Papers with Multi-Hop Inference
TextGraphs 2019 Shared Task on Multi-Hop Inference for Explanation Regeneration (D19-53)
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| Challenge: | Detailed extended analyses of all submitted systems showed large relative improvements in accessing the most challenging multi-hop inference problems, while absolute performance remains low. |
| Approach: | The Shared Task on Multi-Hop Inference for Explanation Regeneration asks participants to regenerate detailed gold explanations for elementary science questions by selecting facts from a knowledge base of semi-structured tables. |
| Outcome: | The top-performing system achieved a mean average precision of 0.56 . the task combines facts from a knowledge base and supervised training data . |
Team SVMrank: Leveraging Feature-rich Support Vector Machines for Ranking Explanations to Elementary Science Questions (D19-53)
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| Challenge: | TextGraphs 2019 Shared Task on Multi-Hop Inference for Explanation Regeneration tackles explanation generation for elementary science questions. |
| Approach: | They propose a hybrid pipelined machine learning model and rule-based system to address MIER-19 . they use a featurerich learning-to-rank machine learning and a rule-driven system to rerank the LTR model predictions. |
| Outcome: | The proposed model was ranked fourth in the evaluation, close to the second and third ranked teams, achieving 39.4% MAP. |