2 citations · 3 across the 7 of their papers we have counts for
7 papers
PID Control-Based Self-Healing to Improve the Robustness of Large Language Models
Zhuotong Chen, Zihu Wang, Yifan Yang +2
Despite the effectiveness of deep neural networks in numerous natural language processing applications, recent findings have exposed the vulnerability of these language models when…
See the Unseen: Better Context-Consistent Knowledge-Editing by Noises
Youcheng Huang, Wenqiang Lei, Zheng Zhang +2
Knowledge-editing updates knowledge of large language models (LLMs) and contributes to the interpretability and application of LLMs. However, knowledge applying is context-consiste…
A Self-enhancement Approach for Domain-specific Chatbot Training via Knowledge Mining and Digest
Ruohong Zhang, Luyu Gao, Chen Zheng +6
Large Language Models (LLMs), despite their great power in language generation, often encounter challenges when dealing with intricate and knowledge-demanding queries in specific d…
Click: Controllable Text Generation with Sequence Likelihood Contrastive Learning
Chujie Zheng, Pei Ke, Zheng Zhang +1
It has always been an important yet challenging problem to control language models to avoid generating texts with undesirable attributes, such as toxic language and unnatural repet…
An AMR-based Link Prediction Approach for Document-level Event Argument Extraction
Yuqing Yang, Qipeng Guo, Xiangkun Hu +3
Recent works have introduced Abstract Meaning Representation (AMR) for Document-level Event Argument Extraction (Doc-level EAE), since AMR provides a useful interpretation of compl…
Exploiting Abstract Meaning Representation for Open-Domain Question Answering
Cunxiang Wang, Zhikun Xu, Qipeng Guo +4
The Open-Domain Question Answering (ODQA) task involves retrieving and subsequently generating answers from fine-grained relevant passages within a database. Current systems levera…