343 citations · 361 across the 9 of their papers we have counts for
7 papers · 1 filter
Addressing Both Statistical and Causal Gender Fairness in NLP Models
Hannah Chen, Yangfeng Ji, David Evans
Statistical fairness stipulates equivalent outcomes for every protected group, whereas causal fairness prescribes that a model makes the same prediction for an individual regardles…
Blending Reward Functions via Few Expert Demonstrations for Faithful and Accurate Knowledge-Grounded Dialogue Generation
Wanyu Du, Yangfeng Ji
The development of trustworthy conversational information-seeking systems relies on dialogue models that can generate faithful and accurate responses based on relevant knowledge te…
Pre-training Transformers for Knowledge Graph Completion
Sanxing Chen, Hao Cheng, Xiaodong Liu +3
Learning transferable representation of knowledge graphs (KGs) is challenging due to the heterogeneous, multi-relational nature of graph structures. Inspired by Transformer-based p…
Improving Interpretability via Explicit Word Interaction Graph Layer
Arshdeep Sekhon, Hanjie Chen, Aman Shrivastava +3
Recent NLP literature has seen growing interest in improving model interpretability. Along this direction, we propose a trainable neural network layer that learns a global interact…
Simple Text Detoxification by Identifying a Linear Toxic Subspace in Language Model Embeddings
Andrew Wang, Mohit Sudhakar, Yangfeng Ji
Large pre-trained language models are often trained on large volumes of internet data, some of which may contain toxic or abusive language. Consequently, language models encode tox…
Entity-Augmented Distributional Semantics for Discourse Relations
Yangfeng Ji, Jacob Eisenstein
Discourse relations bind smaller linguistic elements into coherent texts. However, automatically identifying discourse relations is difficult, because it requires understanding the…