Papers with answer predictor

3 papers
Elaboration-Generating Commonsense Question Answering at Scale (2023.acl-long)

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Challenge: elaborations are generated using language models that generate background knowledge that helps improve performance . human evaluations show that the quality of the generated ellaborations is high .
Approach: They propose to finetune smaller language models to generate useful intermediate context . they compare a language model with an answer predictor and generate elaborations . human evaluations show that the quality of the generated ellaborations is high .
Outcome: The proposed framework outperforms other models on commonsense questions on four commons sense benchmarks.
REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation (2024.acl-long)

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Challenge: Existing knowledge graphs suffer from incompleteness and lack information critical for answering given questions.
Approach: They propose to enhance the open domain question answering model with a knowledge graph generation module that generates KGs from the passages and an answer predictor.
Outcome: The proposed model improves the exact match score by 2.7% on the EntityQuestion dataset, with an average improvement of 1.8% across all the datasets.
A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction (2020.acl-main)

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Challenge: Existing models for machine reading comprehension lack evidence labels for training models.
Approach: They propose a method which supervises the evidence extractor with auto-generated evidence labels in an iterative process.
Outcome: The proposed method improves on three MRC tasks on seven datasets.

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