Papers with detection techniques
Rethinking Hallucinations: Correctness, Consistency, and Prompt Multiplicity (2026.eacl-long)
Copied to clipboard
| Challenge: | Existing hallucination evaluations focus only on correctness and often overlook consistency . a significant inconsistency in benchmarks like Med-HALT suggests hallucianation-related harms have been misunderstood. |
| Approach: | They propose a framework for quantifying consistency in hallucination evaluations . they find that detection techniques detect consistency, not correctness . |
| Outcome: | The proposed framework uncovers critical limitations in hallucination evaluations. |
EMO&LY (EMOtion and AnomaLY) : A new corpus for anomaly detection in an audiovisual stream with emotional context. (L18-1)
Copied to clipboard
| Challenge: | Anomalies in discourse are induced or acted by a machine learning algorithm. |
| Approach: | They propose to use facial and speech video to create a corpus that contains controlled anomalies. |
| Outcome: | The proposed corpus contains controlled anomalies in speech and facial video recordings of subjects. |
Explainable Tsetlin Machine Framework for Fake News Detection with Credibility Score Assessment (2022.lrec-1)
Copied to clipboard
| Challenge: | Existing models for fake news classification are difficult to explain and quality-assure . however, they are black-box-based and lack a clear explanation of their decisions. |
| Approach: | They propose an interpretable fake news detection framework based on the recently introduced Tsetlin Machine (TM) they use conjunctive clauses to capture lexical and semantic properties of both true and fake news text and use clause ensembles to calculate the credibility of fake news. |
| Outcome: | The proposed framework outperforms baseline models on PolitiFact and GossipCop datasets in terms of accuracy and provides higher F1-score than BERT and XLNet, but lower accuracy. |