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Multi-hop Question Answering

2개 벤치마크 · 논문 323편 · 이 태스크의 논문 보기 →

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Papers

LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation

2026-09-09 · Daniel Alejandro Coll Tejeda, Pedro García López, Daniel Barcelona-Pons arxiv

Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversized contexts that reduce generation efficiency. We present LiteRAG, a g…

Multi-hop Question Answering

Hi-Q: Hierarchical Evidence-guided Query Refinement for Multi-Hop Question Answering

2026-08-31 · Jueun Kim, Sungho Park, Wook-Shin Han arxiv

A central bottleneck in multi-hop Question Answering (QA) is that the granularity at which a question is expressed often differs from the granularity at which corpus evidence is retrievable. Existing methods address this…

Multi-hop Question Answering

BrailleBench: Investigating Multi-Criteria Braille Comprehension in Large Language Models

2026-08-27 · Jinghan Zhang, Fengran Mo, Zhiyu Chen, Xiaoyan Han 외 arxiv

Although Large language models (LLMs) mediate access to knowledge and computational assistance, their capabilities should benefit vulnerable groups in the same way. However, it is unclear whether existing AI systems are …

Multi-hop Question Answering

LivingRAG: Augmenting Graph RAG with Experience

2026-08-26 · Yuzhuo Cui, Zongye Zhang, Qingjie Liu arxiv

Graph-based RAG improves multi-hop question answering by organizing evidence as a knowledge graph. However, most existing RAG systems process each query in isolation and discard useful reasoning from the LLM's response a…

Multi-hop Question AnsweringAnswer Generation

Better Decomposition, Free Aggregation: A Synthesizer-Folding Framework for Multilingual Multi-Hop Question Answering

2026-08-13 · Yilin Wang, Yuchun Fan, Weidong Bao, Zili Wei 외 arxiv

Multilingual retrieval-augmented generation (mRAG) equips large language models with access to globally distributed external knowledge for complex multilingual question answering. Recent approaches either translate retri…

Multi-hop Question Answering

CoinRAG: Contextualized Information Nugget KV Cache Reuse for Long-Context RAG

2026-08-07 · Gyuwan Kim, Cheoneum Park, Tao Yang hf

Recent optimization studies on Retrieval-Augmented Generation (RAG) have exploited chunk-level KV cache reuse to avoid processing long retrieved contexts for higher efficiency, while significant information redundancy an…

Multi-hop Question Answering

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