Papers
Research papers from arXiv and related sources
A Context Alignment Pre-processor for Enhancing the Coherence of Human-LLM Dialog
Large language models (LLMs) have made remarkable progress in generating fluent text, but they still face a critical challenge of contextual misalignment in long-term and dynamic dialogue. When hum...
Ding Wei
An immersed peridynamics method for fluid-driven damage and failure of anisotropic materials
The immersed peridynamics (IPD) method is a fluid-structure interaction (FSI) model to simulate fluid-driven material damage and failure of an immersed structure, in which a peridynamic (PD) consti...
Keon Ho Kim, Boyce E. Griffith
Power Analysis for Prediction-Powered Inference
Modern studies increasingly leverage outcomes predicted by machine learning and artificial intelligence (AI/ML) models, and recent work, such as prediction-powered inference (PPI), has developed va...
Yiqun T. Chen, Moran Guo, Shengy Li
Compact Optical Single-axis Joint Torque Sensor Using Redundant Photo-Reflectors and Quadratic-Programming Calibration
This study proposes a non-contact photo-reflector-based joint torque sensor for precise joint-level torque control and safe physical interaction. Current-sensor-based torque estimation in many coll...
Hyun-Bin Kim, Byeong-Il Ham, Kyung-Soo Kim
Identification Verification for Structural Vector Autoregressions with Sparse Heterogeneous Markov Switching Heteroskedasticity
We propose a structural vector autoregressive model with a new and flexible specification of the volatility process which we call Sparse Heterogeneous Markov-Switching Heteroskedasticity. In this m...
Fei Shang, Tomasz Woźniak
Geometry-Aligned LLM Fine-Tuning for Sequential Narrow-Opening Planning
We study rigid-body motion planning through multiple sequential narrow openings, which requires long-horizon geometric reasoning because the configuration used to traverse an early opening constrai...
Al Jaber Mahmud, Xuan Wang
Ringdown bounds and spectral density limits from GWTC-3
We establish the first observational bounds on causal nonlocal extensions of gravity characterized by retarded Stieltjes-type kernels with positive spectral density rho(mu) >= 0, using two compleme...
Christian Balfagon
Making Software Metrics Useful
Most engineers use measurements to make decisions. However, measurements are rarely used for decisions about constructing software products. While many approaches to measuring attributes of softwar...
Ewan Tempero, Paul Ralph
A minimal fractional deformation of Newtonian gravity
We consider a minimal fractional deformation of Newtonian gravity characterized by a single parameter $α$. In the limit $α\to 1$, the theory reduces to standard Newtonian gravity. Previous works sh...
S. M. M. Rasouli
Emulation of SPHEREx Galaxy Power Spectra I: Neural Network Details and Optimization
We present neural networks to generate redshift-space galaxy power spectrum multipoles for multiple tracer and redshift bins simultaneously given a set of input cosmology and galaxy bias parameters...
Joseph Adamo, Grace Gibbins, Anne Moore, Tim Eifler
NLP Occupational Emergence Analysis: How Occupations Form and Evolve in Real Time -- A Zero-Assumption Method Demonstrated on AI in the US Technology Workforce, 2022-2026
Occupations form and evolve faster than classification systems can track. We propose that a genuine occupation is a self-reinforcing structure (a bipartite co-attractor) in which a shared professio...
David Nordfors
Physics-Constrained Neural Closure for Lattice Boltzmann Large-Eddy Simulation
We present a physics-constrained, data-driven subgrid-scale (SGS) stress closure for large-eddy simulation (LES) in the lattice Boltzmann method (LBM). Trained on filtered-downsampled (FD) data fro...
Muhammad Idrees Khan, Sauro Succi, Hua-Dong Yao, Giacomo Falcucci
Something from Nothing: Data Augmentation for Robust Severity Level Estimation of Dysarthric Speech
Dysarthric speech quality assessment (DSQA) is critical for clinical diagnostics and inclusive speech technologies. However, subjective evaluation is costly and difficult to scale, and the scarcity...
Jaesung Bae, Xiuwen Zheng, Minje Kim, Chang D. Yoo, Mark Hasegawa-Johnson
An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc
While large language models have significantly accelerated scientific code generation, comprehensively evaluating the generated code remains a major challenge. Traditional benchmarks reduce evaluat...
Hong Zhang, Barry Smith, Satish Balay, Le Chen, Murat Keceli, Lois Curfman McInnes, Junchao Zhang
A Comprehensive Benchmark of Histopathology Foundation Models for Kidney Histopathology
Histopathology foundation models (HFMs), pretrained on large-scale cancer datasets, have advanced computational pathology. However, their applicability to non-cancerous chronic kidney disease remai...
Harishwar Reddy Kasireddy, Patricio S. La Rosa, Akshita Gupta, Anindya S. Paul, Jamie L. Fermin, ...
Optimizing Hospital Capacity During Pandemics: A Dual-Component Framework for Strategic Patient Relocation
The COVID-19 pandemic has placed immense strain on hospital systems worldwide, leading to critical capacity challenges. This research proposes a two-part framework to optimize hospital capacity thr...
Sadaf Tabatabaee, Hicham El Baz, Mohammed Khalil Ghali, Nagendra N. Nagarur
POLAR:A Per-User Association Test in Embedding Space
Most intrinsic association probes operate at the word, sentence, or corpus level, obscuring author-level variation. We present POLAR (Per-user On-axis Lexical Association Re-port), a per-user lexic...
Pedro Bento, Arthur Buzelin, Arthur Chagas, Yan Aquino, Victoria Estanislau, Samira Malaquias, Pe...
Evaluating Performance Characteristic of Opportunistic Routing Protocols: A Case Study of the 2016 Italian League Match Earthquake in the Stadio Adriatico
Delay Tolerant Networks (DTNs) can provide emergency communication support when conventional infrastructure is disrupted during disasters. This paper evaluates the performance of opportunistic rout...
Yihang Cao, Milena Radenkovic
Saddle Point Evasion via Curvature-Regularized Gradient Dynamics
Nonconvex optimization underlies many modern machine learning and control tasks, where saddle points pose the dominant obstacle to reliable convergence in high-dimensional settings. Escaping these ...
Liraz Mudrik, Isaac Kaminer, Sean Kragelund, Abram H. Clark
QCD-driven dark matter: AQNs formation and observational tests
The nature of dark energy remains a central problem in cosmology. A compelling possibility is that dark matter is macroscopic, consisting of composite objects formed in the early Universe. We intro...
Ludovic Van Waerbeke