awesome-hallucination-detection
List of papers on hallucination detection in LLMs.
GraphCanon updated Oct 11, 2026 · GitHub synced Oct 11, 2026
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Decision brief
awesome-hallucination-detection provides a curated list of research papers focused on techniques to detect and mitigate hallucinations in large language models (LLMs), including process supervision methods for factual QA
Good fit when
- - When focusing on specific methodologies like Corpus Verify (CorVer) from the paper 'Verifiable Rewards Beyond Math and Code' which utilizes lightweight, process-based rewards to mitigate hallucinat
- - For scientific critique tasks requiring calibrated and evidence-grounded judgment as per REFUTE benchmark
Avoid when
- When immediate implementation or code is needed rather than research papers, this repository is not suitable as it only curates information on methodologies and benchmarks.
- - If your focus is on general LLM training techniques without a specific emphasis on hallucination detection or calibration
Observed Jul 11, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (2d since push)
- As of Oct 11, 2026
- Provenance
- Not a fork · Organization account
- As of Oct 11, 2026
- Security (OSV)
- No lockfile
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/EdinburghNLP/awesome-hallucination-detectionSimilar tools
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Evidence and technical details
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Overview
Repository containing a curated list of research papers focused on methods to detect and mitigate hallucinations generated by large language models (LLMs), including specific techniques like process supervision for factual QA tasks and calibration benchmarks for scientific critiques.
Capability facts
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README
awesome hallucination detection Papers and Summaries Enoki: Efficient Multi Level Hallucination Detection Metrics: AUROC, AUPRC, Span Coverage F1, FLOPs. Datasets: EnokiQA, HalluEntity, MuSHROOM, RAGTruth, PsiloQA, FactCheckBench, ANAH. Comments: Introduces Enoki , an Open Inform...
For agents
This page has a .md twin and JSON over the API.