80 citations · 281 across the 33 of their papers we have counts for
4 papers · 2 filters
Making Large Language Models Better Reasoners with Alignment
Peiyi Wang, Lei Li, Liang Chen +5
Reasoning is a cognitive process of using evidence to reach a sound conclusion. The reasoning capability is essential for large language models (LLMs) to serve as the brain of the…
Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledge
Jiangjie Chen, Wei Shi, Ziquan Fu +3
Large language models (LLMs) have been widely studied for their ability to store and utilize positive knowledge. However, negative knowledge, such as "lions don't live in the ocean…
Revisiting k-NN for Fine-tuning Pre-trained Language Models
Lei Li, Jing Chen, Bozhong Tian +1
Pre-trained Language Models (PLMs), as parametric-based eager learners, have become the de-facto choice for current paradigms of Natural Language Processing (NLP). In contrast, k-N…
One Model for All Domains: Collaborative Domain-Prefix Tuning for Cross-Domain NER
Xiang Chen, Lei Li, Shuofei Qiao +5
Cross-domain NER is a challenging task to address the low-resource problem in practical scenarios. Previous typical solutions mainly obtain a NER model by pre-trained language mode…