87 citations · 347 across the 47 of their papers we have counts for
5 papers · 1 filter
The KITMUS Test: Evaluating Knowledge Integration from Multiple Sources in Natural Language Understanding Systems
Akshatha Arodi, Martin Pömsl, Kaheer Suleman +3
Many state-of-the-art natural language understanding (NLU) models are based on pretrained neural language models. These models often make inferences using information from multiple…
Question Personalization in an Intelligent Tutoring System
Sabina Elkins, Robert Belfer, Ekaterina Kochmar +2
This paper investigates personalization in the field of intelligent tutoring systems (ITS). We hypothesize that personalization in the way questions are asked improves student lear…
MaskEval: Weighted MLM-Based Evaluation for Text Summarization and Simplification
Yu Lu Liu, Rachel Bawden, Thomas Scialom +2
In text summarization and simplification, system outputs must be evaluated along multiple dimensions such as relevance, factual consistency, fluency, and grammaticality, and a wide…
Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment
Zichao Li, Prakhar Sharma, Xing Han Lu +2
Most research on question answering focuses on the pre-deployment stage; i.e., building an accurate model for deployment. In this paper, we ask the question: Can we improve QA syst…
Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation
Kushal Arora, Layla El Asri, Hareesh Bahuleyan +1
Current language generation models suffer from issues such as repetition, incoherence, and hallucinations. An often-repeated hypothesis is that this brittleness of generation model…