6 papers
A Dual-Layered Evaluation of Geopolitical and Cultural Bias in LLMs
Sean Kim, Hyuhng Joon Kim
As large language models (LLMs) are increasingly deployed across diverse linguistic and cultural contexts, understanding their behavior in both factual and disputable scenarios is…
UniKnow: A Unified Framework for Reliable Language Model Behavior across Parametric and External Knowledge
Youna Kim, Hyuhng Joon Kim, Minjoon Choi +4
Language models often benefit from external knowledge beyond parametric knowledge. While this combination enhances performance, achieving reliable knowledge utilization remains cha…
When to Speak, When to Abstain: Contrastive Decoding with Abstention
Hyuhng Joon Kim, Youna Kim, Sang-goo Lee +1
Large Language Models (LLMs) demonstrate exceptional performance across diverse tasks by leveraging pre-trained (i.e., parametric) and external (i.e., contextual) knowledge. While…
Adaptive Contrastive Decoding in Retrieval-Augmented Generation for Handling Noisy Contexts
Youna Kim, Hyuhng Joon Kim, Cheonbok Park +6
When using large language models (LLMs) in knowledge-intensive tasks, such as open-domain question answering, external context can bridge the gap between external knowledge and the…
Aligning Language Models to Explicitly Handle Ambiguity
Hyuhng Joon Kim, Youna Kim, Cheonbok Park +5
In interactions between users and language model agents, user utterances frequently exhibit ellipsis (omission of words or phrases) or imprecision (lack of exactness) to prioritize…
Investigating the Influence of Prompt-Specific Shortcuts in AI Generated Text Detection
Choonghyun Park, Hyuhng Joon Kim, Junyeob Kim +6
AI Generated Text (AIGT) detectors are developed with texts from humans and LLMs of common tasks. Despite the diversity of plausible prompt choices, these datasets are generally co…