Preconditioned Visual Language Inference with Weak Supervision

Humans can infer the affordance of objects by extracting related contextual preconditions for each scenario. For example, upon seeing an image of a broken cup, we can infer that this precondition prevents the cup from being used for drinking. Reasoning with preconditions of commonsense is studied in NLP where the model explicitly gets the contextual precondition. However, it is unclear if SOTA visual language models (VLMs) can extract such preconditions and infer the affordance of objects with them. In this work, we introduce the task of preconditioned visual language inference and rationalization (PVLIR). We propose a learning resource based on three strategies to retrieve weak supervision signals for the task and develop a human-verified test set for evaluation. Our results reveal the shortcomings of SOTA VLM models in the task and draw a road map to address the challenges ahead in improving them

Joint NMF for Identification of Shared Features in Datasets and a Dataset Distance Measure

In this paper, we derive a new method for determining shared features of datasets by employing joint non-negative matrix factorization and analyzing the resulting factorizations. Our approach uses the joint factorization of two dataset matrices $X_1,X_2$ into non-negative matrices $X_1 = AS_1, X_2 = AS_2$ to derive a similarity measure that determines how well a shared basis for $X_1, X_2$ approximates each dataset. We also propose a dataset distance measure built upon this method and the learned factorization. Our method is able to successfully identity differences in structure in both image and text datasets. Potential applications include classification, detecting plagiarism or other manipulation, and learning relationships between data sets

Structural characterization of low‐temperature molecular beam epitaxial In0.52Al0.48As/InP heterolayers

A systematic study of the structural quality and arsenic content of as‐grown In0.52Al0.48As/InP layers deposited on InP by molecular beam epitaxy at temperatures between 150 and 450 °C was performed using transmission electron microscopy and particle‐induced x‐ray emission. We found that the amount of As incorporated in the layers generally increases with decreasing growth temperature, with the crystalline quality of the layers being good at growth temperatures higher than 200 °C. At 150 °C, a large density of pyramidal defects is formed, the defects are related to the very large amount of excess As incorporated into the layer. The mechanisms leading to the formation of these defects are discussed. At 200 °C, however, the amount of excess As is lower than expected, and wavy streaks of diffuse scattering are seen in electron diffraction. It is shown that small ordered domains of the CuPt type on the group III atoms are responsible for these features.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70657/2/APPLAB-60-8-989-1.pd

A Surface Reconstruction with a Fractional Hole: (5×5)R26.6∘(\sqrt{5}\times\sqrt{5}) R26.6^\circ LaAlO3_3 (001)

The structure of the $(\sqrt{5}\times\sqrt{5})R26.6^\circ$ reconstruction of LaAlO$_3$ (001) has been determined using transmission electron diffraction combined with direct methods. The structure is relatively simple, consisting of a lanthanum oxide termination with one lanthanum cation vacancy per surface unit cell. The electronic structure is unusual since a fractional number of holes or atomic occupancies per surface unit cell are required to achieve charge neutrality. Density functional calculations indicate that the charge compensation mechanism occurs by means of highly delocalized holes. The surface contains no oxygen vacancies and with a better than 99% confidence level, the holes are not filled with hydrogen. The reconstruction can be understood in terms of expulsion of the more electropositive cation from the surface followed by an increased covalency between the remaining surface lanthanum atoms and adjacent oxygen atoms.Comment: 4 Pages, 3 Figure

High-Resolution Electron Microscopy of Semiconductor Heterostructures and Nanostructures

This chapter briefly describes the fundamentals of high-resolution electron microscopy techniques. In particular, the Peak Pairs approach for strain mapping with atomic column resolution, and a quantitative procedure to extract atomic column compositional information from Z-contrast high-resolution images are presented. It also reviews the structural, compositional, and strain results obtained by conventional and advanced transmission electron microscopy methods on a number of III–V semiconductor nanostructures and heterostructures