Papers
Research papers from arXiv and related sources
Superintegrability and choreographic obstructions in dihedral $n$-body Hamiltonian systems
In this study $n$-body systems on the plane, invariant under the dihedral group $D_n$, with quadratic pairwise interactions are considered. In the center-of-mass frame the dynamics separates into F...
Adrian M Escobar-Ruiz, Manuel Fernandez-Guasti
In-Context Learning for Pure Exploration in Continuous Spaces
In active sequential testing, also termed pure exploration, a learner is tasked with the goal to adaptively acquire information so as to identify an unknown ground-truth hypothesis with as few quer...
Alessio Russo, Yin-Ching Lee, Ryan Welch, Aldo Pacchiano
Generating adversarial inputs for a graph neural network model of AC power flow
This work formulates and solves optimization problems to generate input points that yield high errors between a neural network's predicted AC power flow solution and solutions to the AC power flow ...
Robert Parker
Minimax optimal adaptive structured transfer learning through semi-parametric domain-varying coefficient model
Transfer learning aims to improve inference in a target domain by leveraging information from related source domains, but its effectiveness critically depends on how cross-domain heterogeneity is m...
Hanxiao Chen, Debarghya Mukherjee
Mining Type Constructs Using Patterns in AI-Generated Code
Artificial Intelligence (AI) increasingly automates various parts of the software development tasks. Although AI has enhanced the productivity of development tasks, it remains unstudied whether AI ...
Imgyeong Lee, Tayyib Ul Hassan, Abram Hindle
CUICurate: A GraphRAG-based Framework for Automated Clinical Concept Curation for NLP applications
Background: Clinical named entity recognition tools commonly map free text to Unified Medical Language System (UMLS) Concept Unique Identifiers (CUIs). For many downstream tasks, however, the clini...
Victoria Blake, Mathew Miller, Jamie Novak, Sze-yuan Ooi, Blanca Gallego
A Geometric Probe of the Accuracy-Robustness Trade-off: Sharp Boundaries in Symmetry-Breaking Dimensional Expansion
The trade-off between clean accuracy and adversarial robustness is a pervasive phenomenon in deep learning, yet its geometric origin remains elusive. In this work, we utilize Symmetry-Breaking Dime...
Yu Bai, Zhe Wang, Jiarui Zhang, Dong-Xiao Zhang, Yinjun Gao, Jun-Jie Zhang
Optimizing Graph Causal Classification Models: Estimating Causal Effects and Addressing Confounders
Graph data is becoming increasingly prevalent due to the growing demand for relational insights in AI across various domains. Organizations regularly use graph data to solve complex problems involv...
Simi Job, Xiaohui Tao, Taotao Cai, Haoran Xie, Jianming Yong, Xin Wang
Analyzing LLM Instruction Optimization for Tabular Fact Verification
Instruction optimization provides a lightweight, model-agnostic approach to enhancing the reasoning performance of large language models (LLMs). This paper presents the first systematic comparison ...
Xiaotang Du, Giwon Hong, Wai-Chung Kwan, Rohit Saxena, Ivan Titov, Pasquale Minervini, Emily Allaway
Operational Agency: A Permeable Legal Fiction for Tracing Culpability in AI Systems
Modern artificial intelligence (AI) systems act with a high degree of independence yet lack legal personhood-a paradox that fractures doctrines grounded in human-centric notions of mens rea and act...
Anirban Mukherjee, Hannah Hanwen Chang
Memory-Based Advantage Shaping for LLM-Guided Reinforcement Learning
In environments with sparse or delayed rewards, reinforcement learning (RL) incurs high sample complexity due to the large number of interactions needed for learning. This limitation has motivated ...
Narjes Nourzad, Carlee Joe-Wong
MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance
Reinforcement learning (RL) agents often suffer from high sample complexity in sparse or delayed reward settings due to limited prior structure. Large language models (LLMs) can provide subgoal dec...
Narjes Nourzad, Carlee Joe-Wong
Visual Anthropomorphism Shifts Evaluations of Gendered AI Managers
This research examines whether competence cues can reduce gender bias in evaluations of AI managers and whether these effects depend on how the AI is represented. Across two preregistered experimen...
Ruiqing Han, Hao Cui, Taha Yasseri
Alignment in Time: Peak-Aware Orchestration for Long-Horizon Agentic Systems
Traditional AI alignment primarily focuses on individual model outputs; however, autonomous agents in long-horizon workflows require sustained reliability across entire interaction trajectories. We...
Hanjing Shi, Dominic DiFranzo
El Agente Gráfico: Structured Execution Graphs for Scientific Agents
Large language models (LLMs) are increasingly used to automate scientific workflows, yet their integration with heterogeneous computational tools remains ad hoc and fragile. Current agentic approac...
Jiaru Bai, Abdulrahman Aldossary, Thomas Swanick, Marcel Müller, Yeonghun Kang, Zijian Zhang, Jin...
Symfrog-512: High-Capacity Sponge-Based AEAD Cipher (1024-bit State)
This submission includes a complete reference implementation together with deterministic test vectors and a reproducible benchmark suite. All source code, build instructions, and regression artifac...
Victor Duarte Melo
The Strategic Gap: How AI-Driven Timing and Complexity Shape Investor Trust in the Age of Digital Agents
Traditional models of market efficiency assume that equity prices incorporate information based on content alone, often neglecting the structural influence of reporting timing and cadence. This stu...
Krishna Neupane
HookLens: Visual Analytics for Understanding React Hooks Structures
Maintaining and refactoring React web applications is challenging, as React code often becomes complex due to its core API called Hooks. For example, Hooks often lead developers to create complex d...
Suyeon Hwang, Minkyu Kweon, Jeongmin Rhee, Soohyun Lee, Seokhyeon Park, Seokweon Jung, Hyeon Jeon...
The Information Dynamics of Insider Intent: How Reporting Inversions (Form 144) Mask Informational Rents in Insider Sales (Form 4)
This study identifies and quantifies a significant informational friction embedded in the SEC Form 144 disclosure regime, characterized as predictive decoupling. Drawing on a theoretical foundation...
Krishna Neupane
Machine Learning Based Prediction of Surgical Outcomes in Chronic Rhinosinusitis from Clinical Data
Artificial intelligence (AI) has increasingly transformed medical prognostics by enabling rapid and accurate analysis across imaging and pathology. However, the investigation of machine learning pr...
Sayeed Shafayet Chowdhury, Karen D'Souza, V. Siva Kakumani, Snehasis Mukhopadhyay, Shiaofen Fang,...