Science Question Answering

6 papers with code • 1 benchmarks • 2 datasets

Most implemented papers

Multimodal Chain-of-Thought Reasoning in Language Models

amazon-science/mm-cot 2 Feb 2023

Large language models (LLMs) have shown impressive performance on complex reasoning by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains as the rationale to infer the answer.

Unification-based Reconstruction of Multi-hop Explanations for Science Questions

ai-systems/unification_reconstruction_explanations EACL 2021

This paper presents a novel framework for reconstructing multi-hop explanations in science Question Answering (QA).

Dynamic Semantic Graph Construction and Reasoning for Explainable Multi-hop Science Question Answering

wwxu21/AMR-SG Findings (ACL) 2021

Our framework contains three new ideas: (a) {\tt AMR-SG}, an AMR-based Semantic Graph, constructed by candidate fact AMRs to uncover any hop relations among question, answer and multiple facts.

Exploiting Reasoning Chains for Multi-hop Science Question Answering

wwxu21/cgr Findings (EMNLP) 2021

We propose a novel Chain Guided Retriever-reader ({\tt CGR}) framework to model the reasoning chain for multi-hop Science Question Answering.

Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering

lupantech/ScienceQA 20 Sep 2022

We further design language models to learn to generate lectures and explanations as the chain of thought (CoT) to mimic the multi-hop reasoning process when answering ScienceQA questions.

Two is Better than Many? Binary Classification as an Effective Approach to Multi-Choice Question Answering

declare-lab/team 29 Oct 2022

We show the efficacy of our proposed approach in different tasks -- abductive reasoning, commonsense question answering, science question answering, and sentence completion.