2 citations · 3 across the 20 of their papers we have counts for
4 papers · 1 filter
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,…
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…
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…