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Found 8 papers, 4 papers with code
A Divide-And-Conquer Approach for Multi-label Multi-hop Relation Detection in Knowledge Base Question Answering
However, most of existing approaches only detect one single path to obtain the answer without considering other correct paths, which might affect the final performance.
Beyond Text: Incorporating Metadata and Label Structure for Multi-Label Document Classification using Heterogeneous Graphs
The other is label heterogeneous graph, which is constructed based on both the labels’ hierarchy and their statistical dependencies.
A Novel Framework Based on Medical Concept Driven Attention for Explainable Medical Code Prediction via External Knowledge
Medical code prediction from clinical notes aims at automatically associating medical codes with the clinical notes.
SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting
Temporal complex event forecasting aims to predict the future events given the observed events from history.
Context-aware Event Forecasting via Graph Disentanglement
The task of event forecasting aims to model the relational and temporal patterns based on historical events and makes forecasting to what will happen in the future.
Structured and Natural Responses Co-generation for Conversational Search
Existing approaches either 1) predict structured dialog acts first and then generate natural response; or 2) map conversation context to natural responses directly in an end-to-end manner.
Decoupling Strategy and Surface Realization for Task-oriented Dialogues
The core is to construct a latent content space for strategy optimization and disentangle the surface style from it.
Neural Topic Modeling with Bidirectional Adversarial Training
Recent years have witnessed a surge of interests of using neural topic models for automatic topic extraction from text, since they avoid the complicated mathematical derivations for model inference as in traditional topic models such as Latent Dirichlet Allocation (LDA).
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