Large language models (LLMs) have achieved significant advancements in natural language processing tasks, but they remain prone to generating hallucinations—outputs that are logically inconsistent or factually incorrect. While previous research has primarily focused on hallucinations in affirmative contexts, how negate...
Jaehyung Seo, Hyeonseok Moon, Heu-Jeoung Lim· ACM Transactions on Knowledg...· 0 citations
Knowledge distillation aims to transfer the factual knowledge of large language models to smaller models for efficient deployment. Yet a teacher may recall a relation in one direction while failing to generate the answer in the reverse direction. Distillation from its generated answers can therefore propagate this dire...
Jungseob Lee, Sugyeong Eo, Seongtae Hong et al.· 0 citations
Current cultural evaluations for large language models (LLMs) often reduce culture to single-turn factual recall via MCQs, failing to capture a common use case: users seeking practical help over multiple turns in culturally grounded scenarios. We introduce CultureConverse, a scalable, multilingual simulation and evalua...
Bryan Chen Zhengyu Tan, Wei-Hua Zheng, Thong T. Doan et al.· 0 citations
GLANCE is presented, the first one-pass block drafter that is lossless on an unmodified VLM target, and it breaks the cycle at both ends of a self-defeating cycle.
Jungseob Lee, Seongtae Hong, D. Lee et al.· 0 citations
DART is introduced, a training-free routing framework that samples two cheap no-think drafts, accepts direct answering when the drafts agree, and predicts a thinking budget from draft entropy when they disagree, and preserves or improves always-thinking accuracy in most settings while reducing thinking-token use.
Jungseob Lee, Seongtae Hong, Seungjun Lee et al.· arXiv.org· 1 citation
Because the signal spans a contiguous layer band, LayerMix aggregates it to match oracle-layer performance without oracle access, and characterize the geometry within the controlled paired-example paradigm.
The causes of modal divergence are probed, offering insights into fostering culturally robust MLLMs, and a Multilingual, Multimodal Alignment framework for Cultural grounding evaluation is proposed.
Weihua Zheng, Zhengyuan Liu, Tanmoy Chakraborty et al.· Annual Meeting of the Associ...· 0 citations
CultureConverse is introduced, a scalable, multilingual simulation and evaluation harness for culturally grounded assistant dialogue that covers 10 East and Southeast Asian regions, 58 subgroup identities, and 7 domains and performance gains from fine-tuning on 27,860 high-quality CultureConverse-DS samples improve in-...
Bryan Chen Zhengyu Tan, Weihua Zheng, Thong T. Doan et al.· 0 citations
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