4 papers
Towards Principled Design of Mixture-of-Experts Language Models under Memory and Inference Constraints
Seng Pei Liew, Kenta Shinzato, Yuyang Dong
Modern Mixture-of-Experts (MoE) language models are designed based on total parameters (memory footprint) and active parameters (inference cost). However, we find these two factors…
Adaptive Layer Selection for Layer-Wise Token Pruning in LLM Inference
Rei Taniguchi, Yuyang Dong, Makoto Onizuka +1
Due to the prevalence of large language models (LLMs), key-value (KV) cache reduction for LLM inference has received remarkable attention. Among numerous works that have been propo…
SCAN: Semantic Document Layout Analysis for Textual and Visual Retrieval-Augmented Generation
Nobuhiro Ueda, Yuyang Dong, Krisztián Boros +3
With the increasing adoption of Large Language Models (LLMs) and Vision-Language Models (VLMs), rich document analysis technologies for applications like Retrieval-Augmented Genera…
Table Enrichment System for Machine Learning
Yuyang Dong, Masafumi Oyamada
Data scientists are constantly facing the problem of how to improve prediction accuracy with insufficient tabular data. We propose a table enrichment system that enriches a query t…