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Found 9 papers, 7 papers with code
CausalQA: A Benchmark for Causal Question Answering
At least 5% of questions submitted to search engines ask about cause-effect relationships in some way.
Causal Question Answering with Reinforcement Learning
We introduce an Actor-Critic-based agent which learns to search through the graph to answer causal questions.
Universal Knowledge Graph Embeddings
Most of them obtain embeddings by learning the structure of the knowledge graph within a link prediction setting.
LitCQD: Multi-Hop Reasoning in Incomplete Knowledge Graphs with Numeric Literals
We evaluate LitCQD on query types with and without literal values.
Explaining $\mathcal{ELH}$ Concept Descriptions through Counterfactual Reasoning
Knowledge bases are widely used for information management, enabling high-impact applications such as web search, question answering, and natural language processing.
Neural Class Expression Synthesis
Our main intuition is that class expression learning can be regarded as a translation problem.
EvoLearner: Learning Description Logics with Evolutionary Algorithms
We contribute a novel initialization method for the initial population: starting from positive examples, we perform biased random walks and translate them to description logic concepts.
Learning Concept Lengths Accelerates Concept Learning in ALC
We then extend the CELOE algorithm, which learns ALC concepts, with our concept length predictor.
Convolutional Hypercomplex Embeddings for Link Prediction
We propose the four approaches QMult, OMult, ConvQ and ConvO to tackle the link prediction problem.
