Papers
Research papers from arXiv and related sources
From Labor to Collaboration: A Methodological Experiment Using AI Agents to Augment Research Perspectives in Taiwan's Humanities and Social Sciences
Generative AI is reshaping knowledge work, yet existing research focuses predominantly on software engineering and the natural sciences, with limited methodological exploration for the humanities a...
Yi-Chih Huang
NotebookRAG: Retrieving Multiple Notebooks to Augment the Generation of EDA Notebooks for Crowd-Wisdom
High-quality exploratory data analysis (EDA) is essential in the data science pipeline, but remains highly dependent on analysts' expertise and effort. While recent LLM-based approaches partially r...
Yi Shan, Yixuan He, Zekai Shao, Kai Xu, Siming Chen
Extending quantum theory with AI-assisted deterministic game theory
We present an AI-assisted framework for predicting individual runs of complex quantum experiments, including contextuality and causality (adaptive measurements), within our long-term programme of d...
Florian Pauschitz, Ben Moseley, Ghislain Fourny
Algorithmic Collusion at Test Time: A Meta-game Design and Evaluation
The threat of algorithmic collusion, and whether it merits regulatory intervention, remains debated, as existing evaluations of its emergence often rely on long learning horizons, assumptions about...
Yuhong Luo, Daniel Schoepflin, Xintong Wang
The Case for HTML First Web Development
Since its introduction in the early 90s, the web has become the largest application platform available globally. HyperText Markup Language (HTML) has been an essential part of the web since the beg...
Juho Vepsäläinen
Kolmogorov analysis of pulsar TOA
The Kolmogorov stochasticity parameter (KSP) as a sensitive descriptor of degree of randomness of signals is used to analyze the properties of the NANOGrav pulsar timing data associated to a stocha...
N. Galikyan, A. A. Kocharyan, V. G. Gurzadyan
Robustness and Reasoning Fidelity of Large Language Models in Long-Context Code Question Answering
Large language models (LLMs) increasingly assist software engineering tasks that require reasoning over long code contexts, yet their robustness under varying input conditions remains unclear. We c...
Kishan Maharaj, Nandakishore Menon, Ashita Saxena, Srikanth Tamilselvam
When LLM Judges Inflate Scores: Exploring Overrating in Relevance Assessment
Human relevance assessment is time-consuming and cognitively intensive, limiting the scalability of Information Retrieval evaluation. This has led to growing interest in using large language models...
Chuting Yu, Hang Li, Joel Mackenzie, Teerapong Leelanupab
SimulatorCoder: DNN Accelerator Simulator Code Generation and Optimization via Large Language Models
This paper presents SimulatorCoder, an agent powered by large language models (LLMs), designed to generate and optimize deep neural network (DNN) accelerator simulators based on natural language de...
Yuhuan Xia, Tun Li, Hongji Zhou, Xianfa Zhou, Chong Chen, Ruiyu Zhang
Powering Up Zeroth-Order Training via Subspace Gradient Orthogonalization
Zeroth-order (ZO) optimization provides a gradient-free alternative to first-order (FO) methods by estimating gradients via finite differences of function evaluations, and has recently emerged as a...
Yicheng Lang, Changsheng Wang, Yihua Zhang, Mingyi Hong, Zheng Zhang, Wotao Yin, Sijia Liu
Integrable cellular automata on finite fields of order $2^n$
This paper explores cellular automata (CA) constructed from Yang-Baxter maps over finite fields $F_{2^n}$. We define $R$-matrices using a map $f$ on $F_{2^n}$ and establish necessary and sufficient...
Aoi Araoka, Tetsuji Tokihiro
Generating Rely-Guarantee Conditions with the Conditional-Writes Domain
Abstract interpretation has been shown to be a promising technique for the thread-modular verification of concurrent programs. Central to this is the generation of interferences, in the form of rel...
James Tobler, Graeme Smith
Graphene FET Process and Analysis Optimization in 200 mm Pilot Line Environment
The maturity of the chemical vapor deposition graphene-based device processing has increased from chip level demonstrations to wafer-scale fabrication in the past few years. Due to this wafer-scale...
Anton Murros, Miika Soikkeli, Anni Virta, Arantxa Maestre, Leire Morillo, Alba Centeno, Amaia Zur...
Breit corrections to moderately charged ions in all-orders calculations
The atomic properties of heavy, moderately-charged ions are important for a wide variety of applications, including precision tests of fundamental physics and for the study and development of atomi...
Andoni Skoufris, Benjamin M. Roberts
The Emergence of Lab-Driven Alignment Signatures: A Psychometric Framework for Auditing Latent Bias and Compounding Risk in Generative AI
As Large Language Models (LLMs) transition from standalone chat interfaces to foundational reasoning layers in multi-agent systems and recursive evaluation loops (LLM-as-a-judge), the detection of ...
Dusan Bosnjakovic
3D Scene Rendering with Multimodal Gaussian Splatting
3D scene reconstruction and rendering are core tasks in computer vision, with applications spanning industrial monitoring, robotics, and autonomous driving. Recent advances in 3D Gaussian Splatting...
Chi-Shiang Gau, Konstantinos D. Polyzos, Athanasios Bacharis, Saketh Madhuvarasu, Tara Javidi
TIFO: Time-Invariant Frequency Operator for Stationarity-Aware Representation Learning in Time Series
Nonstationary time series forecasting suffers from the distribution shift issue due to the different distributions that produce the training and test data. Existing methods attempt to alleviate the...
Xihao Piao, Zheng Chen, Lingwei Zhu, Yushun Dong, Yasuko Matsubara, Yasushi Sakurai
Epistemology of Generative AI: The Geometry of Knowing
Generative AI presents an unprecedented challenge to our understanding of knowledge and its production. Unlike previous technological transformations, where engineering understanding preceded or ac...
Ilya Levin
Projective Psychological Assessment of Large Multimodal Models Using Thematic Apperception Tests
Thematic Apperception Test (TAT) is a psychometrically grounded, multidimensional assessment framework that systematically differentiates between cognitive-representational and affective-relational...
Anton Dzega, Aviad Elyashar, Ortal Slobodin, Odeya Cohen, Rami Puzis
Toward Trustworthy Evaluation of Sustainability Rating Methodologies: A Human-AI Collaborative Framework for Benchmark Dataset Construction
Sustainability or ESG rating agencies use company disclosures and external data to produce scores or ratings that assess the environmental, social, and governance performance of a company. However,...
Xiaoran Cai, Wang Yang, Xiyu Ren, Chekun Law, Rohit Sharma, Peng Qi