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Found 5 papers, 1 papers with code
TSOM: Small Object Motion Detection Neural Network Inspired by Avian Visual Circuit
As an inspiration from nature, the avian visual system is capable of processing motion information in various complex aerial scenes, and its Retina-OT-Rt visual circuit is highly sensitive to capturing the motion information of small objects from high altitudes.
EXPLAIN, EDIT, GENERATE: Rationale-Sensitive Counterfactual Data Augmentation for Multi-hop Fact Verification
Experimental results show that the proposed approach outperforms the SOTA baselines and can generate linguistically diverse counterfactual data without disrupting their logical relationships.
Explainable Topic-Enhanced Argument Mining from Heterogeneous Sources
Specifically, with the use of the neural topic model and the language model, the target information is augmented by explainable topic representations.
Consistent Multi-Granular Rationale Extraction for Explainable Multi-hop Fact Verification
The success of deep learning models on multi-hop fact verification has prompted researchers to understand the behavior behind their veracity.
Exploring Faithful Rationale for Multi-hop Fact Verification via Salience-Aware Graph Learning
In specific, GCN is utilized to incorporate the topological interaction information among multiple pieces of evidence for learning evidence representation.
