Zhang, Yizhe

DIALOGPT : Large-Scale Generative Pre-training for Conversational Response Generation

Zhang, Y., Sun, S., Galley, M., Chen, Y.-C., Brockett, C., Gao, X., Gao, J., Liu, J., & Dolan, B. (2020) · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations

Speech and dialogue systemsTopic Modeling

Cited by 1,076

What Makes Good In-Context Examples for GPT-3?

Liu, J., Shen, D., Zhang, Y., Dolan, B., Carin, L., & Chen, W. (2022) · Proceedings of Deep Learning Inside Out (DeeLIO 2022): The 3rd Workshop on Knowledge Extraction and Integration for Deep Learning Architectures

Topic ModelingNatural Language Processing Techniques

Cited by 563

Baseline Needs More Love: On Simple Word-Embedding-Based Models and Associated Pooling Mechanisms

Shen, D., Wang, G., Wang, W., Min, M. R., Su, Q., Zhang, Y., Li, C., Henao, R., & Carin, L. (2018) · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingSentiment Analysis and Opinion Mining

Cited by 328

What Makes Good In-Context Examples for GPT-$3$?

Liu, J., Shen, D., Zhang, Y., Dolan, B., Carin, L., & Chen, W. (2021) · arXiv

Topic ModelingDomain Adaptation and Few-Shot Learning

Cited by 148

A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation

Liu, T., Zhang, Y., Brockett, C., Mao, Y., Sui, Z., Chen, W., & Dolan, B. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 63

Highly accurate ab initio gene annotation with ANNEVO

Zhang, P., Xu, T., Wang, S., Yang, X., Sun, P., Jia, P., Lin, J., Wang, B., Zhang, Y., Meng, D., et al. (2026) · Nature Methods

Genomics and Phylogenetic StudiesMachine Learning in Bioinformatics

Cited by 34

RetGen: A Joint Framework for Retrieval and Grounded Text Generation Modeling

Zhang, Y., Sun, S., Gao, X., Fang, Y., Brockett, C., Galley, M., Gao, J., & Dolan, B. (2022) · Proceedings of the AAAI Conference on Artificial Intelligence

Topic ModelingInformation Retrieval and Search Behavior

Cited by 27

Executable Code Actions Elicit Better LLM Agents

Wang, X., Chen, Y., Yuan, L., Zhang, Y., Li, Y., Peng, H., & Ji, H. (2024) · arXiv

AI-based Problem Solving and PlanningSoftware Engineering Research

Cited by 23

A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation

Liu, T., Zhang, Y., Brockett, C., Mao, Y., Sui, Z., Chen, W., & Dolan, B. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 12

On the Way to LLM Personalization: Learning to Remember User Conversations

Magister, L. C., Metcalf, K., Zhang, Y., & ter Hoeve, M. (2024) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 6

ToolSandbox: A Stateful, Conversational, Interactive Evaluation Benchmark for LLM Tool Use Capabilities

Lu, J., Holleis, T., Zhang, Y., Aumayer, B., Nan, F., Bai, F., Ma, S., Ma, S., Li, M., Yin, G., et al. (2024) · arXiv

Speech and dialogue systemsTopic Modeling

Cited by 2

Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling

Maini, P., Seto, S., Bai, H., Grangier, D., Zhang, Y., & Jaitly, N. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1