arXiv subjects

Yuan Si

Publications and source records attributed to Yuan Si.

28 records · Page 2Linked to original sources

arXiv2026

ScratchEval : A Multimodal Evaluation Framework for LLMs in Block-Based Programming

LLMs have achieved strong performance on text-based programming tasks, yet they remain unreliable for block-based languages such as Scratch. Scratch programs exhibit deeply nested, non-linear structures, event-driven concurrency across multiple sprites, and tight coupling between code and multimedia assets, properties that differ fundamentally from textual code. As a result, LLMs often misinterpret Scratch semantics and generate large, invasive edits that are syntactically valid but semantically incorrect when repairing buggy programs. We introduce ScratchEval, the first executable benchmark designed to evaluate LLM-based repair for Scratch programs, covering program understanding, debugging, analysis, and repair. The benchmark contains 100 curated Scratch projects from the public repository, selected for structural and semantic complexity. Each project is paired with executable test suites, bug descriptions with corresponding fixes, block-level edit constraints defining minimal semantically correct repairs, and required multimedia assets. The benchmark is constructed through a human-in-the-loop pipeline combining automated project mining with expert validation of trigger-outcome semantics and representative bug patterns, with emphasis on event ordering, concurrency, and state management. To enable rigorous and reproducible evaluation, we propose a three-layer executable protocol measuring functional correctness via VM-level execution, repair quality using block-level edit distance and behavioral trajectory comparisons, and explanation quality via structured rubrics assessing alignment between model reasoning and generated patches. Using ScratchEval, we study domain-specific fine-tuning, training data effectiveness, and model generalization to unseen bug types. ScratchEval provides a reproducible foundation for evaluating and post-training LLMs on block-based programming tasks.

cs.SE↗

arXiv2025

Stitch: Step-by-step LLM Guided Tutoring for Scratch

Block-based environments such as Scratch are increasingly popular in programming education. While block syntax reduces surface errors, semantic bugs remain common and challenging for novices to resolve. Existing debugging workflows typically show the correct program directly to learners, a strategy that may fix errors but undermines the development of problem-solving skills. We present Stitch, an interactive tutoring system that replaces "showing the answer" with step-by-step scaffolding. The system's Diff-Analyze module contrasts a student's project with a reference implementation, identifies the most critical differences, and uses a large language model to explain why these changes matter. Learners inspect highlighted blocks through a custom rendering engine, understand the explanations, and selectively apply partial fixes. This iterative process continues until the intended functionality is achieved. We evaluate Stitch in an empirical study, comparing it against a state-of-the-art automated feedback generation tool for Scratch. Our key insight is that simply presenting the correct program is pedagogically ineffective. In contrast, our interactive, step-by-step guided system promotes a more effective learning experience. More broadly, what constitutes effective feedback in block-based programming remains an open question. Our evaluation provides new evidence that step-by-step tutoring significantly enhances learning outcomes, outperforming both direct-answer approaches and current automated feedback generation tools.

cs.SE↗

arXiv2025

ViScratch: Using Large Language Models and Gameplay Videos for Automated Feedback in Scratch

Block-based programming environments such as Scratch are increasingly popular in programming education, in particular for young learners. While the use of blocks helps prevent syntax errors, semantic bugs remain common and difficult to debug. Existing tools for Scratch debugging rely heavily on predefined rules or user manual inputs, and crucially, they ignore the platform's inherently visual nature. We introduce ViScratch, the first multimodal feedback generation system for Scratch that leverages both the project's block code and its generated gameplay video to diagnose and repair bugs. ViScratch uses a two-stage pipeline: a vision-language model first aligns visual symptoms with code structure to identify a single critical issue, then proposes minimal, abstract syntax tree level repairs that are verified via execution in the Scratch virtual machine. We evaluate ViScratch on a set of real-world Scratch projects against state-of-the-art LLM-based tools and human testers. Results show that gameplay video is a crucial debugging signal: ViScratch substantially outperforms prior tools in both bug identification and repair quality, even without access to project descriptions or goals. This work demonstrates that video can serve as a first-class specification in visual programming environments, opening new directions for LLM-based debugging beyond symbolic code alone.

cs.SE↗

arXiv2025

Revealing the evanescent components in Kronecker-product based codebooks: insights and implications

The orthogonal bases of discrete Fourier transform (DFT) has been recognized as the standard spatial-domain bases for Type I, Type II and enhanced Type II codewords by the 3rd Generation Partnership Project (3GPP). For uniform planar arrays, these spatial-domain bases are derived as the Kronecker product of one-dimensional DFT bases. Theoretically, each spatial basis corresponds to a beam directed towards a specific angle of departure and the set of bases represent the orthogonal beams that cover the front hemisphere of an array. While the Kronecker-product based precoding scheme facilitates the concise indexing of a codeword in the codebooks through precoding matrix indicators (PMIs) in channel state information feedback, it introduces redundant spatial beams characterized by high spatial-frequency components. This paper investigates the presence of codewords representing high spatial-frequency components within the Kronecker-product based codebooks. Through theoretical analysis and simulations, we confirm the redundancy of these codewords in MIMO communications, advocating for their removal from the codebooks to enhance system performance. Several topics relevant to the high spatial components are also involved in the discussion. Practical suggestions regarding future standard design are provided based on our theoretical analysis and simulation results.

cs.IT↗

arXiv2025

Bridging BCI and Communications: A MIMO Framework for EEG-to-ECoG Wireless Channel Modeling

As a method to connect human brain and external devices, Brain-computer interfaces (BCIs) are receiving extensive research attention. Recently, the integration of communication theory with BCI has emerged as a popular trend, offering potential to enhance system performance and shape next-generation communications. A key challenge in this field is modeling the brain wireless communication channel between intracranial electrocorticography (ECoG) emitting neurons and extracranial electroencephalography (EEG) receiving electrodes. However, the complex physiology of brain challenges the application of traditional channel modeling methods, leaving relevant research in its infancy. To address this gap, we propose a frequency-division multiple-input multiple-output (MIMO) estimation framework leveraging simultaneous macaque EEG and ECoG recordings, while employing neurophysiology-informed regularization to suppress noise interference. This approach reveals profound similarities between neural signal propagation and multi-antenna communication systems. Experimental results show improved estimation accuracy over conventional methods while highlighting a trade-off between frequency resolution and temporal stability determined by signal duration. This work establish a conceptual bridge between neural interfacing and communication theory, accelerating synergistic developments in both fields.

eess.SP↗

arXiv2024

Patterned Beam Training: A Novel Low-Complexity and Low-Overhead Scheme for ELAA

Extremely large antenna arrays (ELAAs) can provide higher spectral efficiency. However, the use of narrower beams for data transmission significantly increases the overhead associated with beam training. In this letter, we propose a novel patterned beam training (PBT) scheme characterized by its low overhead and complexity. This scheme requires only a single linear operation by both the base station and the user equipment to determine the optimal beam, reducing the training overhead to half or even less compared to traditional exhaustive search methods. Furthermore, We discuss the pattern design principles in detail and provide specific forms. Simulation results demonstrate that the proposed scheme outperforms the compared methods in terms of beam alignment accuracy and achieves a balance between signal-to-noise ratio (SNR) conditions and training overhead, making it a promising alternative.

eess.SP↗

arXiv2024

Rainbow and Gallai-Rado numbers involving binary function equations

Let $\mathcal{E}$, $\mathcal{E}_1$, and $\mathcal{E}_2$ be equations, $n$ and $k$ be positive integers. The rainbow number $\operatorname{rb}([n],\mathcal{E})$ is difined as the minimum number of colors such that for every exact $(\operatorname{rb}([n],\mathcal{E}))$-coloring of $[n]$, there exists a rainbow solution of $\mathcal{E}$. The Gallai-Rado number $\operatorname{GR}_k(\mathcal{E}_1:\mathcal{E}_2)$ is defined as the minimum positive integer $N$, if it exists, such that for all $n\ge N$, every $k$-colored $[n]$ contains either a rainbow solution of $\mathcal{E}_1$ or a monochromatic solution of $\mathcal{E}_2$. In this paper, we get some exact values of rainbow and Gallai-Rado numbers involving binary function equations. We also provide an algorithm to calculate the rainbow numbers of nonlinear binary function equations.

math.CO↗

arXiv2024

Fast Beam Training and Performance Analysis for Extremely Large Aperture Array

Extremely large aperture array (ELAA) can significantly enhance beamforming gain and spectral efficiency. Unfortunately, the use of narrower beams for data transmission results in a substantial increase in the cost of beam training. In this paper, we study a high-efficiency and low-overhead scheme named hash beam training. Specifically, two improved hash codebook design methods, random and fixed, are proposed. Moreover, we analyze beam alignment performance. Since the derived beam alignment success probability is a complex function, we also propose a heuristic metric to evaluate the impact of codebook parameter on performance. Finally, simulation results validate the theoretical analysis, indicating that the proposed beam training scheme can achieve fast beam alignment with lower overhead and higher accuracy.

eess.SP↗

arXiv2024

Gallai-Ramsey multiplicity for rainbow small trees

Let $G, H$ be two non-empty graphs and $k$ be a positive integer. The Gallai-Ramsey number $\operatorname{gr}_k(G:H)$ is defined as the minimum positive integer $N$ such that for all $n\geq N$, every $k$-edge-coloring of $K_n$ contains either a rainbow subgraph $G$ or a monochromatic subgraph $H$. The Gallai-Ramsey multiplicity $\operatorname{GM}_k(G:H)$ is defined as the minimum total number of rainbow subgraphs $G$ and monochromatic subgraphs $H$ for all $k$-edge-colored $K_{\operatorname{gr}_k(G:H)}$. In this paper, we get some exact values of the Gallai-Ramsey multiplicity for rainbow small trees versus general monochromatic graphs under a sufficiently large number of colors. We also study the bipartite Gallai-Ramsey multiplicity.

math.CO↗

arXiv2022

Symmetry-breaking-induced multifunctionalities of two-dimensional chromium-based materials for nanoelectronics and clean energy conversion

Structural symmetry-breaking that could lead to exotic physical properties plays a crucial role in determining the functions of a system, especially for two-dimensional (2D) materials. Here we demonstrate that multiple functionalities of 2D chromium-based materials could be achieved by breaking inversion symmetry via replacing Y atoms in one face of pristine CrY (Y=P, As, Sb) monolayers with N atoms, i.e., forming Janus Cr2NY monolayers. The functionalities include spin-gapless, very low work function, inducing carrier doping and catalytic activity, which are predominately ascribed to the large intrinsic dipole of Janus Cr2NY monolayers, making them having great potentials in various applications. Specifically, Cr2NSb is found to be a spin-gapless semiconductor, Cr2NP and Cr2NHPF could simultaneously induce n- and p-type carrier doping for two graphene sheets with different concentrations (forming intrinsic p-n vertical junction), and Cr2NY exhibits excellent electrocatalytic hydrogen evolution activity, even superior to benchmark Pt. The results confirm that breaking symmetry is a promising approach for the rational design of multifunctional 2D materials.

physics.comp-ph↗