Naturalizing a Programming Language via Interactive Learning

Our goal is to create a convenient natural language interface for performing well-specified but complex actions such as analyzing data, manipulating text, and querying databases. However, existing natural language interfaces for such tasks are quite primitive compared to the power one wields with a programming language. To bridge this gap, we start with a core programming language and allow users to "naturalize" the core language incrementally by defining alternative, more natural syntax and increasingly complex concepts in terms of compositions of simpler ones. In a voxel world, we show that a community of users can simultaneously teach a common system a diverse language and use it to build hundreds of complex voxel structures. Over the course of three days, these users went from using only the core language to using the naturalized language in 85.9\% of the last 10K utterances.Comment: 10 pages, ACL201

The Past and Present of the CCP First Congress Memorial, Shanghai

2009 is a year of anniversaries for China, with the 90th birthday of the May 4th Movement coming in the spring and the 60th of the PRC arriving in the fall. With this in mind, we’ve asked Samuel Liang of the University of Manchester, a specialist in Shanghai’s built environment, to provide our readers with background on a locale that has special significance for both of the just-mentioned anniversaries. Namely, the building where an early meeting of the Communist Party was held in 1921, which stands near the recently built shopping and entertainment district known as Xintiandi. This structure, often treated as a sacred revolutionary shrine, has a complex history, as readers will see. It is tied to the May 4th Movement because many of those who attended the Party Congress held within its wall, including Mao Zedong, had been active in those 1919 protests and the general “New Culture” intellectual fermentation of the time, and as a birthplace of the Communist Party it is tied to the founding of the PRC in even more obvious ways. In the late nineteenth century, foreign landowners and Chinese builders jointly created lilong compounds for Chinese residents in the foreign settlements of Shanghai. Somewhere between enclosed compounds and open alleyways, thelilong houses opened up traditional walled domains, generated fluid spaces between houses, neighborhoods, and streets, and accommodated a wide range of commercial and residential functions and people from all walks of life

Simple Baselines for Interactive Video Retrieval with Questions and Answers

To date, the majority of video retrieval systems have been optimized for a "single-shot" scenario in which the user submits a query in isolation, ignoring previous interactions with the system. Recently, there has been renewed interest in interactive systems to enhance retrieval, but existing approaches are complex and deliver limited gains in performance. In this work, we revisit this topic and propose several simple yet effective baselines for interactive video retrieval via question-answering. We employ a VideoQA model to simulate user interactions and show that this enables the productive study of the interactive retrieval task without access to ground truth dialogue data. Experiments on MSR-VTT, MSVD, and AVSD show that our framework using question-based interaction significantly improves the performance of text-based video retrieval systems.Comment: ICCV 2023, project page: https://github.com/kevinliang888/IVR-QA-baseline

Infrared Dichroism of Mutually Perpendicular Normal Modes in Oriented High Polymers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71246/2/JCPSA6-27-6-1437-1.pd

Orientation in Polyethylene Terephthalate Film

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/70201/2/JCPSA6-27-1-327-1.pd

Infrared Spectra of High Polymers. III. Polytetrafluoroethylene and Polychlorotrifluoroethylene

The infrared spectra of polytetrafluoroethylene and polychlorotrifluoroethylene have been obtained between 4000 cm—1 and 70 cm—1. Polarization measurements on oriented samples were obtained in the region of 4000 cm—1 to 300 cm—1. It is known from x‐ray diffraction studies that both polymers have helical chain configurations. From a factor group analysis of the one‐dimensional space group, selection rules and approximate vibrational patterns of the infrared active fundamentals have been derived. A calculation of the normal frequencies of an assumed planar zig‐zag chain model of (CF2)n has been made, resulting in a satisfactory assignment of the bands in the infrared spectra of both polymers.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/71248/2/JCPSA6-25-3-563-1.pd

Adaptive MCMC for Bayesian variable selection in generalised linear models and survival models

Developing an efficient computational scheme for high-dimensional Bayesian variable selection in generalised linear models and survival models has always been a challenging problem due to the absence of closed-form solutions for the marginal likelihood. The RJMCMC approach can be employed to samples model and coefficients jointly, but effective design of the transdimensional jumps of RJMCMC can be challenge, making it hard to implement. Alternatively, the marginal likelihood can be derived using data-augmentation scheme e.g. Polya-gamma data argumentation for logistic regression) or through other estimation methods. However, suitable data-augmentation schemes are not available for every generalised linear and survival models, and using estimations such as Laplace approximation or correlated pseudo-marginal to derive marginal likelihood within a locally informed proposal can be computationally expensive in the "large n, large p" settings. In this paper, three main contributions are presented. Firstly, we present an extended Point-wise implementation of Adaptive Random Neighbourhood Informed proposal (PARNI) to efficiently sample models directly from the marginal posterior distribution in both generalised linear models and survival models. Secondly, in the light of the approximate Laplace approximation, we also describe an efficient and accurate estimation method for the marginal likelihood which involves adaptive parameters. Additionally, we describe a new method to adapt the algorithmic tuning parameters of the PARNI proposal by replacing the Rao-Blackwellised estimates with the combination of a warm-start estimate and an ergodic average. We present numerous numerical results from simulated data and 8 high-dimensional gene fine mapping data-sets to showcase the efficiency of the novel PARNI proposal compared to the baseline add-delete-swap proposal

Structure Learning with Adaptive Random Neighborhood Informed MCMC

In this paper, we introduce a novel MCMC sampler, PARNI-DAG, for a fully-Bayesian approach to the problem of structure learning under observational data. Under the assumption of causal sufficiency, the algorithm allows for approximate sampling directly from the posterior distribution on Directed Acyclic Graphs (DAGs). PARNI-DAG performs efficient sampling of DAGs via locally informed, adaptive random neighborhood proposal that results in better mixing properties. In addition, to ensure better scalability with the number of nodes, we couple PARNI-DAG with a pre-tuning procedure of the sampler's parameters that exploits a skeleton graph derived through some constraint-based or scoring-based algorithms. Thanks to these novel features, PARNI-DAG quickly converges to high-probability regions and is less likely to get stuck in local modes in the presence of high correlation between nodes in high-dimensional settings. After introducing the technical novelties in PARNI-DAG, we empirically demonstrate its mixing efficiency and accuracy in learning DAG structures on a variety of experiments