Supervising model attention with human explanations for robust natural language inference
Abstract Natural Language Inference (NLI) models are known to learn from biases and
artefacts within their training data, impacting how well they generalise to other unseen …
artefacts within their training data, impacting how well they generalise to other unseen …
Generating knowledge aware explanation for natural language inference
Natural language inference (NLI) is an increasingly important task of natural language
processing, and the explainable NLI generates natural language explanations (NLEs) in …
processing, and the explainable NLI generates natural language explanations (NLEs) in …
Profiling users for question answering communities via flow-based constrained co-embedding model
In this article, we study the task of user profiling in question answering communities (QACs).
Previous user profiling algorithms suffer from a number of defects: they regard users and …
Previous user profiling algorithms suffer from a number of defects: they regard users and …
Natural language generation using sequential models: a survey
AK Pandey, SS Roy - Neural Processing Letters, 2023 - Springer
Abstract Natural Language Generation (NLG) is one of the most critical yet challenging tasks
in all Natural Language Processing applications. It is a process to automate text generation …
in all Natural Language Processing applications. It is a process to automate text generation …
RNSC: A hierarchical deep learning model for net promoter scoring understanding by combining review and note through semantic consistency
X Shi, Q Wei - Knowledge-Based Systems, 2024 - Elsevier
Abstract The Net Promoter Score (NPS) is a widely-used metric for measuring customer
loyalty and is an essential element in customer service analysis. To understand and analyze …
loyalty and is an essential element in customer service analysis. To understand and analyze …
Text-in-context: Token-level error detection for table-to-text generation
We present our Charles-UPF submission for the Shared Task on Evaluating Accuracy in
Generated Texts at INLG 2021. Our system can detect the errors automatically using a …
Generated Texts at INLG 2021. Our system can detect the errors automatically using a …
Explainable natural language inference via identifying important rationales
Natural language inference (NLI) is an important task in the field of natural language
processing (NLP), which requires certain common sense and logical reasoning abilities …
processing (NLP), which requires certain common sense and logical reasoning abilities …
Conditional Natural Language Inference
To properly explain sentence pairs that provide contradictory (different) information for
different conditions, we introduce the task of conditional natural language inference (Cond …
different conditions, we introduce the task of conditional natural language inference (Cond …
Discovering Biases in Information Retrieval Models Using Relevance Thesaurus as Global Explanation
Most efforts in interpreting neural relevance models have focused on local explanations,
which explain the relevance of a document to a query but are not useful in predicting the …
which explain the relevance of a document to a query but are not useful in predicting the …
[HTML][HTML] Natural Language Inference with Transformer Ensembles and Explainability Techniques
I Perikos, S Souli - Electronics, 2024 - mdpi.com
Background: Open Access Editor's Choice Article Natural Language Inference with
Transformer Ensembles and Explainability Techniques by Isidoros Perikos 1, 2,* and Spyro …
Transformer Ensembles and Explainability Techniques by Isidoros Perikos 1, 2,* and Spyro …