Cover Image

RAG-DIVE: A Dynamic Approach for Multi-Turn Dialogue Evaluation in Retrieval-Augmented Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Brehme, Lorenz, Dornauer, Benedikt, Böttcher, Jan-Henrik, Schmid, Klaus, Racasan, Mircea-Cristian, Breu, Ruth
Format:	Preprint
Published:	2026
Subjects:	Information Retrieval Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Retrieval-Augmented Generation in Industry: An Interview Study on Use Cases, Requirements, Challenges, and Evaluation
by: Brehme, Lorenz, et al.
Published: (2025)

Evaluating Multi-Hop Reasoning in RAG Systems: A Comparison of LLM-Based Retriever Evaluation Strategies
by: Brehme, Lorenz, et al.
Published: (2026)

Can LLMs Be Trusted for Evaluating RAG Systems? A Survey of Methods and Datasets
by: Brehme, Lorenz, et al.
Published: (2025)

RAGnaroX: A Secure, Local-Hosted ChatOps Assistant Using Small Language Models
by: Dornauer, Benedikt, et al.
Published: (2026)

How Industry Tackles Anomalies during Runtime: Approaches and Key Monitoring Parameters
by: Steidl, Monika, et al.
Published: (2024)

LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation
by: Li, Haitao, et al.
Published: (2025)

StratRAG: A Multi-Hop Retrieval Evaluation Dataset for Retrieval-Augmented Generation Systems
by: Patodiya, Aryan
Published: (2026)

DA-RAG: Dynamic Attributed Community Search for Retrieval-Augmented Generation
by: Zeng, Xingyuan, et al.
Published: (2026)

Prospects of Retrieval Augmented Generation (RAG) for Academic Library Search and Retrieval
by: Bevara, Ravi, et al.
Published: (2025)

QDA-SQL: Questions Enhanced Dialogue Augmentation for Multi-Turn Text-to-SQL
by: Sun, Yinggang, et al.
Published: (2024)

Evaluating Hybrid Retrieval Augmented Generation using Dynamic Test Sets: LiveRAG Challenge
by: Fensore, Chase, et al.
Published: (2025)

H-RAG at SemEval-2026 Task 8: Hierarchical Parent-Child Retrieval for Multi-Turn RAG Conversations
by: Elchafei, Passant, et al.
Published: (2026)

MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation
by: Chang, Chia-Yuan, et al.
Published: (2024)

OmniBench-RAG: A Multi-Domain Evaluation Platform for Retrieval-Augmented Generation Tools
by: Liang, Jiaxuan, et al.
Published: (2025)

LARA: Linguistic-Adaptive Retrieval-Augmentation for Multi-Turn Intent Classification
by: Liu, Junhua, et al.
Published: (2024)

Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks
by: Su, Jinyan, et al.
Published: (2024)

Overview of the TREC 2025 Retrieval Augmented Generation (RAG) Track
by: Upadhyay, Shivani, et al.
Published: (2026)

HypRAG: Hyperbolic Dense Retrieval for Retrieval Augmented Generation
by: Madhu, Hiren, et al.
Published: (2026)

Loops On Retrieval Augmented Generation (LoRAG)
by: Thakur, Ayush, et al.
Published: (2024)

MG$^2$-RAG: Multi-Granularity Graph for Multimodal Retrieval-Augmented Generation
by: Dai, Sijun, et al.
Published: (2026)

HopRAG: Multi-Hop Reasoning for Logic-Aware Retrieval-Augmented Generation
by: Liu, Hao, et al.
Published: (2025)

HASH-RAG: Bridging Deep Hashing with Retriever for Efficient, Fine Retrieval and Augmented Generation
by: Guo, Jinyu, et al.
Published: (2025)

DynaRAG: Bridging Static and Dynamic Knowledge in Retrieval-Augmented Generation
by: Liang, Penghao, et al.
Published: (2026)

Optimizing and Evaluating Enterprise Retrieval-Augmented Generation (RAG): A Content Design Perspective
by: Packowski, Sarah, et al.
Published: (2024)

DomainRAG: A Chinese Benchmark for Evaluating Domain-specific Retrieval-Augmented Generation
by: Wang, Shuting, et al.
Published: (2024)

FeB4RAG: Evaluating Federated Search in the Context of Retrieval Augmented Generation
by: Wang, Shuai, et al.
Published: (2024)

DyG-RAG: Dynamic Graph Retrieval-Augmented Generation with Event-Centric Reasoning
by: Sun, Qingyun, et al.
Published: (2025)

Doctor-RAG: Failure-Aware Repair for Agentic Retrieval-Augmented Generation
by: Jiao, Shuguang, et al.
Published: (2026)

UniRAG: Universal Retrieval Augmentation for Large Vision Language Models
by: Sharifymoghaddam, Sahel, et al.
Published: (2024)

Mindful-RAG: A Study of Points of Failure in Retrieval Augmented Generation
by: Agrawal, Garima, et al.
Published: (2024)

LightRAG: Simple and Fast Retrieval-Augmented Generation
by: Guo, Zirui, et al.
Published: (2024)

TrustRAG: An Information Assistant with Retrieval Augmented Generation
by: Fan, Yixing, et al.
Published: (2025)

LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searchers
by: Zhang, Zhuocheng, et al.
Published: (2025)

MultiRAG: A Knowledge-guided Framework for Mitigating Hallucination in Multi-source Retrieval Augmented Generation
by: Wu, Wenlong, et al.
Published: (2025)

PersonaRAG: Enhancing Retrieval-Augmented Generation Systems with User-Centric Agents
by: Zerhoudi, Saber, et al.
Published: (2024)

UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generation
by: Chen, Yuxuan, et al.
Published: (2025)

Retrieval-Augmented Generation with Graphs (GraphRAG)
by: Han, Haoyu, et al.
Published: (2024)

AtomicRAG: Atom-Entity Graphs for Retrieval-Augmented Generation
by: Hou, Yanning, et al.
Published: (2026)

CausalRAG: Integrating Causal Graphs into Retrieval-Augmented Generation
by: Wang, Nengbo, et al.
Published: (2025)

RAG-Fusion: a New Take on Retrieval-Augmented Generation
by: Rackauckas, Zackary
Published: (2024)