Domestic Conferences (Some)
-
A Multimodal Dataset for Socially Compliant Navigation in Urban Environments,
Zhuonan Liu, Zishuo Wang, Xinyu Zhang, Tomohito Kawabata, Ling Xiao,
信学技報 , vol. 125, no. 356, IE2025-63, pp. 49-54, 2026年2月. [IE賞]
-
Enhancing the Spatial Awareness of Large Language Models in Path Planning,
Ling Xiao and Toshihiko Yamasaki,
第30回 知能メカトロニクスワークショップ 2025 (iMec), 2025.
-
Few-shot推論によるアノテータに個人適応可能なビデオ要約,
杉原朋弥, 増田俊太郎, 肖玲, 山崎俊彦,
MIRU 2025, IS3-102, 2025.
-
時空間情報を統合したプロンプトを用いた保育施設映像の行動認識,
渡辺健太, 増田俊太郎, 肖玲, 山崎俊彦,
MIRU 2025, IS2-081, 2025.
-
LLM-Advisor: Leveraging LLMs as Advisors for Cost-efficient Path Planning Across Diverse Terrains,
Ling Xiao and Toshihiko Yamasaki,
MIRU 2025, IS2-185, 2025.
-
TourMLLM: 検索拡張大規模観光マルチモーダルモデル,
山西博雅, Ling Xiao, 山崎俊彦,
MIRU 2025, IS2-119, 2025.
-
基盤モデルによる視覚的評価を用いた動画広告の効果分析,
田邉克晃, 増田俊太郎, 劉岳松, 丹治直人, 勢〆弘幸, 肖玲, 山崎俊彦,
MIRU 2025, OS2C-06, 2025. [Oral]
-
Content-Aware Layout Generation with Large Language Models,
Chen FU, Naoto Tanji, Gakumatsu Ryu, Hiroyuki SESHIME, Shengzhou Yi, Ling Xiao, and Toshihiko Yamasaki,
MIRU 2025, IS1-102, 2025.
-
タスク適応的検索拡張学習に基づく観光特化大規模マルチモーダルモデル,
山西博雅, 肖 玲, 山崎俊彦,
信学技報, 画像工学研究会 (IE), IE2024-61.
-
Explainable Image Aesthetic Assessment Leveraging Vision-Language Models,
S. Viriyavisuthisakul, S.n Yoshida, K. Shiohara, L. Xiao, and T. Yamasaki,
信学技報, 画像工学研究会 (IE), IE2024-66.
-
Momentum Knowledge Distillation for Enhanced Online Continual Learning,
N. Michel, M. Wang, L. Xiao, and T. Yamasaki,
信学技報, 画像工学研究会 (IE), IE2024-57.
-
Llava-Planner: Enhancing Spatial Awareness of LLaVA for Cost-Effective Path Planning,
L. Xiao, H. Yamanishi, and T. Yamasaki,
信学技報, 画像工学研究会 (IE), IE2024-44.
-
LLM-Advisor: A LLM Benchmark for Cost-effective Path Planning,
L. Xiao and T. Yamasaki,
PCSJ/IMPS 2024, P-2-05, 2024.
-
マルチモーダル観光レビュー生成データセットと大規模レビュー生成モデルの作成,
H. Yamanishi, L. Xiao, and T. Yamasaki,
PCSJ/IMPS 2024, P-4-18, 2024.
-
Boosting Fine-grained Fashion Retrieval with Relational Knowledge Distillation,
L. Xiao and T. Yamasaki,
信学技報, 画像工学研究会 (IE), vol. 124, no. 60, IE2024-17, pp. 90–94, 2024.
[Code]
-
Language-Guided Self-Supervised Video Summarization Using Text Semantic Matching,
T. Sugihara, S. Masuda, L. Xiao, and T. Yamasaki,
MIRU 2024. [Oral]
-
大規模マルチモーダルモデルを用いた広告画像の評価・改善,
砂田達巳, 塩原楓, 劉岳松, 丹治直人, 勢〆弘幸, 肖玲, 山崎俊彦,
MIRU 2024. [Oral]
-
Multi-hop Question Answering over Incomplete Knowledge Graphs by Edge and Meaning Extensions,
X.T. Ye, L. Xiao, C. Zhang, and T. Yamasaki,
MIRU 2024.
-
Constrianed Advertisement Layout Generation based on Graph Neural Networks,
C. Fu, Y. Liu, N. Tanji, H. Seshime, L. Xiao, and T. Yamasaki,
MIRU 2024.
-
Improving Adversarial Robustness in Continual Learning,
K. Mukai, S. Kumano, N. Michel, L. Xiao, and T. Yamasaki,
信学技報, 画像工学研究会 (IE), vol. 123, no. 381, IE2023-37, pp. 13–18, 2024. [IE賞]
-
大規模言語モデルを活用した自己教師あり学習によるビデオ要約,
杉原朋弥, 増田俊太郎, 肖玲, 山崎俊彦,
IPSJ, 7T-06, pp. 2-653–2-654, 2024.
-
Advertisement Layout Generation based on Graph Neural Network,
C. Fu, Y. Liu, N. Tanji, H. Seshime, L. Xiao, and T. Yamasaki,
信学技報, 画像工学研究会 (IE), vol. 123, no. 381, IE2023-51, pp. 88–89, 2024.
-
Improved Fine-grained Fashion Retrieval with Contrastive Learning,
L. Xiao, X. F. Zhang, and T. Yamasaki,
MIRU 2023, IS3-55, 2023.
-
Video Summarization Based on Masked Autoencoder,
M. L. A. FOK, L. Xiao, and T. Yamasaki,
MIRU 2023, IS1-84, 2023.
-
Improving Fashion Compatibility Prediction with Color Distortion Prediction,
L. Xiao and T. Yamasaki,
信学技報, 画像工学研究会 (IE), vol. 122, no. 385, IE2022-61, pp. 17–18, 2023.
-
Multi-Level Attention Network for Fine-Grained Fashion Retrieval,
L. Xiao and T. Yamasaki,
信学技報, MVE, vol. 122, no. 440, MVE2022-90, pp. 198–199, 2023.
-
SAT: Self-adaptive Training for Fashion Compatibility Prediction,
L. Xiao and T. Yamasaki,
MIRU 2022.
-
Spatial Attention Based Fashion Compatibility Prediction,
L. Xiao and T. Yamasaki,
PCSJ/IMPS 2021, P-3-17, pp. 135–136, 2021.