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Found 8 papers, 4 papers with code
Faithful Embeddings for Knowledge Base Queries
We address this problem with a novel QE method that is more faithful to deductive reasoning, and show that this leads to better performance on complex queries to incomplete KBs.
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Bayesian neural networks (BNN) and deep ensembles are principled approaches to estimate the predictive uncertainty of a deep learning model.
How Large Are Lions? Inducing Distributions over Quantitative Attributes
Most current NLP systems have little knowledge about quantitative attributes of objects and events.
Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary
A desirable property of a reference-based evaluation metric that measures the content quality of a summary is that it should estimate how much information that summary has in common with a reference.
Incremental Reading for Question Answering
Current state-of-the-art question answering models reason over an entire passage, not incrementally.
PullNet: Open Domain Question Answering with Iterative Retrieval on Knowledge Bases and Text
We focus on a setting in which a corpus is supplemented with a large but incomplete KB, and on questions that require non-trivial (e. g., ``multi-hop'') reasoning.
Using Domain Knowledge to Guide Dialog Structure Induction via Neural Probabilistic Soft Logic
Dialog Structure Induction (DSI) is the task of inferring the latent dialog structure (i. e., a set of dialog states and their temporal transitions) of a given goal-oriented dialog.
