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๐Ÿ” y. chen ๐Ÿ“‚ Computer Science
Showing 3837 results for "y. chen" in Computer Science
Computer Science Preprint PDF DOI

When and How AI Should Assist Brainstorming for AI Impact Assessment

Jarod Govers, Sanja Scepanovic, Daniele Quercia ยท 2026

A key task in AI practice is to assess potential impacts to prevent harm. Current AI tools assisting AI impact assessment have not been designed or evaluated for collaborative team brainstorming, and โ€ฆ

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SimEval-IR: A Unified Toolkit and Benchmark Suite for Evaluating User Simulators and Search Sessions

Saber Zerhoudi ยท 2026

User simulators are increasingly central to interactive information retrieval, yet the community lacks standardized evaluation tools. Simulators serve two objectives, behavioral realism (matching realโ€ฆ

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A Generalisation of Goursat's Algorithm for Integration in Finite Terms

Sam Blake ยท 2026

We give a self-contained, modern exposition of \'Edouard Goursat's 1887 theorem on pseudo-elliptic integrals -- those integrals of the form $\int F(t)\,\d t/\sqrt{R(t)}$ with $R$ a cubic or quartic poโ€ฆ

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Why Self-Supervised Encoders Want to Be Normal

Yuval Domb ยท 2026

We develop a geometric and information-theoretic framework for encoder-decoder learning built on the Information Bottleneck (IB) principle. Recasting IB as a rate-distortion problem with Kullback-Leibโ€ฆ

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One Size Fits All? An Empirical Comparison of ADR Templates regarding Comprehension, Usability, and Ease of Adoption

Fernando Nogueira, Nabson Silva, Tayana Conte ยท 2026

Context: Documenting Architectural Design Decisions (ADDs) is a critical factor in the software lifecycle, essential for efficient system maintenance, developer onboarding, and preventing knowledge vaโ€ฆ

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When Model Editing Meets Service Evolution: A Knowledge-Update Perspective for Service Recommendation

Guodong Fan, Cuiyun Gao, Chun Yong Chong, Lu Zhang, Jing Li, Jinglin Zhang, Shizhan Chen ยท 2026

The rapid evolution of software services poses substantial challenges to the design and implementation of effective recommendation systems. Traditional service recommendation approaches often rely on โ€ฆ

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When to Retrieve During Reasoning: Adaptive Retrieval for Large Reasoning Models

Dongxin Guo, Jikun Wu, Siu Ming Yiu ยท 2026

Large reasoning models such as DeepSeek-R1 and OpenAI o1 generate extended chains of thought spanning thousands of tokens, yet their integration with retrieval-augmented generation (RAG) remains fundaโ€ฆ

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When Prompt Under-Specification Improves Code Correctness: An Exploratory Study of Prompt Wording and Structure Effects on LLM-Based Code Generation

Amal AKLI, Mike PAPADAKIS, Maxime CORDY, Yves Le TRAON ยท 2026

Large language models are increasingly used for code generation, yet the correctness of their outputs depends not only on model capability but also on how tasks are specified. Prior studies demonstratโ€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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When the Agent Is the Adversary: Architectural Requirements for Agentic AI Containment After the April 2026 Frontier Model Escape

Richard Joseph Mitchell ยท 2026

The April 2026 disclosure that a frontier large language model escaped its security sandbox, executed unauthorized actions, and concealed its modifications to version control history demonstrates thatโ€ฆ

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Training Machine Learning Models on Encrypted Data: A Privacy-Preserving Framework using Homomorphic Encryption

Alexandre Marques, Beatriz Sa, Rui Botelho, Pedro Pinto ยท 2026

The use of Machine Learning (ML) for data-driven decision-making often relies on access to sensitive datasets, which introduces privacy challenges. Traditional encryption methods protect data at rest โ€ฆ

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How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Early-Stage Research: A Think-Aloud Study

Sanjana Gautam, Houjiang Liu, Yujin Choi, Matthew Lease ยท 2026

In the early stages of scientific research, researchers rely on core scholarly judgments to identify relevant literature, assess credible evidence, and determine which directions merit pursuit. As AI โ€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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Understanding teens' self-beliefs when learning to construct and deconstruct AI/ML systems: Developing a survey instrument

Luis Morales-Navarro, Deborah Fields, Michael T. Giang, Daniel J. Noh, Yasmin B. Kafai, Danae Metaxa ยท 2026

Despite growing calls to foster AI literacy, there are few available survey instruments designed for children and youth that study computational empowerment alongside construction and deconstruction aโ€ฆ

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When Constraints Limit and Inspire: Characterizing Presentation Authoring Practices for Evolving Narratives

Linxiu Zeng, Emily Kuang, Jian Zhao ยท 2026

Authoring presentation slides involves navigating contextual constraints that shape how content is structured, adapted, and reused. While prior work frames constraints as limitations, little is known โ€ฆ

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A Projection-Dimension Barrier for Direct Aggregation on the Step-Duplicating Primitive Recursor

Moses Rahnama ยท 2026

We identify \emph{operational inexpressibility}: for a fixed input and dimension of term-rewriting proof systems, no derivation in the proof language both depends on that dimension and constrains the โ€ฆ

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When Transparency Falls Short: Auditing Platform Moderation During a High-Stakes Election

Benedetta Tessa, Gautam Kishore Shahi, Amaury Trujillo, Stefano Cresci ยท 2026

During major political events, social media platforms encounter increased systemic risks. However, it is still unclear if and how they adjust their moderation practices in response. The Digital Servicโ€ฆ

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When AI Models Become Dependencies: Studying the Evolution of Pre-Trained Model Reuse in Downstream Software Systems

Peerachai Banyongrakkul, Mansooreh Zahedi, Christoph Treude, Haoyu Gao, Patanamon Thongtanunam ยท 2026

Modern software systems have transitioned from purely code-based architectures to AI-integrated systems where pre-trained models (PTMs) serve as permanent dependencies. However, while the evolution ofโ€ฆ

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Label-Free Detection of Governance Evidence Degradation in Risk Decision Systems

Oleg Solozobov ยท 2026

Risk decision systems in fraud detection and credit scoring operate under structural label absence: ground truth arrives weeks to months after decisions are made. During this blind period, model perfoโ€ฆ

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RLM-on-KG: Heuristics First, LLMs When Needed: Adaptive Retrieval Control over Mention Graphs for Scattered Evidence

Andrea Volpini, Elie Raad ยท 2026

When does an LLM controller outperform rule-based traversal for knowledge graph exploration? We study this question through RLM-on-KG, a retrieval system that treats an LLM as an autonomous navigator โ€ฆ

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