22 citations · 24 across the 8 of their papers we have counts for
5 papers · 1 filter
Multi-stage Prompt Refinement for Mitigating Hallucinations in Large Language Models
Jung-Woo Shim, Yeong-Joon Ju, Ji-Hoon Park +1
Recent advancements in large language models (LLMs) have shown strong performance in natural language understanding and generation tasks. However, LLMs continue to encounter challe…
CPR: Mitigating Large Language Model Hallucinations with Curative Prompt Refinement
Jung-Woo Shim, Yeong-Joon Ju, Ji-Hoon Park +1
Recent advancements in large language models (LLMs) highlight their fluency in generating responses to diverse prompts. However, these models sometimes generate plausible yet incor…
KiC: Keyword-inspired Cascade for Cost-Efficient Text Generation with LLMs
Woo-Chan Kim, Ji-Hoon Park, Seong-Whan Lee
Large language models (LLMs) have demonstrated state-of-the-art performance across a wide range of natural language processing tasks. However, high-performing models are typically…
GRAIL: Gradient-Based Adaptive Unlearning for Privacy and Copyright in LLMs
Kun-Woo Kim, Ji-Hoon Park, Ju-Min Han +1
Large Language Models (LLMs) trained on extensive datasets often learn sensitive information, which raises significant social and legal concerns under principles such as the "Right…
SUGAR: Leveraging Contextual Confidence for Smarter Retrieval
Hanna Zubkova, Ji-Hoon Park, Seong-Whan Lee
Bearing in mind the limited parametric knowledge of Large Language Models (LLMs), retrieval-augmented generation (RAG) which supplies them with the relevant external knowledge has…