awesome-hallucination-detection
github.com/edinburghnlp/awesome-hallucination-detection ↗List of papers on hallucination detection in LLMs.
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Papers and SummariesOverviews, Surveys, and Shared TasksMeasuring Hallucinations in LLMsOpen Source Models for Measuring Hallucinations
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me parammute: suppressing knowledge-critical ffns for faithful retrieval-augmented generation resources from awesome-hallucination-detection"
Installation instructions →What's inside
Open Source Models for Measuring Hallucinations
Measuring Hallucinations in LLMs
- AnyScale - Llama 2 is about as factually accurate as GPT-4 for summaries and is 30X cheaper
Llama 2 is about as factually accurate as GPT-4 for summaries and is 30X cheaper
- Arthur.ai - Hallucination Experiment
Hallucination Experiment
- LongTracer
Open-source RAG hallucination detection SDK. Verifies LLM claims against source documents using hybrid STS + NLI, with pluggable backends and LangChain/LlamaIndex/Haystack adapters.
- TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
- UQLM: Uncertainty Quantification for Language Models
- Vectara - Cut the Bull…. Detecting Hallucinations in Large Language Models
Cut the Bull…. Detecting Hallucinations in Large Language Models
Overviews, Surveys, and Shared Tasks
- A Survey of Hallucination in Large Foundation Models
- A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions
- here
- How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances
- llm-hallucination-survey
- LLM Powered Autonomous Agents
Papers and Summaries
- CodeParamMute: Suppressing Knowledge-Critical FFNs for Faithful Retrieval-Augmented Generation
- Enoki-EncoderEnoki: Efficient Multi-Level Hallucination Detection
- https://github.com/shichengf/CorVerVerifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering
- https://github.com/ZhishanQ/QuCo-RAGQuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation
- open-source Reexpress MCP serverSimilarity-Distance-Magnitude Universal Verification
- SiteREFUTE: Scientific Critique & Epistemic Calibration Benchmark
Showing a sample of 30 resources. View the full list on GitHub →