Papers with knowledge retrieval module

2 papers
Leveraging Explicit Procedural Instructions for Data-Efficient Action Prediction (2023.findings-acl)

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Challenge: a paper presents a data-efficient solution to constructing task-oriented dialogue systems . large language models have shown success in modeling such dialogues, but they require large quantities of data .
Approach: They propose a system that leverages explicit instructions from agent guidelines . they propose dialogue-document matching and action-oriented masked language modeling .
Outcome: The proposed system improves accuracy predicting in- and out-of-distribution actions while preserving high performance in settings with low or sparse data.
An LLM-Enabled Knowledge Elicitation and Retrieval Framework for Zero-Shot Cross-Lingual Stance Identification (2024.findings-emnlp)

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Challenge: Existing research is conducted in monolingual setting on English datasets, whereas in other low-resource languages, it lacks sufficient data for training quality stance detection models.
Approach: They propose a knowledge elicitation and retrieval framework that leverages the capability of large language models for stance knowledge acquisition and matches the target language input to the most relevant stance information.
Outcome: The proposed framework improves on multilingual datasets and competitive baselines.

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