OpenRaiser/Intern-Atlas huggingface dataset:
WikiTexVC: MediaWiki's native LaTeX to MathML converter for Wikipedia
Venue: arXiv cs.DL 2024
Year: 2024

MediaWiki and Wikipedia authors usually use LaTeX to define mathematical formulas in the wiki text markup. In the Wikimedia ecosystem, these formulas were processed by a long cascade of web services and finally delivered to users' browsers in rendered form for visually readable representation as SVG. With the latest developments of supporting MathML Core in Chromium-based browsers, MathML continues its path to be a de facto standard markup language for mathematical notation in the web. Conveying formulas in MathML enables semantic annotation and machine readability for extended interpretation of mathematical content, in example for accessibility technologies. With this work, we present WikiTexVC, a novel method for validating LaTeX formulas from wiki texts and converting them to MathML, which is directly integrated into MediaWiki. This mitigates the shortcomings of previously used rendering methods in MediaWiki in terms of robustness, maintainability and performance. In addition, there is no need for a multitude of web services running in the background, but processing takes place directly within MediaWiki instances. We validated this method with an extended dataset of over 300k formulas which have been incorporated as automated tests to the MediaWiki continuous integration instances. Furthermore, we conducted an evaluation with 423 formulas, comparing the tree edit distance for produced parse trees to other MathML renderers. Our method has been made available Open Source and can be used on German Wikipedia and is delivered with recent MediaWiki versions. As a practical example of enabling semantic annotations within our method, we present a new macro that adds content to formula disambiguation to facilitate accessibility for visually impaired people.
A Complete Fragment of LTL(EB)
Venue: arXiv cs.LO 2024
Year: 2024

The verification of liveness conditions is an important aspect of state-based rigorous methods. This article investigates this problem in a fragment $\square$LTL of the logic LTL(EB), the integration of the UNTIL-fragment of Pnueli's linear time temporal logic (LTL) and the logic of Event-B, in which the most commonly used liveness conditions can be expressed. For this fragment a sound set of derivation rules is developed, which is also complete under mild restrictions for Event-B machines.
Scalable Network Emulation on Analog Neuromorphic Hardware
Venue: arXiv cs.NE 2024
Year: 2024

We present a novel software feature for the BrainScaleS-2 accelerated neuromorphic platform that facilitates the partitioned emulation of large-scale spiking neural networks. This approach is well suited for deep spiking neural networks and allows for sequential model emulation on undersized neuromorphic resources if the largest recurrent subnetwork and the required neuron fan-in fit on the substrate. The ability to emulate and train networks larger than the substrate provides a pathway for accurate performance evaluation in planned or scaled systems, ultimately advancing the development and understanding of large-scale models and neuromorphic computing architectures. We demonstrate the training of two deep spiking neural network models -- using the MNIST and EuroSAT datasets -- that exceed the physical size constraints of a single-chip BrainScaleS-2 system.
Depends-Kotlin: A Cross-Language Kotlin Dependency Extractor
Venue: arXiv cs.SE 2024
Year: 2024

Since Google introduced Kotlin as an official programming language for developing Android apps in 2017, Kotlin has gained widespread adoption in Android development. However, compared to Java, there is limited support for Kotlin code dependency analysis, which is the foundation to software analysis. To bridge this gap, we develop Depends-Kotlin to extract entities and their dependencies in Kotlin source code. Not only does Depends-Kotlin support extracting entities' dependencies in Kotlin code, but it can also extract dependency relations between Kotlin and Java. Using three open-source Kotlin-Java mixing projects as our subjects, Depends-Kotlin demonstrates high accuracy and performance in resolving Kotlin-Kotlin and Kotlin-Java dependencies relations. The source code of Depends-Kotlin and the dataset used have been made available at https: //github.com/XYZboom/depends-kotlin. We also provide a screen-cast presenting Depends-Kotlin at https://youtu.be/ZPq8SRhgXzM.
New Centralized MSR Codes With Small Sub-packetization
Venue: arXiv cs.IT 2024
Year: 2024

Centralized repair refers to repairing $h\geq 2$ node failures using $d$ helper nodes in a centralized way, where the repair bandwidth is counted by the total amount of data downloaded from the helper nodes. A centralized MSR code is an MDS array code with $(h,d)$-optimal repair for some $h$ and $d$. In this paper, we present several classes of centralized MSR codes with small sub-packetization. At first, we construct an alternative MSR code with $(1,d_i)$-optimal repair for multiple repair degrees $d_i$ simultaneously. Based on the code structure, we are able to construct a centralized MSR code with $(h_i,d_i)$-optimal repair property for all possible $(h_i,d_i)$ with $h_i\mid (d_i-k)$ simultaneously. The sub-packetization is no more than ${\rm lcm}(1,2,\ldots,n-k)(n-k)^n$, which is much smaller than a previous work given by Ye and Barg ($({\rm lcm}(1,2,\ldots,n-k))^n$). Moreover, for general parameters $2\leq h\leq n-k$ and $k\leq d\leq n-h$, we further give a centralized MSR code enabling $(h,d)$-optimal repair with sub-packetization smaller than all previous works.
A Tournament of Transformation Models: B-Spline-based vs. Mesh-based Multi-Objective Deformable Image Registration
Venue: arXiv cs.CV 2024
Year: 2024

The transformation model is an essential component of any deformable image registration approach. It provides a representation of physical deformations between images, thereby defining the range and realism of registrations that can be found. Two types of transformation models have emerged as popular choices: B-spline models and mesh models. Although both models have been investigated in detail, a direct comparison has not yet been made, since the models are optimized using very different optimization methods in practice. B-spline models are predominantly optimized using gradient-descent methods, while mesh models are typically optimized using finite-element method solvers or evolutionary algorithms. Multi-objective optimization methods, which aim to find a diverse set of high-quality trade-off registrations, are increasingly acknowledged to be important in deformable image registration. Since these methods search for a diverse set of registrations, they can provide a more complete picture of the capabilities of different transformation models, making them suitable for a comparison of models. In this work, we conduct the first direct comparison between B-spline and mesh transformation models, by optimizing both models with the same state-of-the-art multi-objective optimization method, the Multi-Objective Real-Valued Gene-pool Optimal Mixing Evolutionary Algorithm (MO-RV-GOMEA). The combination with B-spline transformation models, moreover, is novel. We experimentally compare both models on two different registration problems that are both based on pelvic CT scans of cervical cancer patients, featuring large deformations. Our results, on three cervical cancer patients, indicate that the choice of transformation model can have a profound impact on the diversity and quality of achieved registration outcomes.
The Thins Ordering on Relations
Venue: arXiv cs.LO 2024
Year: 2024

Earlier papers \cite{VB2022,VB2023a,VB2023b} introduced the notions of a core and an index of a relation (an index being a special case of a core). A limited form of the axiom of choice was postulated -- specifically that all partial equivalence relations (pers) have an index -- and the consequences of adding the axiom to axiom systems for point-free reasoning were explored. In this paper, we define a partial ordering on relations, which we call the \textsf{thins} ordering. We show that our axiom of choice is equivalent to the property that core relations are the minimal elements of the \textsf{thins} ordering. We also characterise the relations that are maximal with respect to the \textsf{thins} ordering. Apart from our axiom of choice, the axiom system we employ is paired to a bare minimum and admits many models other than concrete relations -- we do not assume, for example, the existence of complements; in the case of concrete relations, the theorem is that the maximal elements of the \textsf{thins} ordering are the empty relation and the equivalence relations. This and other properties of \textsf{thins} provide further evidence that our axiom of choice is a desirable means of strengthening point-free reasoning on relations.
A Rank-Constrained Coordinate Ascent Approach to Hybrid Precoding for the Downlink of Wideband Massive (MIMO) Systems
Venue: arXiv cs.IT 2024
Year: 2024

An innovative approach to hybrid analog-digital precoding for the downlink of wideband massive MIMO systems is developed. The proposed solution, termed Rank-Constrained Coordinate Ascent (RCCA), starts seeking the full-digital precoder that maximizes the achievable sum-rate over all the frequency subcarriers while constraining the rank of the overall transmit covariance matrix. The frequency-flat constraint on the analog part of the hybrid precoder and the non-convex nature of the rank constraint are circumvented by transforming the original problem into a more suitable one, where a convenient structure for the transmit covariance matrix is imposed. Such structure makes the resulting full-digital precoder particularly adequate for its posterior analog-digital factorization. An additional problem formulation to determine an appropriate power allocation policy according to the rank constraint is also provided. The numerical results show that the proposed method outperforms baseline solutions even for practical scenarios with high spatial diversity.
Generalized Reed-Muller codes: A new construction of information sets
Venue: arXiv cs.IT 2024
Year: 2024

In [2] we show how to construct information sets for Reed-Muller codes only in terms of their basic parameters. In this work we deal with the corresponding problem for q-ary Generalized Reed-Muller codes of first and second order. We see that for first-order codes the result for binary Reed-Muller codes is also valid, while for second-order codes, with q > 2, we have to manage more complex defining sets and we show that we get different information sets. We also present some examples and associated open problems.
On egalitarian values for cooperative games with level structures
Venue: arXiv cs.GT 2024
Year: 2024

In this paper we extend the equal division and the equal surplus division values for transferable utility cooperative games to the more general setup of transferable utility cooperative games with level structures. In the case of the equal surplus division value we propose three possible extensions, one of which has already been described in the literature. We provide axiomatic characterizations of the values considered, apply them to a particular cost sharing problem and compare them in the framework of such an application.
Exact SINR Analysis of Matched-filter Precoder
Venue: arXiv cs.IT 2024
Year: 2024

This paper answers a fundamental question about the exact distribution of the signal-to-interference-plus-noise ratio (SINR) under matched-filter (MF) precoding. Specifically, we derive the exact expressions for the cumulative distribution function (CDF) and the probability density function (PDF) of SINR under MF precoding over Rayleigh fading channels. Based on the exact analysis, we then rigorously prove that the SINR converges to some specific distributions separately in high SNR and in massive MIMO. To simplify the exact result in general cases, we develop a good approximation by modelling the interference as a Beta distribution. We then shift to the exact analysis of the transmit rate, and answer the fundamental question: How does the exact rate converge to the well-known asymptotic rate in massive MIMO? After that, we propose a novel approximation for the ergodic rate, which performs better than various existing approximations. Finally, we present some numerical results to demonstrate the accuracy of the derived analytical models.
Taxonomy of Mathematical Plagiarism
Venue: arXiv cs.IR 2024
Year: 2024

Plagiarism is a pressing concern, even more so with the availability of large language models. Existing plagiarism detection systems reliably find copied and moderately reworded text but fail for idea plagiarism, especially in mathematical science, which heavily uses formal mathematical notation. We make two contributions. First, we establish a taxonomy of mathematical content reuse by annotating potentially plagiarised 122 scientific document pairs. Second, we analyze the best-performing approaches to detect plagiarism and mathematical content similarity on the newly established taxonomy. We found that the best-performing methods for plagiarism and math content similarity achieve an overall detection score (PlagDet) of 0.06 and 0.16, respectively. The best-performing methods failed to detect most cases from all seven newly established math similarity types. Outlined contributions will benefit research in plagiarism detection systems, recommender systems, question-answering systems, and search engines. We make our experiment's code and annotated dataset available to the community: https://github.com/gipplab/Taxonomy-of-Mathematical-Plagiarism
Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow
Venue: arXiv cs.CV 2024
Year: 2024

Multi-image super-resolution (MISR) allows to increase the spatial resolution of a low-resolution (LR) acquisition by combining multiple images carrying complementary information in the form of sub-pixel offsets in the scene sampling, and can be significantly more effective than its single-image counterpart. Its main difficulty lies in accurately registering and fusing the multi-image information. Currently studied settings, such as burst photography, typically involve assumptions of small geometric disparity between the LR images and rely on optical flow for image registration. We study a MISR method that can increase the resolution of sets of images acquired with arbitrary, and potentially wildly different, camera positions and orientations, generalizing the currently studied MISR settings. Our proposed model, called EpiMISR, moves away from optical flow and explicitly uses the epipolar geometry of the acquisition process, together with transformer-based processing of radiance feature fields to substantially improve over state-of-the-art MISR methods in presence of large disparities in the LR images.
Performance Analysis of Generalized Product Codes with Irregular Degree Distribution
Venue: arXiv cs.IT 2024
Year: 2024

This paper investigates the theoretical analysis of intrinsic message passing decoding for generalized product codes (GPCs) with irregular degree distributions, a generalization of product codes that allows every code bit to be protected by a minimum of two and potentially more component codes. We derive a random hypergraph-based asymptotic performance analysis for GPCs, extending previous work that considered the case where every bit is protected by exactly two component codes. The analysis offers a new tool to guide the code design of GPCs by providing insights into the influence of degree distributions on the performance of GPCs.
Re3val: Reinforced and Reranked Generative Retrieval
Venue: arXiv cs.IR 2024
Year: 2024

Generative retrieval models encode pointers to information in a corpus as an index within the model's parameters. These models serve as part of a larger pipeline, where retrieved information conditions generation for knowledge-intensive NLP tasks. However, we identify two limitations: the generative retrieval does not account for contextual information. Secondly, the retrieval can't be tuned for the downstream readers as decoding the page title is a non-differentiable operation. This paper introduces Re3val, trained with generative reranking and reinforcement learning using limited data. Re3val leverages context acquired via Dense Passage Retrieval to rerank the retrieved page titles and utilizes REINFORCE to maximize rewards generated by constrained decoding. Additionally, we generate questions from our pre-training dataset to mitigate epistemic uncertainty and bridge the domain gap between the pre-training and fine-tuning datasets. Subsequently, we extract and rerank contexts from the KILT database using the rerank page titles. Upon grounding the top five reranked contexts, Re3val demonstrates the Top 1 KILT scores compared to all other generative retrieval models across five KILT datasets.
SAL-PIM: A Subarray-level Processing-in-Memory Architecture with LUT-based Linear Interpolation for Transformer-based Text Generation
Venue: arXiv cs.AR 2024
Year: 2024

Text generation is a compelling sub-field of natural language processing, aiming to generate human-readable text from input words. In particular, the decoder-only generative models, such as generative pre-trained transformer (GPT), are widely used for text generation, with two major computational stages: summarization and generation. Unlike the summarization stage, which can process the input tokens in parallel, the generation stage is difficult to accelerate due to its sequential generation of output tokens through iteration. Moreover, each iteration requires reading a whole model with little data reuse opportunity. Therefore, the workload of transformer-based text generation is severely memory-bound, making the external memory bandwidth system bottleneck. In this paper, we proposed a subarray-level processing-in-memory architecture named SAL-PIM, HBM-based PIM architecture for the end-to-end acceleration of transformer-based text generation. The SAL-PIM architecture includes three architectural features. First, the SAL-PIM architecture utilizes higher internal bandwidth by integrating multiple subarray-level arithmetic logic units with optimized data mapping schemes. Second, the SAL-PIM architecture adopts LUT-based linear interpolation to perform complex non-linear functions in PIM. Third, the SAL-PIM architecture accelerates end-to-end inference on PIM in text generation. Furthermore, to validate the SAL-PIM architecture, we built cycle-accurate simulator and implemented the SAL-PIM's logic units in 28-nm CMOS technology. As a result, when the input size is from 32 to 128 and the output size is from 1 to 256, SAL-PIM achieves a maximum of 4.72 times speedup and an average of 1.83 times speedup for the text generation based on the GPT-2 medium model compared to the server-level GPU.
Enhancing Gaussian Process Surrogates for Optimization and Posterior Approximation via Random Exploration
Venue: arXiv cs.LG 2024
Year: 2024

This paper proposes novel noise-free Bayesian optimization strategies that rely on a random exploration step to enhance the accuracy of Gaussian process surrogate models. The new algorithms retain the ease of implementation of the classical GP-UCB algorithm, but the additional random exploration step accelerates their convergence, nearly achieving the optimal convergence rate. Furthermore, to facilitate Bayesian inference with an intractable likelihood, we propose to utilize optimization iterates for maximum a posteriori estimation to build a Gaussian process surrogate model for the unnormalized log-posterior density. We provide bounds for the Hellinger distance between the true and the approximate posterior distributions in terms of the number of design points. We demonstrate the effectiveness of our Bayesian optimization algorithms in non-convex benchmark objective functions, in a machine learning hyperparameter tuning problem, and in a black-box engineering design problem. The effectiveness of our posterior approximation approach is demonstrated in two Bayesian inference problems for parameters of dynamical systems.
Movable Antenna-Enabled Co-Frequency Co-Time Full-Duplex Wireless Communication
Venue: arXiv cs.IT 2024
Year: 2024

Movable antenna (MA) provides an innovative way to arrange antennas that can contribute to improved signal quality and more effective interference management. This technology is especially beneficial for co-frequency co-time full-duplex (CCFD) wireless communication, which struggles with self-interference (SI) that usually overpowers the desired incoming signals. By dynamically repositioning transmit/receive antennas, we can mitigate the SI and enhance the reception of incoming signals. Thus, this paper proposes a novel MA-enabled point-to-point CCFD system and formulates the minimum achievable rate of two CCFD terminals. To maximize the minimum achievable rate and determine the positions of MAs, we introduce a solution based on projected particle swarm optimization (PPSO), which can circumvent common suboptimal positioning issues. Moreover, simulation results reveal that the PPSO method leads to better performance compared to the conventional alternating position optimization (APO). The results also demonstrate that an MA-enabled CCFD system outperforms the one using fixed-position antennas (FPAs).
Casting manipulation of unknown string by robot arm
Venue: arXiv cs.RO 2024
Year: 2024

Casting manipulation has been studied to expand the robot's movable range. In this manipulation, the robot throws and reaches the end effector to a distant target. Usually, a special casting manipulator, which consists of rigid arm links and specific flexible linear objects, is constructed for an effective casting manipulation. However, the special manipulator cannot perform normal manipulations, such as picking and placing, grasping, and operating objects. We propose that the normal robot arm, which can perform normal tasks, picks up an unknown string in the surrounding environment and realizes casting manipulation with it. As the properties of the string are not provided in advance, it is crucial how to reflect it in casting manipulation. This is realized by the motion generation of the robot arm with the simulation of string movement, actual string manipulation by the robot arm, and string parameter estimation from the actual string movement. After repeating these three steps, the simulated string movement approximates the actual to realize casting manipulation with the unknown string. We confirmed the effectiveness of the proposed method through experiments. The try of this study will lead to enhancement of the performance of home service robot, exploration robot, rescue robot and entertainment robot.