Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling

Uncertainty decomposition refers to the task of decomposing the total uncertainty of a model into data (aleatoric) uncertainty, resulting from the inherent complexity or ambiguity of the data, and model (epistemic) uncertainty, resulting from the lack of knowledge in the model. Performing uncertainty decomposition for large language models (LLMs) is an important step toward improving the reliability, trustworthiness, and interpretability of LLMs, but this research task is very challenging and remains unresolved. The existing canonical method, Bayesian Neural Network (BNN), cannot be applied to LLMs, because BNN requires training and ensembling multiple variants of models, which is infeasible or prohibitively expensive for LLMs. In this paper, we introduce an uncertainty decomposition framework for LLMs, called input clarifications ensemble, which bypasses the need to train new models. Rather than ensembling models with different parameters, our approach generates a set of clarifications for the input, feeds them into the fixed LLMs, and ensembles the corresponding predictions. We show that our framework shares a symmetric decomposition structure with BNN. Empirical evaluations demonstrate that the proposed framework provides accurate and reliable uncertainty quantification on various tasks. Code will be made publicly available at https://github.com/UCSB-NLP-Chang/llm_uncertainty .Comment: 15 pages, 3 figure

Gray Matter Atrophy in Parkinson’s Disease and the Parkinsonian Variant of Multiple System Atrophy: A Combined ROI- and Voxel-Based Morphometric Study

OBJECTIVES: Parkinson’s disease (PD) and the parkinsonian variant of multiple system atrophy (MSA-P) are distinct neurodegenerative disorders that share similar clinical features of parkinsonism. The morphological alterations of these diseases have yet to be understood. The purpose of this study was to evaluate gray matter atrophy in PD and MSA-P using regions of interest (ROI)-based measurements and voxel-based morphometry (VBM). METHODS: We studied 41 patients with PD, 20 patients with MSA-P, and 39 controls matched for age, sex, and handedness using an improved T1-weighted sequence that eased gray matter segmentation. The gray matter volumes were measured using ROI and VBM. RESULTS: ROI volumetric measurements showed significantly reduced bilateral putamen volumes in MSA-P patients compared with those in PD patients and controls (po0.05), and the volumes of the bilateral caudate nucleus were significantly reduced in both MSA-P and PD patients compared with those in the controls (po0.05). VBM analysis revealed multifocal cortical and subcortical atrophy in both MSA-P and PD patients, and the volumes of the cerebellum and temporal lobes were remarkably reduced in MSA-P patients compared with the volumes in PD patients (po0.05). CONCLUSIONS: Both PD and MSA-P are associated with gray matter atrophy, which mainly involves the bilateral putamen, caudate nucleus, cerebellum, and temporal lobes. ROI and VBM can be used to identify these morphological alterations, and VBM is more sensitive and repeatable and less time-consuming, which may have potential diagnostic value

Thermal-Induced Autolysis Enzymes Inactivation, Protein Degradation and Physical Properties of Sea Cucumber, Cucumaria frondosa

Funding Information: Funding: This work was supported by the Fisheries Training Programme of United Nations University (UNU-FTP2017), Research and Demonstration of Efficient Clean Production Mode of Important Marine Fish in Liaoning Province (2020JH1/10200002), National Key R&D Program of China (2019YFD0901800), Project of Education Department of Liaoning Province (JL202011), Project of Ocean and Fisheries Department of Liaoning Province (201722), Key Laboratory of Environment Controlled Aquaculture (Dalian Ocean University) Ministry of Education (202203); National Key R&D Program of China (2020YFD0900600). Funding Information: Acknowledgments: The authors would like to express their heartfelt gratitude to United Nations University Fisheries Training Programme (now GRÓ Fisheries Training Programme, United Nations Education, Scientific and Cultural Organization) and Matis for supporting this research. Special thanks go to Tumi Tomasson, Thor Asgeirsson, Mary Frances Davidson, Julie Ingham, Stefan Ulfarsson, and Lilja Bjork Jonsdottir, for their enthusiastic guidance and assistance during the experiment. Publisher Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland.The main objective is to effectively denature the autolysis enzymes of C. frondosa on the premise of avoiding the quality deterioration caused by overheating. The effects of the different thermal treatments (blanching at 40–80◦ C for 45 min, boiling and steaming at 100◦ C for 15–120 min) on the cooking yield, moisture content, protein degradation, texture, and enzyme inactivation were studied, and the inner relationship was investigated by multivariate analysis. The autolysis enzymes of C. frondosa were thermally stable and cannot be denatured completely by blanching. Boiling and steaming could efficiently inactivate the enzymes but overheating for 60–120 min reduced the cooking yield and texture quality. Boiling at 100◦ C for 45 min was suitable for pre-treatment, with cooking yield of 70.3% and protein content of 78.5%. Steaming at 100◦ C for at least 30 min was preferable for long-term storage and instant food, in which the relative activity was only 3.2% with better palatability.Peer reviewe

Genotypic and Environmental Effects on the Volatile Chemotype of Valeriana jatamansi Jones

Valeriana jatamansi Jones is an aromatic medicinal herb and important alternative to V. officinalis, which is utilized for medicinal purposes in China and India and also as spices in India. Bioactive ingredients of V. jatamansi vary in different regions. However, no information is currently available on influence of genotype and environmental factors in the volatile compounds, especially when germplasms and planting locations need to be selected. Based on the results of SNP and volatile constituents from GC-MS analysis, this study found various genotypes and chemotypes of V. jatamansi for wild plants from seven regions in China and common-garden samples; correlations between genotype and chemotype were revealed for the plants. Two distinct populations (PX, FY) were distinguishable from five others (GJ, YL, SY, DD, DY) according to their genotypes and volatile profiles, the consistency of which was observed showing that genotype could significantly influence chemotype. Wild populations and common-garden samples were also separated in their volatile profiles, demonstrating that environmental factors strongly affected their chemotypes. Compounds contributing to the discrimination were identified as discriminatory compounds. This investigation has explored and provided essential information concerning the correlation between genotype and chemotype as well as environmental factors and chemotype of V. jatamansi in some regions of China. Feasible plantation and conservation strategies of V. jatamansi could be further explored based on these results