GPT-3’s performance. The paper outlines previous
works on LLM reliability, highlighting the novelty
of this study’s comprehensive analysis and focus on
effective prompting strategies. Drawing inspiration
from ML safety surveys, the reliability framework
aligns with identified risks in existing conceptual
frameworks. Lastly, the systematic exploration of
GPT-3’s reliability has been summarized, which
introduces practical prompting strategies, and em-
phasizes the study’s contribution to insights into
LLMs and practical recommendations for GPT-3
users.
ChatProtect: (Mündler et al., 2023) focuses on
an important type of hallucination called self-
contradiction, which occurs when an LLM gener-
ates two logically inconsistent sentences given the
same context. They propose a three-step pipeline
for reasoning about self-contradictions.
Impor-
tantly, the approach is built upon prompting strate-
gies, making it applicable to black-box LLMs with-
out requiring external grounded knowledge. They
AComprehensiveSurveyofHallucinationMitigationTechniquesinLarge LanguageModels