Papers with mapping process
A Benchmark for Recipe Understanding in Artificial Agents (2024.lrec-main)
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Jens Nevens, Robin de Haes, Rachel Ringe, Mihai Pomarlan, Robert Porzel, Katrien Beuls, Paul van Eecke
| Challenge: | a benchmark has been designed to evaluate whether artificial agents are able to understand how to perform everyday activities. |
| Approach: | They propose a benchmark task that maps a recipe to a set of cooking actions that are precise enough to be executed in the simulated kitchen. |
| Outcome: | The proposed benchmark consists of mapping a recipe to a set of cooking actions that is precise enough to be executed in the simulated kitchen and yields the desired dish. |
Mapping Text to Knowledge Graph Entities using Multi-Sense LSTMs (D18-1)
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| Challenge: | a paper addresses the problem of mapping natural language text to knowledge base entities. |
| Approach: | They propose a model for mapping natural language text to knowledge base entities using a multi-dimensional entity space obtained from a knowledge graph. |
| Outcome: | The proposed model is applied to large-scale text-to-entity mapping and entity classification tasks with state-of-the-art results. |
Multi Modal Distance - An Approach to Stemma Generation With Weighting (L18-1)
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| Challenge: | Stemma generation is a task where manuscripts are copied and copied from each other and from M. Existing methods to generate stemma using unweighted token similarity weighting have been used. |
| Approach: | They propose to use a distance model to weight the texts of M1 and M2 to estimate the most likely tree from a series of mapping processes. |
| Outcome: | The proposed method is small in the experimental scenario(s) it is based on psycholinguistically gained distance matrices of letters in three modalities: vision, audition and motorics. |