Despite their impressive performance on diverse tasks, large language mo...
Knowledge bases (KBs) are often incomplete and constantly changing in
pr...
In typical machine learning systems, an estimate of the probability of t...
Question answering (QA) over real-world knowledge bases (KBs) is challen...
At the foundation of scientific evaluation is the labor-intensive proces...
It is often challenging for a system to solve a new complex problem from...
Abstractive summarization is the task of compressing a long document int...
A case-based reasoning (CBR) system solves a new problem by retrieving
`...
We present a surprisingly simple yet accurate approach to reasoning in
k...
Given questions regarding some prototypical situation – such as Name
som...
General Question Answering (QA) systems over texts require the multi-hop...
Multi-hop question answering (QA) requires an information retrieval (IR)...
String similarity models are vital for record linkage, entity resolution...
This paper introduces a new framework for open-domain question answering...
A significant amount of information in today's world is stored in struct...
We propose a neural machine-reading model that constructs dynamic knowle...
The recent work of Clark et al. introduces the AI2 Reasoning Challenge (...
This paper aims at improving how machines can answer questions directly ...
Knowledge bases (KB), both automatically and manually constructed, are o...
Existing question answering methods infer answers either from a knowledg...
Our goal is to combine the rich multistep inference of symbolic logical
...