https://www.slickrock.dev/roles/hallucination-detection-specialist
Hire a Hallucination Detection Specialist or Fractional Team? | Slickrock.dev
Deep semantic analysis on hiring a Hallucination Detection Specialist. Learn the exact tech stack (Jupyter, Pandas), salary data ($150K - $250K), and why...
hallucination detectionhirespecialistfractionalteam
https://cris.openu.ac.il/en/publications/interrogatellm-zero-resource-hallucination-detection-in-llm-gener/
InterrogateLLM: Zero-Resource Hallucination Detection in LLM-Generated Answers - Open University of...
hallucination detectionopen universityzeroresourcellm
https://www.sciencestack.ai/paper/2511.07318
When Bias Pretends to Be Truth: How Spurious Correlations Undermine Hallucination Detection in LLMs...
Nov 10, 2025 - This work investigates spurious correlations as a primary driver of hallucinations in large language models, showing that surface-level statistical shortcuts ca
to bespurious correlationshallucination detectionbiaspretends
https://www.richardewing.io/vault/curriculum/tracks/agent-governance/21-4
21-4: Hallucination Detection & Verification Economics | Curriculum | Richard Ewing | Richard Ewing
hallucination detectioneconomics curriculumverificationrichardewing
https://www.getmaxim.ai/blog/llm-hallucination-detection/
Advanced Hallucination Detection in LLMs: Meet FAVA
Apr 6, 2025 - Explore the innovative FAVA model for detecting fine-grained hallucinations in LLMs. Learn how it outperforms GPT-4 and Llama2, enhancing factual accuracy in...
hallucination detectionadvancedllmsmeetfava
https://arxiv.org/abs/2601.00269
[2601.00269] FaithSCAN: Model-Driven Single-Pass Hallucination Detection for Faithful Visual...
Abstract page for arXiv paper 2601.00269: FaithSCAN: Model-Driven Single-Pass Hallucination Detection for Faithful Visual Question Answering
single passhallucination detectionmodeldrivenfaithful
https://lrec.elra.info/lrec2026-main-552
TCMPHal: A Large-scale Dataset for Hallucination Detection in Traditional Chinese Medicine Pharmacy...
May 1, 2026 - The rapid proliferation of large language models (LLMs) in medicine highlights their potential to revolutionize research in Traditional Chinese Medicine (TCM).
traditional chinese medicinelarge scalehallucination detectiondatasetpharmacy
https://docs.futureagi.com/docs/evaluation/builtin/caption-hallucination
Caption Hallucination Detection Metric for Images | Future AGI Docs
Evaluates whether an image caption contains fabricated details not visible in the image, flagging invented content not grounded in the visual input.
hallucination detectioncaptionmetricimagesfuture
https://liner.com/review/machine-translation-hallucination-detection-for-low-and-high-resource-languages
Machine Translation Hallucination Detection for Low and High Resource Languages using Large...
Regarding this EMNLP 2024 paper, this review summarizes LLM and embedding-based methods for machine translation hallucination detection across HRLs and LRL...
machine translationhallucination detectionlowhighresource
https://tldr.takara.ai/p/2509.17671
Turk-LettuceDetect: A Hallucination Detection Models for Turkish RAG Applications | Takara TLDR
The widespread adoption of Large Language Models (LLMs) has been hindered by their tendency to hallucinate, generating plausible but factually incorrect info...
hallucination detectionturkmodelsragapplications
https://csitcp.com/abstract/14/147csit03
In-Context Learning for Scalable and Online Hallucination Detection in RAGS
Ensuring fidelity to source documents is crucial for the responsible use of Large Language Models (LLMs) in Retrieval Augmented Generation (RAG) systems. We...
in contextlearning forhallucination detectionscalableonline
https://www.technavio.com/report/ai-hallucination-detection-and-mitigation-tools-market-industry-analysis
AI Hallucination Detection And Mitigation Tools Market Growth Analysis - Size and Forecast...
The AI Hallucination Detection And Mitigation Tools Market size is expected to grow by USD 4353.4 million from 2026-2030 expanding at a CAGR of 32.9% during...
ai hallucination detectionmarket growthmitigationtoolsanalysis