4 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CL2024
Synthesizing Text-to-SQL Data from Weak and Strong LLMs
Jiaxi Yang, Binyuan Hui, Min Yang +3
The capability gap between open-source and closed-source large language models (LLMs) remains a challenge in text-to-SQL tasks. In this paper, we introduce a synthetic data approac…
cs.CL2024★ 4 cited
Self-play with Execution Feedback: Improving Instruction-following Capabilities of Large Language Models
Guanting Dong, Keming Lu, Chengpeng Li +4
One core capability of large language models (LLMs) is to follow natural language instructions. However, the issue of automatically constructing high-quality training data to enhan…
cs.CV2023★ 3 cited
JOTR: 3D Joint Contrastive Learning with Transformers for Occluded Human Mesh Recovery
Jiahao Li, Zongxin Yang, Xiaohan Wang +3
In this study, we focus on the problem of 3D human mesh recovery from a single image under obscured conditions. Most state-of-the-art methods aim to improve 2D alignment technologi…