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๐Ÿ” ning li ๐Ÿ“‚ Computer Science
Showing 3915 results for "ning li" in Computer Science
Computer Science Preprint PDF DOI

DEFault++: Automated Fault Detection, Categorization, and Diagnosis for Transformer Architectures

Sigma Jahan, Saurabh Singh Rajput, Tushar Sharma, Mohammad Masudur Rahman ยท 2026

Transformer models are widely deployed in critical AI applications, yet faults in their attention mechanisms, projections, and other internal components often degrade behavior silently without raisingโ€ฆ

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NeuroRing: Scaling Spiking Neural Networks via Multi-FPGA Bidirectional Ring Topologies and Stream-Dataflow Architectures

Muhammad Ihsan Al Hafiz, Artur Podobas ยท 2026

Spiking neural networks (SNNs) are a promising paradigm for energy-efficient event-driven computation, but large-scale SNN execution remains challenging because sparse spike communication and synchronโ€ฆ

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On Higher-Order Probabilistic Verification via the Weighted Relational Model of Linear Logic

Ugo Dal Lago, Guido Fiorillo, Paolo Pistone ยท 2026

The problem of determining whether a probabilistic program terminates almost surely (i.e.~with probability one) is undecidable, and actually $\Pi^0_2$-complete. For this reason, a growing literature hโ€ฆ

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A Reproducibility Study of LLM-Based Query Reformulation

Amin Bigdeli, Radin Hamidi Rad, Hai Son Le, Mert Incesu, Negar Arabzadeh, Charles L. A. Clarke, Ebrahim Bagheri ยท 2026

Large Language Models (LLMs) are now widely used for query reformulation and expansion in Information Retrieval, with many studies reporting substantial effectiveness gains. However, these results areโ€ฆ

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Artistic Practice Opportunities in CST Evaluations: A Longitudinal Group Deployment of ArtKrit

Catherine Liu, Tao Long, Asya Vaisberg, Chau Vu, Jiaju Ma, Jingyi Li ยท 2026

Creativity support tools (CSTs) aim to elevate the quality of artists' creative processes and artifacts. Yet most current CST evaluations overlook temporal and social aspects of tool use. To address tโ€ฆ

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Hot Fixing in the Wild

Carol Hanna, Karine Even-Mendoza, W.B. Langdon, Mar Zamorano Lopez, Justyna Petke, Federica Sarro ยท 2026

Despite the operational importance of hot fixes, large-scale evidence on how they reshape routine maintenance workflows, particularly in the era of autonomous coding agents, remains limited. We analysโ€ฆ

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Resume-ing Control: (Mis)Perceptions of Agency Around GenAI Use in Recruiting Workflows

Sajel Surati, Rosanna Bellini, Emily Black ยท 2026

When generative AI (genAI) systems are used in high-stakes decision-making, its recommended role is to aid, rather than replace, human decision-making. However, there is little empirical exploration oโ€ฆ

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UIGaze: How Closely Can VLMs Approximate Human Visual Attention on User Interfaces?

Min Song, Yoonseong Lee, Yeonhu Seo ยท 2026

Vision Language Models (VLMs) have demonstrated strong capabilities in understanding visual content, yet their ability to predict where humans look on user interfaces remains unexplored. We present UIโ€ฆ

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New Convex Programming Technique for Nash Social Welfare and Scheduling

Yuda Feng, Weijiang Hu, Shi Li ยท 2026

We propose a new convex programming relaxation for the weighted Nash social welfare (NSW) problem that achieves a matching $(e^{1/e}\approx 1.445)$-approximation via the rounding algorithm of Feng andโ€ฆ

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Constructive Separations from Gate Elimination

Marco Carmosino, Ngu Dang, Tim Jackman ยท 2026

Gate elimination is the primary technique for proving explicit lower bounds against general Boolean circuits, including Li and Yang's state-of-the-art $3.1n - o(n)$ bound for affine dispersers (STOC 2โ€ฆ

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SMSI: System Model Security Inference: Automated Threat Modeling for Cyber-Physical Systems

RoYah Radaideh, Ali Khreis ยท 2026

Threat modeling for cyber-physical systems (CPS) remains a largely manual exercise. This project presents SMSI (System Model Security Inference), a hybrid neuro-symbolic pipeline that starts from a Syโ€ฆ

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Evaluation of Prompt Injection Defenses in Large Language Models

Priyal Deep, Shane Emmons, Amy Fox, Kyle Bacon, Kelley McAllister, Krisztian Flautner ยท 2026

LLM-powered applications routinely embed secrets in system prompts, yet models can be tricked into revealing them. We built an adaptive attacker that evolves its strategies over hundreds of rounds andโ€ฆ

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StateScribe: Towards Accessible Change Awareness Across Real-World Revisits

Ruei-Che Chang, Xirui Jiang, Rosiana Natalie, Hao Chen, Vlad Roznyatovskiy, Jianzhong Zhang, Kang G. Shin, Ke Sun, Anhong Guo ยท 2026

Real-world environments evolve continuously, yet blind and low-vision (BLV) individuals often have limited access to understanding how they change over time. Unexpected or relocated objects, layout moโ€ฆ

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Automated Classification of Human Code Review Comments with Large Language Models

Semih Caglar, Sukru Eren Gok{i}rmak, Eray Tuzun ยท 2026

Context: Code reviews are essential for maintaining software quality, yet many human review comments suffer from issues such as redundancy, vagueness, or lack of constructiveness. These types of commeโ€ฆ

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On the Minimum Distances of Some Families of BCH Codes

Yaqi Chen, Hao Chen, Cunsheng Ding, Huimin Lao ยท 2026

BCH codes form an important class of cyclic codes, which have applications in communication and data storage systems. Although the BCH bound provides a lower bound on the minimum distance of BCH codesโ€ฆ

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Evaluating Jailbreaking Vulnerabilities in LLMs Deployed as Assistants for Smart Grid Operations: A Benchmark Against NERC Standards

Taha Hammadia, Lucas Rea, Ahmad Mohammad Saber, Amr Youssef, Deepa Kundur ยท 2026

The deployment of Large Language Models (LLMs) as assistants in electric grid operations promises to streamline compliance and decision-making but exposes new vulnerabilities to prompt-based adversariโ€ฆ

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Adopting State-of-the-Art Pretrained Audio Representations for Music Recommender Systems

Yan-Martin Tamm, Anna Aljanaki ยท 2026

Over the years, Music Information Retrieval (MIR) research community has released various models pretrained on large amounts of music data. Transfer learning showcases the proven effectiveness of pretโ€ฆ

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Rejection Sampling is Optimal for Relative Entropy Coding

Spencer Hill, Fady Alajaji, Tamas Linder, Gergely Flamich ยท 2026

In relative entropy coding, a sender aims to design a stochastic code such that, on input $X \sim P_X$, the receiver can generate a sample $Y \sim P_{Y \mid X}$. It is a standard result that (1) this โ€ฆ

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ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders

Yongqi Jiang, Yansong Gao, Boyu Kuang, Chunyi Zhou, Anmin Fu, Liquan Chen ยท 2026

Self-supervised learning (SSL) encoders are invaluable intellectual property (IP). However, no existing SSL watermarking for IP protection can concurrently satisfy the following two practical requiremโ€ฆ

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Turnstile Streaming Algorithms Might (Still) as Well Be Linear Sketches, for Polynomial-Length Streams

Cheng Jiang, Yinchen Liu, Huacheng Yu ยท 2026

A fundamental question in streaming complexity is whether every space-efficient turnstile algorithm is implicitly a linear sketch. The landmark work of Li, Nguyen, and Woodruff [LNW14] established an โ€ฆ

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