1 citations · 1 across the 2 of their papers we have counts for
3 papers
cs.CL2024
Calibrate to Discriminate: Improve In-Context Learning with Label-Free Comparative Inference
Wei Cheng, Tianlu Wang, Yanmin Ji +3
While in-context learning with large language models (LLMs) has shown impressive performance, we have discovered a unique miscalibration behavior where both correct and incorrect p…
cs.CL2024★ 1 cited
An LLM-Enhanced Adversarial Editing System for Lexical Simplification
Keren Tan, Kangyang Luo, Yunshi Lan +2
Lexical Simplification (LS) aims to simplify text at the lexical level. Existing methods rely heavily on annotated data, making it challenging to apply in low-resource scenarios. I…
cs.CL2024
Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL
Yuanyuan Liang, Keren Tan, Tingyu Xie +4
Graph Databases (Graph DB) find extensive application across diverse domains such as finance, social networks, and medicine. Yet, the translation of Natural Language (NL) into the…