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Multi-hop Question Answering

Papers

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Showing 51–100 of 202 papers

TitleStatusHype
Enhancing Multi-modal and Multi-hop Question Answering via Structured Knowledge and Unified Retrieval-GenerationCode1
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question AnsweringCode1
MQuAKE: Assessing Knowledge Editing in Language Models via Multi-Hop QuestionsCode1
KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge TracingCode1
CompAct: Compressing Retrieved Documents Actively for Question AnsweringCode1
Multi-Step Reasoning Over Unstructured Text with Beam Dense RetrievalCode1
[Re] Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base EmbeddingsCode1
Grounded Multi-Hop VideoQA in Long-Form Egocentric VideosCode1
Reasoning over Public and Private Data in Retrieval-Based SystemsCode1
Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QACode1
Teaching Humans When To Defer to a Classifier via ExemplarsCode1
Furthest Reasoning with Plan Assessment: Stable Reasoning Path with Retrieval-Augmented Large Language Models—0
FSM: A Finite State Machine Based Zero-Shot Prompting Paradigm for Multi-Hop Question Answering—0
A Training-free LLM Framework with Interaction between Contextually Related Subtasks in Solving Complex Tasks—0
From Easy to Hard: Two-stage Selector and Reader for Multi-hop Question Answering—0
A Graph-Retrieval-Augmented Generation Framework Enhances Decision-Making in the Circular Economy—0
LLM-Based Multi-Hop Question Answering with Knowledge Graph Integration in Evolving Environments—0
Fine-tuning Multi-hop Question Answering with Hierarchical Graph Network—0
Few-shot Multi-hop Question Answering over Knowledge Base—0
Multi-hop Question Answering—0
Coarse-grained decomposition and fine-grained interaction for multi-hop question answering—0
Exploiting Hybrid Semantics of Relation Paths for Multi-hop Question Answering Over Knowledge Graphs—0
An Analysis of Decoding Methods for LLM-based Agents for Faithful Multi-Hop Question Answering—0
LightPAL: Lightweight Passage Retrieval for Open Domain Multi-Document Summarization—0
Chain-of-Retrieval Augmented Generation—0
EvolveSearch: An Iterative Self-Evolving Search Agent—0
A STEP towards Interpretable Multi-Hop Reasoning:Bridge Phrase Identification and Query Expansion—0
Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy—0
Read and Think: An Efficient Step-wise Multimodal Language Model for Document Understanding and Reasoning—0
Ask to Understand: Question Generation for Multi-hop Question Answering—0
Iterative Hierarchical Attention for Answering Complex Questions over Long Documents—0
Few-Shot Data Synthesis for Open Domain Multi-Hop Question Answering—0
K-Edit: Language Model Editing with Contextual Knowledge Awareness—0
Dynamic Strategy Planning for Efficient Question Answering with Large Language Models—0
Calibrating Trust of Multi-Hop Question Answering Systems with Decompositional Probes—0
Leveraging Logical Rules in Knowledge Editing: A Cherry on the Top—0
Is Graph Structure Necessary for Multi-hop Question Answering?—0
Interpretable AMR-Based Question Decomposition for Multi-hop Question Answering—0
Inference Scaled GraphRAG: Improving Multi Hop Question Answering on Knowledge Graphs—0
Breadth First Reasoning Graph for Multi-hop Question Answering—0
Drilling Down into the Discourse Structure with LLMs for Long Document Question Answering—0
A Simple Yet Strong Pipeline for HotpotQA—0
If You Want to Go Far Go Together: Unsupervised Joint Candidate Evidence Retrieval for Multi-hop Question Answering—0
Biomedical Multi-hop Question Answering Using Knowledge Graph Embeddings and Language Models—0
Large Language Models as a Tool for Mining Object Knowledge—0
Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games—0
KiRAG: Knowledge-Driven Iterative Retriever for Enhancing Retrieval-Augmented Generation—0
Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks—0
Do Transformers Dream of Inference, or Can Pretrained Generative Models Learn Implicit Inferential Rules?—0
Hybrid Graphs for Table-and-Text based Question Answering using LLMs—0
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All datasetsConcurrentQAMuSiQue-Ans

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Multi-hop Dense Passage Retriever (MDR)Answer F156.5—Unverified
#ModelMetricClaimedVerifiedStatus
1Beam RetrievalAn69.2—Unverified