Papers with retrieval-based systems

3 papers
Answer Generation for Retrieval-based Question Answering Systems (2021.findings-acl)

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Challenge: Question Answering systems are a core component of many commercial applications . answer sentence selection (AS2) models are trained to select the best answer sentence .
Approach: They propose to train a sequence to sequence transformer model to generate an answer from a set of candidates.
Outcome: The proposed model improves accuracy by 32 points over the state-of-the-art model on English AS2 datasets.
Measuring Retrieval Complexity in Question Answering Systems (2024.findings-acl)

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Challenge: a new metric, retrieval complexity (RC), measures the difficulty of answering questions.
Approach: They propose a retrieval complexity metric conditioned on the completeness of retrieved documents . they propose an unsupervised pipeline to measure RC given an arbitrary retrieval system .
Outcome: The proposed pipeline measures RC more accurately than alternative estimators on six challenging QA benchmarks.
Enhancing Study-Level Inference from Clinical Trial Papers via Reinforcement Learning-Based Numeric Reasoning (2025.emnlp-main)

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Challenge: Prior work has framed this task as a textual inference task by retrieving relevant content fragments and inferring conclusions from them.
Approach: They propose to extract structured numerical evidence and apply domain knowledge informed logic to derive outcome-specific conclusions.
Outcome: The proposed approach outperforms general-purpose LLMs of over 400B parameters and achieves a 21% improvement in F1 score over retrieval-based systems.

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