Multi-hop Question Answering

56 papers with code • 2 benchmarks • 4 datasets

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Libraries

Use these libraries to find Multi-hop Question Answering models and implementations

Most implemented papers

Repurposing Entailment for Multi-Hop Question Answering Tasks

StonyBrookNLP/multee NAACL 2019

We introduce Multee, a general architecture that can effectively use entailment models for multi-hop QA tasks.

QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering

michiyasunaga/qagnn NAACL 2021

The problem of answering questions using knowledge from pre-trained language models (LMs) and knowledge graphs (KGs) presents two challenges: given a QA context (question and answer choice), methods need to (i) identify relevant knowledge from large KGs, and (ii) perform joint reasoning over the QA context and KG.

Cognitive Graph for Multi-Hop Reading Comprehension at Scale

THUDM/CogQA ACL 2019

We propose a new CogQA framework for multi-hop question answering in web-scale documents.

Multi-hop Question Answering via Reasoning Chains

soujanyarbhat/aNswER_multirc 7 Oct 2019

Our analysis shows the properties of chains that are crucial for high performance: in particular, modeling extraction sequentially is important, as is dealing with each candidate sentence in a context-aware way.

Commonsense for Generative Multi-Hop Question Answering Tasks

yicheng-w/CommonSenseMultiHopQA EMNLP 2018

We instead focus on a more challenging multi-hop generative task (NarrativeQA), which requires the model to reason, gather, and synthesize disjoint pieces of information within the context to generate an answer.

Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings

malllabiisc/EmbedKGQA ACL 2020

In a separate line of research, KG embedding methods have been proposed to reduce KG sparsity by performing missing link prediction.

Rethinking Label Smoothing on Multi-hop Question Answering

yinzhangyue/smoothing-r3 19 Dec 2022

Multi-Hop Question Answering (MHQA) is a significant area in question answering, requiring multiple reasoning components, including document retrieval, supporting sentence prediction, and answer span extraction.

Analyzing the Effectiveness of the Underlying Reasoning Tasks in Multi-hop Question Answering

alab-nii/multi-hop-analysis 12 Feb 2023

To explain the predicted answers and evaluate the reasoning abilities of models, several studies have utilized underlying reasoning (UR) tasks in multi-hop question answering (QA) datasets.

Can Language Models Solve Graph Problems in Natural Language?

arthur-heng/nlgraph NeurIPS 2023

We then propose Build-a-Graph Prompting and Algorithmic Prompting, two instruction-based approaches to enhance LLMs in solving natural language graph problems.