Liu, Zhiyuan

MoEfication: Transformer Feed-forward Layers are Mixtures of Experts

Zhang, Z., Lin, Y., Liu, Z., Li, P., Sun, M., & Zhou, J. (2022) · Findings of the Association for Computational Linguistics: ACL 2022

Advanced Neural Network ApplicationsTopic Modeling

Cited by 48

AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Chen, W., Su, Y., Zuo, J., Yang, C., Yuan, C., Chan, C.-M., Yu, H., Lu, Y., Hung, Y.-H., Qian, C., et al. (2023) · arXiv

Multi-Agent Systems and NegotiationDistributed Control Multi-Agent Systems

Cited by 39

KoLA: Carefully Benchmarking World Knowledge of Large Language Models

Yu, J., Wang, X., Tu, S., Cao, S., Zhang-Li, D., Lv, X., Peng, H., Yao, Z., Zhang, X., Li, H., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 29

MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies

Hu, S., Tu, Y., Han, X., He, C., Cui, G., Long, X., Zheng, Z., Fang, Y., Huang, Y., Zhao, W., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 28

Finding Skill Neurons in Pre-trained Transformer-based Language Models

Wang, X., Wen, K., Zhang, Z., Hou, L., Liu, Z., & Li, J. (2022) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 28

∞Bench: Extending Long Context Evaluation Beyond 100K Tokens

Zhang, X., Chen, Y., Hu, S., Xu, Z., Chen, J., Hao, M., Han, X., Thai, Z., Wang, S., Liu, Z., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 27

Densing law of LLMs

Xiao, C., Cai, J., Zhao, W., Lin, B., Zeng, G., Zhou, J., Zheng, Z., Han, X., Liu, Z., & Sun, M. (2025) · Nature Machine Intelligence

Topic ModelingNatural Language Processing Techniques

Cited by 24

CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models

Qian, C., Han, C., Fung, Y., Qin, Y., Liu, Z., & Ji, H. (2023) · Findings of the Association for Computational Linguistics: EMNLP 2023

Topic ModelingNatural Language Processing Techniques

Cited by 24

UltraFeedback: Boosting Language Models with Scaled AI Feedback

Cui, G., Yuan, L., Ding, N., Yao, G., He, B., Zhu, W., Ni, Y., Xie, G., Xie, R., Lin, Y., et al. (2023) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 23

StableToolBench: Towards Stable Large-Scale Benchmarking on Tool Learning of Large Language Models

Guo, Z., Cheng, S., Wang, H., Liang, S., Qin, Y., Li, P., Liu, Z., Sun, M., & Liu, Y. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

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

Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Models

Ding, N., Qin, Y., Yang, G., Wei, F., Yang, Z., Su, Y., Hu, S., Chen, Y., Chan, C.-M., Chen, W., et al. (2022) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 20

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

Augmentation-Adapted Retriever Improves Generalization of Language Models as Generic Plug-In

Yu, Z., Xiong, C., Yu, S., & Liu, Z. (2023) · arXiv

Topic ModelingInformation Retrieval and Search Behavior

Cited by 17

Beat LLMs at their own game: Zero-shot LLM-generated text detection via querying ChatGPT

Zhu, B., Yuan, L., Cui, G., Chen, Y., Fu, C., He, B., Deng, Y., Liu, Z., Sun, M., & Gu, M. (2023) · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing

Authorship Attribution and ProfilingTopic Modeling

Cited by 16

InfLLM: Training-Free Long-Context Extrapolation for LLMs with an Efficient Context Memory

Xiao, C., Zhang, P., Han, X., Xiao, G., Lin, Y., Zhang, Z., Liu, Z., & Sun, M. (2024) · Advances in Neural Information Processing Systems 37

Topic ModelingNatural Language Processing Techniques

Cited by 14

Scaling Large Language Model-based Multi-Agent Collaboration

Qian, C., Xie, Z., Wang, Y., Liu, W., Zhu, K., Xia, H., Dang, Y., Du, Z., Chen, W., Yang, C., et al. (2024) · arXiv

Multi-Agent Systems and NegotiationTopic Modeling

Cited by 8

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

$\infty$Bench: Extending Long Context Evaluation Beyond 100K Tokens

Zhang, X., Chen, Y., Hu, S., Xu, Z., Chen, J., Hao, M. K., Han, X., Thai, Z. L., Wang, S., Liu, Z., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

AutoReproduce: Automatic AI Experiment Reproduction with Paper Lineage

Zhao, X., Sang, Z., Li, Y., Shi, Q., Zhao, W., Wang, S., Zhang, D., Han, X., Liu, Z., & Sun, M. (2025) · arXiv

Scientific Computing and Data ManagementSoftware Engineering Research

Cited by 0