Ji, Heng

Moralization in social networks and the emergence of violence during protests

Mooijman, M., Hoover, J., Lin, Y., Ji, H., & Dehghani, M. (2018) · Nature Human Behaviour

Social and Intergroup PsychologyPsychology of Moral and Emotional Judgment

Cited by 229

Tweet, but verify: epistemic study of information verification on Twitter

Zubiaga, A., & Ji, H. (2014) · Social Network Analysis and Mining

Misinformation and Its ImpactsPublic Relations and Crisis Communication

Cited by 125

Towards a Unified Multi-Dimensional Evaluator for Text Generation

Zhong, M., Liu, Y., Yin, D., Mao, Y., Jiao, Y., Liu, P., Zhu, C., Ji, H., & Han, J. (2022) · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing

Topic ModelingNatural Language Processing Techniques

Cited by 117

Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Wang, Z., Mao, S., Wu, W., Ge, T., Wei, F., & Ji, H. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 74

Retrieval-Augmented Generative Question Answering for Event Argument Extraction

Du, X., & Ji, H. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 37

Factuality Challenges in the Era of Large Language Models

Augenstein, I., Baldwin, T., Cha, M., Chakraborty, T., Ciampaglia, G. L., Corney, D., DiResta, R., Ferrara, E., Hale, S., Halevy, A., et al. (2023) · arXiv

Misinformation and Its ImpactsEthics and Social Impacts of AI

Cited by 32

R-Tuning: Instructing Large Language Models to Say ‘I Don’t Know’

Zhang, H., Diao, S., Lin, Y., Fung, Y., Lian, Q., Wang, X., Chen, Y., Ji, H., & Zhang, T. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 28

LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

Han, C., Wang, Q., Peng, H., Xiong, W., Chen, Y., Ji, H., & Wang, S. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 22

A Close Look into the Calibration of Pre-trained Language Models

Chen, Y., Yuan, L., Cui, G., Liu, Z., & Ji, H. (2023) · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 22

MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback

Wang, X., Wang, Z., Liu, J., Chen, Y., Yuan, L., Peng, H., & Ji, H. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 18

A Close Look into the Calibration of Pre-trained Language Models

Chen, Y., Yuan, L., Cui, G., Liu, Z., & Ji, H. (2022) · arXiv

Adversarial Robustness in Machine LearningTopic Modeling

Cited by 18

Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-Collaboration

Wang, Z., Mao, S., Wu, W., Ge, T., Wei, F., & Ji, H. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 11

CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets

Yuan, L., Chen, Y., Wang, X., Fung, Y. R., Peng, H., & Ji, H. (2023) · arXiv

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 11

Democratizing LLMs: An Exploration of Cost-Performance Trade-offs in Self-Refined Open-Source Models

Shashidhar, S., Chinta, A., Sahai, V., Wang, Z., & Ji, H. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Topic ModelingNatural Language Processing Techniques

Cited by 9

Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs Evaluations

Yuan, L., Chen, Y., Cui, G., Gao, H., Zou, F., Cheng, X., Ji, H., Liu, Z., & Sun, M. (2023) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 8

Exploiting geolocation, user and temporal information for natural hazards monitoring in Twitter

Fresno, V., Zubiaga, A., Ji, H., & Martínez, R. (2015) · University of Warwick

Public Relations and Crisis CommunicationInformation Retrieval and Search Behavior

Cited by 6

LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

Han, C., Wang, Q., Peng, H., Xiong, W., Chen, Y., Ji, H., & Wang, S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 4

EVEDIT: Event-based Knowledge Editing with Deductive Editing Boundaries

Liu, J., Yu, P., Zhang, Y., Li, S., Zhang, Z., & Ji, H. (2024) · arXiv

Topic ModelingMultimodal Machine Learning Applications

Cited by 1

xRouter: Training Cost-Aware LLMs Orchestration System via Reinforcement Learning

Qian, C., Liu, Z., Kokane, S., Prabhakar, A., Qiu, J., Chen, H., Liu, Z., Ji, H., Yao, W., Heinecke, S., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0

Self-Improving LLM Agents at Test-Time

Acikgoz, E. C., Qian, C., Ji, H., Hakkani-Tür, D., & Tur, G. (2025) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 0

Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models

Wang, R., Wang, H., Xue, B., Li, Y., Pang, J., Liu, S., Chen, Y., Qiu, J., Wong, D. F., Chen, G., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 0