2 citations · 2 across the 2 of their papers we have counts for
3 papers
cs.CL2024
Dancing in Chains: Reconciling Instruction Following and Faithfulness in Language Models
Zhengxuan Wu, Yuhao Zhang, Peng Qi +6
Modern language models (LMs) need to follow human instructions while being faithful; yet, they often fail to achieve both. Here, we provide concrete evidence of a trade-off between…
cs.CL2022
longhorns at DADC 2022: How many linguists does it take to fool a Question Answering model? A systematic approach to adversarial attacks
Venelin Kovatchev, Trina Chatterjee, Venkata S Govindarajan +9
Developing methods to adversarially challenge NLP systems is a promising avenue for improving both model performance and interpretability. Here, we describe the approach of the tea…
cs.CL2016★ 2 cited
Learning Word Embeddings from Intrinsic and Extrinsic Views
Jifan Chen, Kan Chen, Xipeng Qiu +3
While word embeddings are currently predominant for natural language processing, most of existing models learn them solely from their contexts. However, these context-based word em…