1.5k citations · 1.7k across the 18 of their papers we have counts for
22 papers · 1 filter
Knowledge Prompts: Injecting World Knowledge into Language Models through Soft Prompts
Cicero Nogueira dos Santos, Zhe Dong, Daniel Cer +4
Soft prompts have been recently proposed as a tool for adapting large frozen language models (LMs) to new tasks. In this work, we repurpose soft prompts to the task of injecting wo…
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization
Dheeraj Rajagopal, Siamak Shakeri, Cicero Nogueira dos Santos +2
Abstractive summarization systems based on pretrained language models often generate coherent but factually inconsistent sentences. In this paper, we present a counterfactual data…
ED2LM: Encoder-Decoder to Language Model for Faster Document Re-ranking Inference
Kai Hui, Honglei Zhuang, Tao Chen +8
State-of-the-art neural models typically encode document-query pairs using cross-attention for re-ranking. To this end, models generally utilize an encoder-only (like BERT) paradig…
Joint Text and Label Generation for Spoken Language Understanding
Yang Li, Ben Athiwaratkun, Cicero Nogueira dos Santos +1
Generalization is a central problem in machine learning, especially when data is limited. Using prior information to enforce constraints is the principled way of encouraging genera…
Improving Factual Consistency of Abstractive Summarization via Question Answering
Feng Nan, Cicero Nogueira dos Santos, Henghui Zhu +7
A commonly observed problem with the state-of-the art abstractive summarization models is that the generated summaries can be factually inconsistent with the input documents. The f…
Generative Context Pair Selection for Multi-hop Question Answering
Dheeru Dua, Cicero Nogueira dos Santos, Patrick Ng +4
Compositional reasoning tasks like multi-hop question answering, require making latent decisions to get the final answer, given a question. However, crowdsourced datasets often cap…