works on

From the 1 of 13 linked papers with an AI index.

activity
20242026
collaborators

13 papers

cs.IR2026

DS@GT ARC at Touché: Large Language Models for Retrieval-Augmented Debate

Anthony Miyaguchi, Conor Johnston

We extend the DS@GT ARC working-note submission to the Touché 2025 Retrieval-Augmented Debate task. The task has two subtasks: generating the next utterance in a simulated debate,…

cs.CV2026

DS@GT ARC at AnimalCLEF 2026: Species-Aware Graph Construction for Multi-Species Animal Re-Identification

Evan Sinclair Smith, Anthony Miyaguchi, Snigdha Palamari +1

Automated individual animal re-identification is essential for large-scale biodiversity monitoring; however, field imagery complicates separating identity cues from nuisance variat…

cs.SD2026

Can Tokens Compete? Token Representations against Supervised CNN Backbones for BirdCLEF+ 2026

Anthony Miyaguchi, Murilo Gustineli, Adrian Cheung

The paper presents the DS@GT ARC team's approach to the BirdCLEF+ 2026 competition, building a supervised baseline for multi‑label bird vocalization detection and evaluating whethe…

cs.IR2026

DS@GT at TREC TOT 2025: Bridging Vague Recollection with Fusion Retrieval and Learned Reranking

Wenxin Zhou, Ritesh Mehta, Anthony Miyaguchi

We develop a two-stage retrieval system that combines multiple complementary retrieval methods with a learned reranker and LLM-based reranking, to address the TREC Tip-of-the-Tongu…

cs.CV2025

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…

cs.CV2025

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…