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๐Ÿ” will yeadon ๐Ÿ“‚ Computer Science
Showing 69082 results for "will yeadon" in Computer Science
Computer Science Preprint PDF DOI

Efficient Multivector Retrieval with Token-Aware Clustering and Hierarchical Indexing

Silvio Martinico, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini ยท 2026

Multivector retrieval models achieve state-of-the-art effectiveness through fine-grained token-level representations, but their deployment incurs substantial computational and memory costs. Current soโ€ฆ

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Beyond Code, We Are People: A Systematic Mapping of 25 Years of Literature on Soft Skills in Agile Development Teams

Israely Lima, Lucas Moura Lourenco, Marcio Ribeiro, Ivan Machado, Carla Ilane Bezerra ยท 2026

Software development is a sociotechnical and human-centered endeavor in which human factors directly influence quality, productivity, and innovation capacity. In this context, career development in coโ€ฆ

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Perfectly Private Over-the-Air Computation

Shudi Weng, Ming Xiao, Mikael Skoglund ยท 2026

This paper studies a key research question: how to achieve perfect privacy in over-the-air computation (AirComp)? The problem is particularly intriguing due to a dilemma. Real-field operations can ensโ€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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Exploring Sparse Matrix Multiplication Kernels on the Cerebras CS-3

Milan Shah, Sheng Di, Michela Becchi ยท 2026

In recent years, novel AI accelerators have emerged as promising alternatives to GPU for AI model training and inference tasks. One such accelerator, the Cerebras CS-3, achieves strong performance on โ€ฆ

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Distributed Santa Claus via Global Rounding

Tijn de Vos, Leo Wennmann, Malte Baumecker, Yannic Maus, Florian Schager ยท 2026

In this paper, we consider the Santa Claus problem in the CONGEST model. This NP-hard problem can be modeled as a bipartite graph of children and gifts where an edge indicates that a child desires a gโ€ฆ

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Simpler and Improved Replacement Path Coverings

Davide Bilo, Shiri Chechik, Keerti Choudhary, Sarel Cohen, Martin Schirneck ยท 2026

An important tool in the design of fault-tolerant graph data structures are $(L,f)$-replacement path coverings (RPCs). An RPC is a family $\mathcal{G}$ of subgraphs of a given graph $G$ such that, forโ€ฆ

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Can We Volunteer Out of the Peer Review Crisis?

Theo Tang, Toby Handfield, Julian Garcia ยท 2026

The volume of scientific manuscripts is growing faster than the capacity to evaluate them, yet the institutions that govern peer review have remained largely unchanged. The result is a widening mismatโ€ฆ

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Variational and Majorization Principles in Lattice Reduction

Javier Blanco-Romero, Florina Almenares Mendoza ยท 2026

Lattice reduction smooths the Gram-Schmidt profile, and we use majorization to describe the local swap mechanism behind that smoothing. In this language, each non-degenerate Lov\'asz swap acts as a T-โ€ฆ

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RuC: HDL-Agnostic Rule Completion Benchmark Generation

Arnau Ayguade Domingo, Miquel Alberti-Binimelis, Cristian Gutierrez-Gomez, Emanuele Parisi, Razine Moundir Ghorab, Miquel Moreto, Gokcen Kestor, Dario Garcia-Gasulla ยท 2026

Large Language Models (LLMs) have rapidly improved in performance across code-related tasks, making their integration into Register Transfer Level (RTL) development increasingly attractive. Mimicking โ€ฆ

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Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation

Jiaju Chen, Chongming Gao, Chenxiao Fan, Haoyan Liu, Qingpeng Cai, Peng Jiang, Xiangnan He ยท 2026

Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To accelerate inference without changing the target dโ€ฆ

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Users' Activity Logs: the Good, the Bad, the Misconception, and the Disastrous

Eman Alashwali ยท 2026

Most service providers, such as Google, save logs from data generated by users while using the service. Many service providers provide users with privacy controls to manage whether, how, and for how lโ€ฆ

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Thinking like a business: Reconfiguring relationships to sustain open data infrastructures

Kathleen Gregory, Dorothea Strecker ยท 2026

Sustaining open data infrastructures over time is a complex puzzle, involving dynamic funding models and relationships with customers, collaborators, and competitors. Despite their importance, these mโ€ฆ

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BAss: Symbolic Reasoning in Abstract Dialectical Frameworks

Samuel Pastva, Van-Giang Trinh ยท 2026

We present BAss (BDD-based ADF symbolic solver), a novel analysis tool for Abstract Dialectical Frameworks (ADFs) based on Binary Decision Diagrams (BDDs). It supports the fully symbolic computation oโ€ฆ

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I'm Fine, But My Voice Isn't: Cross-Modal Affective Dissonance Detection for Reflective Journaling

Sumin Lee ยท 2026

Digital journaling creates an authenticity gap: users consciously translate raw emotions into text, often sanitizing narratives even in private writing. We formalize this as Cross-Modal Affective Dissโ€ฆ

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SST-Guard: Detecting and Characterizing Server-Side Google Analytics in the Wild

Muhammad Jazlan, Alexander Gamero-Garrido, Zubair Shafiq, Yash Vekaria ยท 2026

As web browsers increasingly restrict client-side tracking, the web tracking ecosystem is shifting from client-side to server-side tracking (SST). In SST, the browser sends tracking requests to an intโ€ฆ

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Computing the (k+2)-Edge-Connected Components in k-Edge-Connected Digraphs in Subquadratic Time

Loukas Georgiadis, Evangelos Kipouridis, Evangelos Kosinas, Charis Papadopoulos, Nikos Parotsidis ยท 2026

Computing edge-connected components in directed and undirected graphs is a fundamental and well-studied problem in graph algorithms. In a very recent breakthrough, Korhonen [STOC 2025] showed that forโ€ฆ

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The Likelihood Ratio Wall: Structural Limits on Accurate Risk Assessment for Rare Violence

Marco Pollanen ยท 2026

Pretrial risk assessment tools are used on over one million U.S. defendants each year, yet their use for predicting rare violent re-offense faces a basic statistical barrier. We derive a universal preโ€ฆ

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A Diagrammatic Axiomatisation of Behavioural Distance of Nondeterministic Processes

Wojciech Rozowski, Robin Piedeleu, Alexandra Silva, Fabio Zanasi ยท 2026

Behavioural distances provide a quantitative approach to comparing the states of transition systems, moving beyond traditional Boolean notions of equivalence. In this paper, we develop a sound and comโ€ฆ

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Designing sparse temporal graphs satisfying connectivity requirements

Thomas Bellitto, Jules Bouton Popper, Justine Cauvi, Bruno Escoffier, Raphaelle Maistre-Matus ยท 2026

Connectivity of temporal graphs has been widely studied both as graph theory and as gossip theory. In particular, it is well known that in order to connect every vertex to every other, a temporal grapโ€ฆ

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