Papers with false acceptance rate
Using Meta-Knowledge Mined from Identifiers to Improve Intent Recognition in Conversational Systems (2021.acl-long)
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Claudio Pinhanez, Paulo Cavalin, Victor Henrique Alves Ribeiro, Ana Appel, Heloisa Candello, Julio Nogima, Mauro Pichiliani, Melina Guerra, Maira de Bayser, Gabriel Malfatti, Henrique Ferreira
| Challenge: | a recent study shows that meta-knowledge embedded in intent identifiers improves intent recognition in conversational systems . a meta-learning approach is used to classify sentences into discrete sets of classes . classification is a key part of professional conversational system implementations . |
| Approach: | They use meta-knowledge embedded in intent identifiers to improve intent recognition . authors found that meta-knowledge improved accuracy in conversational systems . |
| Outcome: | The meta-knowledge enabled improved intent recognition in conversational systems . the meta-learning improved the false acceptance rate in two thirds of the chatbots . |
SAFER: A Controllable Safeguard for LLMs against Backdoor Attacks (2026.findings-acl)
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| Challenge: | Existing inference-time defenses lack explicit control over false acceptance rate (FAR) existing inference time defenses aim to mitigate poisoned inputs but lack explicit FAR control . |
| Approach: | They propose a framework that provides explicit control over false acceptance rate without prior knowledge of backdoor samples. |
| Outcome: | The proposed framework outperforms existing inference-time defenses on three benchmark datasets . it provides explicit and provable control over false acceptance rate without prior knowledge of backdoor samples . |