9 papers
DINOv3 as a Frozen Encoder for CRPS-Oriented Probabilistic Rainfall Nowcasting
Luciano Araujo Dourado Filho, Almir Moreira da Silva Neto, Anthony Miyaguchi +3
This paper proposes a competitive and computationally efficient approach to probabilistic rainfall nowcasting. A video projector (V-JEPA Vision Transformer) associated to a lightwe…
DS@GT AnimalCLEF: Triplet Learning over ViT Manifolds with Nearest Neighbor Classification for Animal Re-identification
Anthony Miyaguchi, Chandrasekaran Maruthaiyannan, Charles R. Clark
This paper details the DS@GT team's entry for the AnimalCLEF 2025 re-identification challenge. Our key finding is that the effectiveness of post-hoc metric learning is highly conti…
DS@GT at eRisk 2025: From prompts to predictions, benchmarking early depression detection with conversational agent based assessments and temporal attention models
Anthony Miyaguchi, David Guecha, Yuwen Chiu +1
This Working Note summarizes the participation of the DS@GT team in two eRisk 2025 challenges. For the Pilot Task on conversational depression detection with large language-models…
DS@GT at Touché: Large Language Models for Retrieval-Augmented Debate
Anthony Miyaguchi, Conor Johnston, Aaryan Potdar
Large Language Models (LLMs) demonstrate strong conversational abilities. In this Working Paper, we study them in the context of debating in two ways: their ability to perform in a…
DS@GT at LongEval: Evaluating Temporal Performance in Web Search Systems and Topics with Two-Stage Retrieval
Anthony Miyaguchi, Imran Afrulbasha, Aleksandar Pramov
Information Retrieval (IR) models are often trained on static datasets, making them vulnerable to performance degradation as web content evolves. The DS@GT competition team partici…
Transfer Learning and Mixup for Fine-Grained Few-Shot Fungi Classification
Jason Kahei Tam, Murilo Gustineli, Anthony Miyaguchi
Accurate identification of fungi species presents a unique challenge in computer vision due to fine-grained inter-species variation and high intra-species variation. This paper pre…