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Found 7 papers, 6 papers with code
Factually Consistent Summarization via Reinforcement Learning with Textual Entailment Feedback
Despite the seeming success of contemporary grounded text generation systems, they often tend to generate factually inconsistent text with respect to their input.
Abstractive Text Summarization
Natural Language Inference
+2
Controlled Text Reduction
Producing a reduced version of a source text, as in generic or focused summarization, inherently involves two distinct subtasks: deciding on targeted content and generating a coherent text conveying it.
LM-Debugger: An Interactive Tool for Inspection and Intervention in Transformer-Based Language Models
The opaque nature and unexplained behavior of transformer-based language models (LMs) have spurred a wide interest in interpreting their predictions.
Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations
NLP models that compare or consolidate information across multiple documents often struggle when challenged with recognizing substantial information redundancies across the texts.
QA-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositions
Multi-text applications, such as multi-document summarization, are typically required to model redundancies across related texts.
Asking It All: Generating Contextualized Questions for any Semantic Role
We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage.
Controlled Crowdsourcing for High-Quality QA-SRL Annotation
Question-answer driven Semantic Role Labeling (QA-SRL) was proposed as an attractive open and natural flavour of SRL, potentially attainable from laymen.
