activity
20202026
most citedA Survey of Natural Language Generation

151 citations · 229 across the 43 of their papers we have counts for

collaborators
Showing 2023 · cs.CLShow all

14 papers · 2 filters

cs.CL2023★ 2 cited

Towards Real-World Writing Assistance: A Chinese Character Checking Benchmark with Faked and Misspelled Characters

Yinghui Li, Zishan Xu, Shaoshen Chen +7

Writing assistance is an application closely related to human life and is also a fundamental Natural Language Processing (NLP) research field. Its aim is to improve the correctness…

cs.CL2023

Retrieval-Augmented Meta Learning for Low-Resource Text Classification

Rongsheng Li, Yangning Li, Yinghui Li +4

Meta learning have achieved promising performance in low-resource text classification which aims to identify target classes with knowledge transferred from source classes with sets…

cs.CL2023

Prompt Learning With Knowledge Memorizing Prototypes For Generalized Few-Shot Intent Detection

Chaiyut Luoyiching, Yangning Li, Yinghui Li +4

Generalized Few-Shot Intent Detection (GFSID) is challenging and realistic because it needs to categorize both seen and novel intents simultaneously. Previous GFSID methods rely on…

cs.CL2023

An Anchor Learning Approach for Citation Field Learning

Zilin Yuan, Borun Chen, Yimeng Dai +3

Citation field learning is to segment a citation string into fields of interest such as author, title, and venue. Extracting such fields from citations is crucial for citation inde…

cs.CL2023★ 3 cited

SeqGPT: An Out-of-the-box Large Language Model for Open Domain Sequence Understanding

Tianyu Yu, Chengyue Jiang, Chao Lou +12

Large language models (LLMs) have shown impressive ability for open-domain NLP tasks. However, LLMs are sometimes too footloose for natural language understanding (NLU) tasks which…

cs.CL2023★ 1 cited

LatEval: An Interactive LLMs Evaluation Benchmark with Incomplete Information from Lateral Thinking Puzzles

Shulin Huang, Shirong Ma, Yinghui Li +4

With the continuous evolution and refinement of LLMs, they are endowed with impressive logical reasoning or vertical thinking capabilities. But can they think out of the box? Do th…