Halu-NLP at SemEval-2024 Task 6: MetaCheckGPT - A Multi-task Hallucination Detection using LLM uncertainty and meta-models

Rahul Mehta, Andrew Hoblitzell, Jack O’keefe, Hyeju Jang, Vasudeva Varma


Abstract
Hallucinations in large language models(LLMs) have recently become a significantproblem. A recent effort in this directionis a shared task at Semeval 2024 Task 6,SHROOM, a Shared-task on Hallucinationsand Related Observable Overgeneration Mis-takes. This paper describes our winning so-lution ranked 1st and 2nd in the 2 sub-tasksof model agnostic and model aware tracks re-spectively. We propose a meta-regressor basedensemble of LLMs based on a random forestalgorithm that achieves the highest scores onthe leader board. We also experiment with var-ious transformer based models and black boxmethods like ChatGPT, Vectara, and others. Inaddition, we perform an error analysis com-paring ChatGPT against our best model whichshows the limitations of the former
Anthology ID:
2024.semeval-1.52
Volume:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
342–348
Language:
URL:
https://aclanthology.org/2024.semeval-1.52
DOI:
10.18653/v1/2024.semeval-1.52
Bibkey:
Cite (ACL):
Rahul Mehta, Andrew Hoblitzell, Jack O’keefe, Hyeju Jang, and Vasudeva Varma. 2024. Halu-NLP at SemEval-2024 Task 6: MetaCheckGPT - A Multi-task Hallucination Detection using LLM uncertainty and meta-models. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 342–348, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Halu-NLP at SemEval-2024 Task 6: MetaCheckGPT - A Multi-task Hallucination Detection using LLM uncertainty and meta-models (Mehta et al., SemEval 2024)
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PDF:
https://preview.aclanthology.org/landing_page/2024.semeval-1.52.pdf
Supplementary material:
 2024.semeval-1.52.SupplementaryMaterial.zip
Supplementary material:
 2024.semeval-1.52.SupplementaryMaterial.txt