Showing 1–20 of 37 results
/ Date/ Name
Jun 24, 2019Variations on the Chebyshev-Lagrange Activation FunctionSep 24, 2021Robustness and Sensitivity of BERT Models Predicting Alzheimer's Disease from TextApr 2, 2019Impact of ASR on Alzheimer's Disease Detection: All Errors are Equal, but Deletions are More Equal than OthersSep 30, 2019Lexical Features Are More Vulnerable, Syntactic Features Have More Predictive PowerOct 2, 2018Findings of the E2E NLG ChallengeJun 3, 2021Comparing Acoustic-based Approaches for Alzheimer's Disease DetectionSep 12, 2022DECK: Behavioral Tests to Improve Interpretability and Generalizability of BERT Models Detecting Depression from TextJun 28, 2017The E2E Dataset: New Challenges For End-to-End GenerationMar 15, 2018RankME: Reliable Human Ratings for Natural Language GenerationMay 1, 2025Consistency in Language Models: Current Landscape, Challenges, and Future DirectionsFeb 18, 2023Cost-effective Models for Detecting Depression from SpeechDec 30, 2022Multi-modal deep learning system for depression and anxiety detectionAug 20, 2018Detecting cognitive impairments by agreeing on interpretations of linguistic featuresDec 4, 2019Cross-Language Aphasia Detection using Optimal Transport Domain AdaptationJul 26, 2020To BERT or Not To BERT: Comparing Speech and Language-based Approaches for Alzheimer's Disease DetectionOct 13, 2020Fantastic Features and Where to Find Them: Detecting Cognitive Impairment with a Subsequence Classification Guided ApproachJul 19, 2018Deconfounding age effects with fair representation learning when assessing dementiaJan 23, 2019Evaluating the State-of-the-Art of End-to-End Natural Language Generation: The E2E NLG ChallengeApr 2, 2024Zero-Shot Multi-Lingual Speaker Verification in Clinical TrialsMar 31, 2022Impact of Environmental Noise on Alzheimer's Disease Detection from Speech: Should You Let a Baby Cry?