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arXiv · 2506.22356

HLTCOE at LiveRAG: GPT-Researcher using ColBERT retrieval

Kevin Duh·Eugene Yang·Orion Weller·Andrew Yates·Dawn Lawrie
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Abstract

The HLTCOE LiveRAG submission utilized the GPT-researcher framework for researching the context of the question, filtering the returned results, and generating the final answer. The retrieval system was a ColBERT bi-encoder architecture, which represents a passage with many dense tokens. Retrieval used a local, compressed index of the FineWeb10-BT collection created with PLAID-X, using a model fine-tuned for multilingual retrieval. Query generation from context was done with Qwen2.5-7B-Instruct, while filtering was accomplished with m2-bert-80M-8k-retrieval. Up to nine passages were used as context to generate an answer using Falcon3-10B. This system placed 5th in the LiveRAG automatic evaluation for correctness with a score of 1.07.

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Kevin Duh, Eugene Yang, Orion Weller, Andrew Yates, Dawn Lawrie. 2025-06-27. HLTCOE at LiveRAG: GPT-Researcher using ColBERT retrieval. https://arxiv.org/abs/2506.22356

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