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Found 9 papers, 5 papers with code
Timeline-based Sentence Decomposition with In-Context Learning for Temporal Fact Extraction
In addition, we evaluate the performance of LLMs for direct temporal fact extraction and get unsatisfactory results.
RAM: Towards an Ever-Improving Memory System by Learning from Communications
We introduce an innovative RAG-based framework with an ever-improving memory.
Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern Retrieval
We propose Evidence Pattern Retrieval (EPR) to explicitly model the structural dependencies during subgraph extraction.
Conflict Detection for Temporal Knowledge Graphs:A Fast Constraint Mining Algorithm and New Benchmarks
Temporal facts, which are used to describe events that occur during specific time periods, have become a topic of increased interest in the field of knowledge graph (KG) research.
PaTeCon: A Pattern-Based Temporal Constraint Mining Method for Conflict Detection on Knowledge Graphs
Temporal facts, the facts for characterizing events that hold in specific time periods, are attracting rising attention in the knowledge graph (KG) research communities.
Semantic Framework based Query Generation for Temporal Question Answering over Knowledge Graphs
Answering factual questions with temporal intent over knowledge graphs (temporal KGQA) attracts rising attention in recent years.
Automatic Rule Generation for Time Expression Normalization
The understanding of time expressions includes two sub-tasks: recognition and normalization.
Spatio-Temporal Neural Network for Fitting and Forecasting COVID-19
We established a Spatio-Temporal Neural Network, namely STNN, to forecast the spread of the coronavirus COVID-19 outbreak worldwide in 2020.
A Difference-of-Convex Programming Approach With Parallel Branch-and-Bound For Sentence Compression Via A Hybrid Extractive Model
In this paper, we design a hybrid extractive sentence compression model combining a probability language model and a parse tree language model for compressing sentences by guaranteeing the syntax correctness of the compression results.
