Predicate Detection
8 papers with code • 3 benchmarks • 3 datasets
Detecting predicates in sentences. Semantic frames are defined with respect to predicates. This task is a prerequisite to semantic role labeling.
Benchmarks
These leaderboards are used to track progress in Predicate Detection
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CoNLL
Most implemented papers
Representing Prior Knowledge Using Randomly, Weighted Feature Networks for Visual Relationship Detection
pavliclab/aaai2022-clear2022-visual_relationship_detection-rwfn
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AAAI Workshop CLeaR 2022
Furthermore, background knowledge represented by RWFNs can be used to alleviate the incompleteness of training sets even though the space complexity of RWFNs is much smaller than LTNs (1:27 ratio).
Deep Semantic Role Labeling: What Works and What's Next
We introduce a new deep learning model for semantic role labeling (SRL) that significantly improves the state of the art, along with detailed analyses to reveal its strengths and limitations.
Linguistically-Informed Self-Attention for Semantic Role Labeling
Unlike previous models which require significant pre-processing to prepare linguistic features, LISA can incorporate syntax using merely raw tokens as input, encoding the sequence only once to simultaneously perform parsing, predicate detection and role labeling for all predicates.
Weighted Training for Cross-Task Learning
In this paper, we introduce Target-Aware Weighted Training (TAWT), a weighted training algorithm for cross-task learning based on minimizing a representation-based task distance between the source and target tasks.
Comparison of single and multitask learning for predicting cognitive decline based on MRI data
The Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) is a neuropsychological tool that has been designed to assess the severity of cognitive symptoms of dementia.
Contextualized Semantic Distance between Highly Overlapped Texts
Stareru/NeighboringDistributionDivergence
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Overlapping frequently occurs in paired texts in natural language processing tasks like text editing and semantic similarity evaluation.
A Novel Metric for Evaluating Semantics Preservation
Stareru/NeighboringDistributionDivergence
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ACL ARR October 2021
By exploiting the property of NDD, we implement a unsupervised and even training-free algorithm for extractive sentence compression.
Self-Supervised Learning for Visual Relationship Detection through Masked Bounding Box Reconstruction
deeplab-ai/selfsupervisedvrd
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We present a novel self-supervised approach for representation learning, particularly for the task of Visual Relationship Detection (VRD).
