The ADReSS Literature Survey is a literature survey for the results published during the ADReSS Challenge. Antonsson 2021: disfluency + SVF features trained on SVM: lexical > narrative qual. Chlasta 2021: features extracted from VGGish on SVM; also trained new CNN from .wav. Sadeghian 2021: Used GA for feature sel., achieved 94% w/ MMSE alone; dev’d ASR tool. Martinc 2021: CBOW (text) + ADR (sound) late fusion’d to a BERT, ablated for features. Meghanani 2021: spontaneous speech transcripts with fastText and CNN; 83.33% acc. Yuan 2021: ERNIE on transcripts with pause encoding; 89.6% acc. Jonell 2021: Developed a kitchen sink of diag. tools and correlated it with biomarkers. Laguarta 2021: multimodel (OVBM) to embed auditory info + biomarkers for clsf. Shah 2021: late fusion of n-gram and OpenSMILE on std. classifiers. Lindsay 2021: Cross-linguistic markers shared for AD patients between English and French. Zhu 2021: late fusion of CTP task for AD clsf. w/ transf., mobilenet, yamnet, mockingjay. Guo 2021: WLS data to augment CTP from ADReSS Challenge and trained it on a BERT. Balagopalan 2021: lexo. and synt. features trained on a BERT and other models. Mahajan 2021: a bimodal model on speech/text with GRU on speech and CNN-LSTM on text. Parvin 2020: excercize scheme effects on theta/alpha ratio and Brain wave frequency. Luz 2021: review paper presenting the ADReSSo challenge and current baselines. From Meghanani 2021, a review: