Papers by Fernando Rodriguez
Small Encoders Can Rival Large Decoders in Detecting Groundedness (2025.findings-acl)
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Istabrak Abbes, Gabriele Prato, Quentin Fournier, Fernando Rodriguez, Alaa Boukhary, Adam Elwood, Sarath Chandar
| Challenge: | Large language models struggle to answer queries reliably when the provided context lacks information, often resorting to ungrounded speculation or internal knowledge. |
| Approach: | They propose to detect whether a given query is grounded in a document provided in context before LLMs generate answers. |
| Outcome: | The proposed model can generate answers that are grounded in the document provided in context while reducing inference latency by orders of magnitude. |