BeamSearchQA: Large Language Models are Strong Zero-Shot QA Solver

by   Hao Sun, et al.
Peking University

Open-domain question answering is a crucial task that often requires accessing external information. Existing methods typically adopt a single-turn retrieve-then-read approach, where relevant documents are first retrieved, and questions are then answered based on the retrieved information. However, there are cases where answering a question requires implicit knowledge that is not directly retrievable from the question itself. In this work, we propose a novel question-answering pipeline called eamSearchQA. Our approach leverages large language models(LLMs) to iteratively generate new questions about the original question, enabling an iterative reasoning process. By iteratively refining and expanding the scope of the question, our method aims to capture and utilize hidden knowledge that may not be directly obtainable through retrieval. We evaluate our approach on the widely-used open-domain NQ and WebQ datasets. The experimental results demonstrate that BeamSearchQA significantly outperforms other zero-shot baselines, indicating its effectiveness in tackling the challenges of open-domain question answering.


page 1

page 2

page 3

page 4


Knowledge Fusion and Semantic Knowledge Ranking for Open Domain Question Answering

Open Domain Question Answering requires systems to retrieve external kno...

Improving Passage Retrieval with Zero-Shot Question Generation

We propose a simple and effective re-ranking method for improving passag...

IfQA: A Dataset for Open-domain Question Answering under Counterfactual Presuppositions

Although counterfactual reasoning is a fundamental aspect of intelligenc...

Language Models as Fact Checkers?

Recent work has suggested that language models (LMs) store both common-s...

FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering

Knowledge base question answering (KBQA) is a critical yet challenging t...

Large Language Models are Built-in Autoregressive Search Engines

Document retrieval is a key stage of standard Web search engines. Existi...

Exploiting Abstract Meaning Representation for Open-Domain Question Answering

The Open-Domain Question Answering (ODQA) task involves retrieving and s...

Please sign up or login with your details

Forgot password? Click here to reset