoard: An analytical evaluation board of multi-turn LLM agents

Ma, C., Zhang, J., Zhu, Z., Yang, C., Yang, Y., Jin, Y., Lan, Z., Kong, L., & He, J. (2024) · Advances in Neural Information Processing Systems 37

Speech and dialogue systemsMulti-Agent Systems and Negotiation

Cited by 26

AgentBoard: An Analytical Evaluation Board of Multi-turn LLM Agents

Ma, C., Zhang, J., Zhu, Z., Yang, C., Yang, Y., Jin, Y., Lan, Z., Kong, L., & He, J. (2024) · arXiv

Speech and dialogue systemsMulti-Agent Systems and Negotiation

Cited by 26

Compression Represents Intelligence Linearly

Huang, Y., Zhang, J., Shan, Z., & He, J. (2024) · arXiv

Topic ModelingAlgorithms and Data Compression

Cited by 5

Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers

Su, Z., Xia, P., Guo, H., Liu, Z., Ma, Y., Qu, X., Liu, J., Li, Y., Zeng, K., Yang, Z., et al. (2025) · arXiv

Multimodal Machine Learning ApplicationsLogic, Reasoning, and Knowledge

Cited by 0

IntentionQA: A Benchmark for Evaluating Purchase Intention Comprehension Abilities of Language Models in E-commerce

Ding, W., Wang, W., Kwok, S. H. D., Liu, M., Fang, T., Bai, J., Liu, X., Yu, C., Li, Z., Luo, C., et al. (2024) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 0

Predictive Data Selection: The Data That Predicts Is the Data That Teaches

Shum, K., Huang, Y., Zou, H., Ding, Q., Liao, Y., Chen, X., Liu, Q., & He, J. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0