1 citations · 1 across the 2 of their papers we have counts for
4 papers
KSAFE-MM: A Multimodal Safety Benchmark via Localized Contextualization for Korean Cultural Risks
Yongwoo Kim, Sojung An, Yunjin Park +8
Multimodal Large Language Models (MLLMs) exacerbate safety risks by introducing vulnerabilities across multiple modalities, such as language and vision. Current MLLM safety evaluat…
Scaling Multi-Node Mixture-of-Experts Inference Using Expert Activation Patterns
Abhimanyu Bambhaniya, Geonhwa Jeong, Jason Park +6
Most recent state-of-the-art (SOTA) large language models (LLMs) use Mixture-of-Experts (MoE) architectures to scale model capacity without proportional per-token compute, enabling…
Multilingual Machine Translation with Open Large Language Models at Practical Scale: An Empirical Study
Menglong Cui, Pengzhi Gao, Wei Liu +2
Large language models (LLMs) have shown continuously improving multilingual capabilities, and even small-scale open-source models have demonstrated rapid performance enhancement. I…
SUTRA: Scalable Multilingual Language Model Architecture
Abhijit Bendale, Michael Sapienza, Steven Ripplinger +3
In this paper, we introduce SUTRA, multilingual Large Language Model architecture capable of understanding, reasoning, and generating text in over 50 languages. SUTRA's design uniq…