4 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
EvolSQL: Structure-Aware Evolution for Scalable Text-to-SQL Data Synthesis
Xuanguang Pan, Chongyang Tao, Jiayuan Bai +5
Training effective Text-to-SQL models remains challenging due to the scarcity of high-quality, diverse, and structurally complex datasets. Existing methods either rely on limited h…
AIR: Post-training Data Selection for Reasoning via Attention Head Influence
Jinrui Liu, Jeff Wu, Xuanguang Pan +3
LLMs achieve remarkable multi-step reasoning capabilities, yet effectively transferring these skills via post-training distillation remains challenging. Existing data selection met…
LLMs are Also Effective Embedding Models: An In-depth Overview
Chongyang Tao, Tao Shen, Shen Gao +6
Large language models (LLMs) have revolutionized natural language processing by achieving state-of-the-art performance across various tasks. Recently, their effectiveness as embedd…
Leveraging Large Language Models for NLG Evaluation: Advances and Challenges
Zhen Li, Xiaohan Xu, Tao Shen +5
In the rapidly evolving domain of Natural Language Generation (NLG) evaluation, introducing Large Language Models (LLMs) has opened new avenues for assessing generated content qual…