Yang, Jingfeng

Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond

Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Yin, B., & Hu, X. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 644

Harnessing the power of llms in practice: a survey on chatGPT and beyond

Yang, J., Jin, H., Tang, R., Han, X., Feng, Q., Jiang, H., Zhong, S., Yin, B., & Hu, X. (2024) · ACM Transactions on Knowledge Discovery from Data

Topic ModelingNatural Language Processing Techniques

Cited by 644

TableFormer: Robust Transformer Modeling for Table-Text Encoding

Yang, J., Gupta, A., Upadhyay, S., He, L., Goel, R., & Paul, S. (2022) · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingMultimodal Machine Learning Applications

Cited by 85

SEQZERO: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models

Yang, J., Jiang, H., Yin, Q., Zhang, D., Yin, B., & Yang, D. (2022) · Findings of the Association for Computational Linguistics: NAACL 2022

Topic ModelingNatural Language Processing Techniques

Cited by 15

Inductive or Deductive? Rethinking the Fundamental Reasoning Abilities of LLMs

Cheng, K., Yang, J., Jiang, H., Wang, Z., Huang, B., Li, R., Li, S., Li, Z., Gao, Y., Li, X., et al. (2024) · arXiv

Topic ModelingLogic, Reasoning, and Knowledge

Cited by 4