Cover Image

Reducing Hallucinations in Language Model-based SPARQL Query Generation Using Post-Generation Memory Retrieval

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Sharma, Aditya, Pal, Christopher J., Zouaq, Amal
Format:	Preprint
Published:	2025
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DeSQ: Decomposition-based SPARQL Query Generation
by: Diallo, Papa Abdou Karim Karou, et al.
Published: (2026)

FRASE: Structured Representations for Generalizable SPARQL Query Generation
by: Diallo, Papa Abdou Karim Karou, et al.
Published: (2025)

A Comprehensive Evaluation of Neural SPARQL Query Generation from Natural Language Questions
by: Diallo, Papa Abdou Karim Karou, et al.
Published: (2023)

GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models
by: Sharma, Aditya, et al.
Published: (2024)

Enhancing Frame Detection with Retrieval Augmented Generation
by: Diallo, Papa Abdou Karim Karou, et al.
Published: (2025)

Ontology-Constrained Generation of Domain-Specific Clinical Summaries
by: Mehenni, Gaya, et al.
Published: (2024)

What is the Best Process Model Representation? A Comparative Analysis for Process Modeling with Large Language Models
by: Brissard, Alexis, et al.
Published: (2025)

LLMs Can't Play Hangman: On the Necessity of a Private Working Memory for Language Agents
by: Baldelli, Davide, et al.
Published: (2026)

SPARQL-LLM: Real-Time SPARQL Query Generation from Natural Language Questions
by: Smeros, Panayiotis, et al.
Published: (2025)

Reducing Hallucinations of Medical Multimodal Large Language Models with Visual Retrieval-Augmented Generation
by: Chu, Yun-Wei, et al.
Published: (2025)

Probabilistic Calibration Is a Trainable Capability in Language Models
by: Baldelli, Davide, et al.
Published: (2026)

MedHal: An Evaluation Dataset for Medical Hallucination Detection
by: Mehenni, Gaya, et al.
Published: (2025)

Leveraging the Domain Adaptation of Retrieval Augmented Generation Models for Question Answering and Reducing Hallucination
by: Rakin, Salman, et al.
Published: (2024)

Conversational Lexicography: Querying Lexicographic Data on Knowledge Graphs with SPARQL through Natural Language
by: Sennrich, Kilian, et al.
Published: (2025)

SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection
by: Gashkov, Aleksandr, et al.
Published: (2025)

Automating SPARQL Query Translations between DBpedia and Wikidata
by: Bartels, Malte Christian, et al.
Published: (2025)

Finetune-RAG: Fine-Tuning Language Models to Resist Hallucination in Retrieval-Augmented Generation
by: Lee, Zhan Peng, et al.
Published: (2025)

Micro-Macro Retrieval: Reducing Long-Form Hallucination in Large Language Models
by: Feng, Yujie, et al.
Published: (2026)

GRASP: Generic Reasoning And SPARQL Generation across Knowledge Graphs
by: Walter, Sebastian, et al.
Published: (2025)

Integrating Multi-Head Convolutional Encoders with Cross-Attention for Improved SPARQL Query Translation
by: Chen, Yi-Hui, et al.
Published: (2024)

Active Layer-Contrastive Decoding Reduces Hallucination in Large Language Model Generation
by: Zhang, Hongxiang, et al.
Published: (2025)

Context-aware Decoding Reduces Hallucination in Query-focused Summarization
by: Xu, Zhichao
Published: (2023)

GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrieval
by: Liu, Lingyuan, et al.
Published: (2025)

Improving Tool Retrieval by Leveraging Large Language Models for Query Generation
by: Kachuee, Mohammad, et al.
Published: (2024)

Assessing SPARQL capabilities of Large Language Models
by: Meyer, Lars-Peter, et al.
Published: (2024)

Enhancing Retrieval Processes for Language Generation with Augmented Queries
by: Ghali, Julien Pierre Edmond, et al.
Published: (2024)

Bi'an: A Bilingual Benchmark and Model for Hallucination Detection in Retrieval-Augmented Generation
by: Jiang, Zhouyu, et al.
Published: (2025)

Evaluating Retrieval Augmented Generative Models for Document Queries in Transportation Safety
by: Melton, Chad, et al.
Published: (2025)

Stable-RAG: Mitigating Retrieval-Permutation-Induced Hallucinations in Retrieval-Augmented Generation
by: Zhang, Qianchi, et al.
Published: (2026)

JointCQ: Improving Factual Hallucination Detection with Joint Claim and Query Generation
by: Xu, Fan, et al.
Published: (2025)

Retrieving Time-Series Differences Using Natural Language Queries
by: Dohi, Kota, et al.
Published: (2025)

Rowen: Adaptive Retrieval-Augmented Generation for Hallucination Mitigation in LLMs
by: Ding, Hanxing, et al.
Published: (2024)

ImpRAG: Retrieval-Augmented Generation with Implicit Queries
by: Zhang, Wenzheng, et al.
Published: (2025)

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level
by: Perçin, Sezen, et al.
Published: (2025)

Assessing the Answerability of Queries in Retrieval-Augmented Code Generation
by: Kim, Geonmin, et al.
Published: (2024)

Stronger Baselines for Retrieval-Augmented Generation with Long-Context Language Models
by: Laitenberger, Alex, et al.
Published: (2025)

BlendFilter: Advancing Retrieval-Augmented Large Language Models via Query Generation Blending and Knowledge Filtering
by: Wang, Haoyu, et al.
Published: (2024)

Generative Language Models with Retrieval Augmented Generation for Automated Short Answer Scoring
by: Wang, Zifan, et al.
Published: (2024)

InterpDetect: Interpretable Signals for Detecting Hallucinations in Retrieval-Augmented Generation
by: Tan, Likun, et al.
Published: (2025)

Detecting Hallucination and Coverage Errors in Retrieval Augmented Generation for Controversial Topics
by: Chang, Tyler A., et al.
Published: (2024)