Lawformer A Pre trained Language Model for Chinese Legal Long Documents

Legal artificial intelligence (LegalAI) aims to benefit legal systems with the technology of artificial intelligence, especially natural languageprocessing (NLP) In this paper, we release the Longformer-based pre-trained languagemodel, named as Lawformer, for Chinese legal long documents understanding . Weevaluate Lawformer on a variety of LegalAI tasks, including judgmentprediction, similar case retrieval, legal reading comprehension, and legalquestion answering .…

Similarity Downselection A Python implementation of a heuristic search algorithm for finding the set of the n most dissimilar items with an application in conformer sampling

Finding the set of the n items most dissimilar from each other out of alarger population becomes increasingly difficult and computationally expensive . An exactsolution would have to search all possible combinations of size n in the population, exhaustively . We present an open-source software called similaritydownselection (SDS) written in Python and freely available on GitHub .…

Stochastic Multi Armed Bandits with Control Variates

This paper studies a new variant of the stochastic multi-armed banditsproblem, where the learner has access to auxiliary information about the arms . The auxiliary information is correlated with the arm rewards, which we treat as control variates . In many applications, the rewards are a function of someexogenous values, whose mean value is known a priori from historical data .…

Dataset and Performance Comparison of Deep Learning Architectures for Plum Detection and Robotic Harvesting

Robotic fruit harvesting is an important technology to address the increasing labourshortages and uncertainty suffered by tree crop growers . An eye-in-hand sensingsetup is commonly used in harvesting systems and provides benefits to sensingaccuracy and flexibility . However, as the hand and camera move from viewing theentire trellis to picking a specific fruit, large changes in lighting, colour, and exposure occur .…

ReLie a Reduce program for Lie group analysis of differential equations

Lie symmetry analysis provides a theoretical framework for investigating ordinary and partial differential equations . The theory is algorithmic even if it usually involves lengthy computations . ReLie, written in the Computer Algebra System Reduce, is able to perform almost automatically the needed computations for Lie symmetric analysis of differential equations.…

News Kaleidoscope Visual Investigation of Coverage Diversity in News Event Reporting

We develop a visual analytics system to investigate thehow news reporting of events varies . NewsKaleidoscope combines several backendtext language processing techniques with a coordinated visualization interfacetailored for visualization non-expert users . Results indicate that, for bothnews novice and experts, NewsKalidoscope supports an effective, task-drivenflow for analyzing the diversity of news coverage about events, thoughjournalism expertise has a significant influence on the user insights and takeaways .…

Holomorphic feedforward networks

Feedforward neural network is a popular model in machine learning . The FFN can approximate general functions and mitigate the curse ofdimensionality . Here we introduce FFNs which represent sections of holomorphicline bundles on complex manifolds . We also explain formal similarities between the standardapproach to supervised learning and the problem of finding numerical Ricci flatK\”ahler metrics .…

Swarm Differential Privacy for Purpose Driven Data Information Knowledge Wisdom Architecture

Privacy protection has recently attracted the attention of both academics and industry . Society protects individual data privacy through complex legalframeworks . Swarm Intelligence could effectively optimize and reduce thenumber of items in DIKW used in differential privacy . The proposed approach is proved through the application of personalized data that is based on the open-sourse IRIS dataset .…

Continual Mixed Language Pre Training for Extremely Low Resource Neural Machine Translation

The data scarcity in low-resource languages has become a bottleneck tobuilding robust neural machine translation systems . In this paper, we present a continual pre-training framework on mBART to adapt it to unseen languages . We first construct noisymixed-language text from the monolingual corpus of the target language in the translation pair to cover both the source and target languages .…

Solving social dilemmas by reasoning about expectations

It has been argued that social constructs coordinate the expectations of autonomous entities in order to resolve collective action situations . We investigate how explicitreasoning about expectations can be used to encode both traditional game theory solutions and social mechanisms for the social dilemma situation .…

Opening the Blackbox Accelerating Neural Differential Equations by Regularizing Internal Solver Heuristics

Current strategies to overcome slow prediction require high order automaticdifferentiation, leading to significantly higher training time . We describe anovel regularization method that uses internal cost heuristics of adaptivedifferential equation solvers combined with discrete adjoint sensitivities toguide the training process towards learning NDEs that are easier to solve .…

Employing Agent Beliefs during Fault Diagnosis for IEC 61499 Industrial Cyber Physical Systems

Efficient,reliable fault identification and management has become a critical factor in the design of increasingly sophisticated and complex devices . Teams of software agents are one way to coordinate the flow of diagnosticinformation gathered during fault-finding . Using domain knowledge of the IEC61499 Function Block architecture, agents are able to examine and rigorouslyevaluate both individual components and entire subsystems.…

Meta validation of bipartite network projections

Monopartite projections of bipartite networks are key tools to model indirectinteractions in complex systems . The standard approach to extract informativepatterns from these systems is to statistically validate them using a suitablenull network model . However different CM formulations exist, depending on how the degree constraints are imposed and for which nodes are nodes .…

A Novel Map of Knowledge for Science

A three-dimensional knowledge map is proposed with time, space and number based on category and numericity . It concludes all the scientific problems related to numericity interdisciplinary . It is intuitive and readable, on which nature, society and formal science are expressed in the same picture .…

Euclidean Distance Optimal Post Processing of Grid Based Paths

Paths planned over grids can often be suboptimal in an Euclidean space and contain a large number of unnecessary turns . Researchers have looked into post-processing techniques to improve the paths after they are planned . Homotopic Visibility Graph Planning (HVG) is guaranteed to shorten the path such that it is at least as short as the provably shortest path that lies within the same topological class as the initially computed path .…

Learning Image Attacks toward Vision Guided Autonomous Vehicles

This paper presents an online adversarial machine learning framework that can effectively misguide autonomous vehicles’ missions . The framework removes the need for fully converged optimization atevery frame to realize image attacks in real-time . Using reinforcementlearning, a generative neural network is trained over a set of image frames to obtain an attack policy that is more robust to dynamic and uncertain environments .…

Delay Tolerant Constrained OCO with Application to Network Resource Allocation

We consider online convex optimization (OCO) with multi-slot feedback delay . The current convex lossfunction and the long-term constraint function are revealed to the agent onlyafter the decision is made . Wepropose an efficient algorithm, termed Delay-Tolerant Constrained-OCO, which uses a novel constraint penalty with double regularization totackle the asynchrony between information feedback and decision updates .…

Generative Mechanisms The mechanisms that implement codes

The purpose of this paper is to abstractly describe the notion of agenerative mechanism that implements a code . A generative mechanism is distinguishedfrom a selectionist mechanism that has heretofore played an important role in modeling (e.g., Darwinian evolution and the immune system) The paper provides examples of the DNA-RNA machinery that implements the genetic code, Chomsky’sPrinciples & Parameters model of a child acquiring a specific grammar given`chunks’ of linguistic experience .…

Fast n fold Boolean Convolution via Additive Combinatorics

We consider the problem of computing the Boolean convolution (withwraparound) of $n$~vectors of dimension $m$ Although nearly optimal algorithms are known for specialcases of this problem, not even tiny improvements have been known for the generalcase . We almost resolve the computational complexity of the problem, shaving a factor of $ n$ from the running time of previous algorithms .…

Aerospace Sliding Mode Control Toolbox Relative Degree Approach with Resource Prospector Lander and Launch Vehicle Case Studies

Sliding mode control and observation techniques are widely used in aerospace applications, including aircrafts, UAVs, launch vehicles, missileinterceptors, and hypersonic missiles . This work is dedicated to creating aMATLAB-based sliding mode controller design and simulation software toolbox . The efficacy of the SMC Aero toolbox isconfirmed in two case studies: controlling and simulating resource prospectorlander (RPL) soft landing on the Moon and launch vehicle (LV) attitude control in ascent mode .…

Impacts of Privately Owned Electric Vehicles on Distribution System Resilience A Multi agent Optimization Approach

We investigate the effects of private electric vehicles (EVs) on the resilience of distribution systems after disruptions . We propose a framework of network-based multi-agent optimization problems with equilibrium constraints . To solve the high-dimensional non-convexproblem, we develop an efficient computational algorithm based on exact convexreformulation .…

High performance symbolic numerics via multiple dispatch

Symbolics.jl is an extendable symbolicsystem which uses dynamic multiple dispatch to change behavior depending on the domain needs . We show that byformalizing a generic API on actions independent of implementation, we can retroactively add optimized data structures to our system without changing thepre-existing term rewriters .…

Discomfort a New Material for Interaction Design

This paper proposes discomfort as a new material for HCI researchers and designers to consider in any application that helps a person develop a newskill, practice or state . Engaging effectively with discomfort may lead to increased personal development . We propose incorporating discomfort-as-material into our designs explicitly as a mechanism to makedesired adaptations available to more of us, more effectively and more of thetime.…

FNet Mixing Tokens with Fourier Transforms

We show that Transformer encoder architectures can be massively sped up, with limited accuracy costs, by replacing the self-attention sublayers with simplelinear transformations that “mix” input tokens . The resulting model,which we name FNet, scales very efficiently to long inputs, matching the accuracy of the most accurate “efficient” Transformers on the Long Range Arenabenchmark, but training and running faster across all sequence lengths on GPUs .…

Non iterative Optimization Algorithm for Active Distribution Grids Considering Uncertainty of Feeder Parameters

A paper formulates a time-varying optimization problem for distribution grids with DERs and develops a novel non-iterative algorithm . Different from existing methods, the proposedapproach does not require iterations during the sampling interval . It only needs to perform a single one-step calculation at each interval to obtain theevolution of the optimal trajectory .…

Analyzing Online Political Advertisements

Online political advertising is a central aspect of modern election campaigns . Computational analysis of political ads is of utmost importance in political science to understand characteristicsof digital campaigning . It is also important in computational linguistics to study features of political discourse and communication on a large scale .…