Papers
Research papers from arXiv and related sources
Learning to Tune Pure Pursuit in Autonomous Racing: Joint Lookahead and Steering-Gain Control with PPO
Pure Pursuit (PP) is widely used in autonomous racing for real-time path tracking due to its efficiency and geometric clarity, yet performance is highly sensitive to how key parameters-lookahead di...
Mohamed Elgouhary, Amr S. El-Wakeel
Ori-Sense: origami capacitive sensing for soft robotic applications
This work introduces Ori-Sense, a compliant capacitive sensor inspired by the inverted Kresling origami pattern. The device translates torsional deformation into measurable capacitance changes, ena...
Hugo de Souza Oliveira, Xin Li, Mohsen Jafarpour, Edoardo Milana
"How Do I ...?": Procedural Questions Predominate Student-LLM Chatbot Conversations
Providing scaffolding through educational chatbots built on Large Language Models (LLM) has potential risks and benefits that remain an open area of research. When students navigate impasses, they ...
Alexandra Neagu, Marcus Messer, Peter Johnson, Rhodri Nelson
Quantum Maximum Likelihood Prediction via Hilbert Space Embeddings
Recent works have proposed various explanations for the ability of modern large language models (LLMs) to perform in-context prediction. We propose an alternative conceptual viewpoint from an infor...
Sreejith Sreekumar, Nir Weinberger
Statistical Confidence in Functional Correctness: An Approach for AI Product Functional Correctness Evaluation
The quality assessment of Artificial Intelligence (AI) systems is a fundamental challenge due to their inherently probabilistic nature. Standards such as ISO/IEC 25059 provide a quality model, but ...
Wallace Albertini, Marina Condé Araújo, Júlia Condé Araújo, Antonio Pedro Santos Alves, Marcos Ka...
Qualitative Coding Analysis through Open-Source Large Language Models: A User Study and Design Recommendations
Qualitative data analysis is labor-intensive, yet the privacy risks associated with commercial Large Language Models (LLMs) often preclude their use in sensitive research. To address this, we intro...
Tung T. Ngo, Dai Nguyen Van, Anh-Minh Nguyen, Phuong-Anh Do, Anh Nguyen-Quoc
Vichara: Appellate Judgment Prediction and Explanation for the Indian Judicial System
In jurisdictions like India, where courts face an extensive backlog of cases, artificial intelligence offers transformative potential for legal judgment prediction. A critical subset of this backlo...
Pavithra PM Nair, Preethu Rose Anish
Super-Resolution Structured-Illumination X-Ray Microscopy based on Fourier Decomposition
We present a structured-illumination technique for full-field super-resolution transmission X-ray microscopy, which employs Fourier spectral decomposition inspired by established methods in visible...
Stefan Schwaiger, Lennart Forster, Martin Dierolf, Franz Pfeiffer, Benedikt Günther
Tendon-Driven Reciprocating and Non-Reciprocating Motion via Snapping Metabeams
Snapping beams enable rapid geometric transitions through nonlinear instability, offering an efficient means of generating motion in soft robotic systems. In this study, a tendon-driven mechanism c...
Mohsen Jafarpour, Ayberk Yüksek, Shahab Eshghi, Stanislav Gorb, Edoardo Milana
VeriSoftBench: Repository-Scale Formal Verification Benchmarks for Lean
Large language models have achieved striking results in interactive theorem proving, particularly in Lean. However, most benchmarks for LLM-based proof automation are drawn from mathematics in the ...
Yutong Xin, Qiaochu Chen, Greg Durrett, Işil Dillig
ReqElicitGym: An Evaluation Environment for Interview Competence in Conversational Requirements Elicitation
With the rapid improvement of LLMs' coding capabilities, the bottleneck of LLM-based automated software development is shifting from generating correct code to eliciting users' requirements. Despit...
Dongming Jin, Zhi Jin, Zheng Fang, Linyu Li, XiaoTian Yang, Yuanpeng He, Xiaohong Chen
FeatureBleed: Inferring Private Enriched Attributes From Sparsity-Optimized AI Accelerators
Backend enrichment is now widely deployed in sensitive domains such as product recommendation pipelines, healthcare, and finance, where models are trained on confidential data and retrieve private ...
Darsh Asher, Farshad Dizani, Joshua Kalyanapu, Rosario Cammarota, Aydin Aysu, Samira Mirbagher Aj...
On the Semantic and Syntactic Information Encoded in Proto-Tokens for One-Step Text Reconstruction
Autoregressive large language models (LLMs) generate text token-by-token, requiring n forward passes to produce a sequence of length n. Recent work, Exploring the Latent Capacity of LLMs for One-St...
Ivan Bondarenko, Egor Palkin, Fedor Tikunov
Analyzing and Improving Chain-of-Thought Monitorability Through Information Theory
Chain-of-thought (CoT) monitors are LLM-based systems that analyze reasoning traces to detect when outputs may exhibit attributes of interest, such as test-hacking behavior during code generation. ...
Usman Anwar, Tim Bakker, Dana Kianfar, Cristina Pinneri, Christos Louizos
Context-Aware Mapping of 2D Drawing Annotations to 3D CAD Features Using LLM-Assisted Reasoning for Manufacturing Automation
Manufacturing automation in process planning, inspection planning, and digital-thread integration depends on a unified specification that binds the geometric features of a 3D CAD model to the geome...
Muhammad Tayyab Khana, Lequn Chen, Wenhe Feng, Seung Ki Moon
GR-Athena++: Binary Neutron Star Merger Simulations with Neutrino Transport
We present general-relativistic radiation magnetohydrodynamics simulations of binary neutron star mergers performed with GR-Athena++. Neutrino transport is treated using a moment-based, energy-inte...
Boris Daszuta, Sebastiano Bernuzzi, Maximilian Jacobi, Eduardo M. Gutiérrez, Peter Hammond, Willi...
Chromaticity-Optimized Antenna Design and Bayesian Foreground Validation for the CANTAR Global 21 cm Experiment
Detecting the global 21 cm signal from the epoch of reionization remains a major observational challenge due to bright foregrounds and instrumental systematics. As part of the Colombian Antarctic T...
Michelle Mora, German Chaparro, Juan D. Guerrero, Catalina Alzate, Juan P. Urrego, Jimena Giraldo...
Two-Stage Multiple Test Procedures Controlling False Discovery Rate with auxiliary variable and their Application to Set4Delta Mutant Data
In this paper, we present novel methodologies that incorporate auxiliary variables for multiple hypotheses testing related to the main point of interest while effectively controlling the false disc...
Seohwa Hwang, Mark Louie Ramos, DoHwan Park, Junyong Park, Johan Lim, Erin Green
A Probabilistic Framework for LLM-Based Model Discovery
Automated methods for discovering mechanistic simulator models from observational data offer a promising path toward accelerating scientific progress. Such methods often take the form of agentic-st...
Stefan Wahl, Raphaela Schenk, Ali Farnoud, Jakob H. Macke, Daniel Gedon
Simplifying Outcomes of Language Model Component Analyses with ELIA
While mechanistic interpretability has developed powerful tools to analyze the internal workings of Large Language Models (LLMs), their complexity has created an accessibility gap, limiting their u...
Aaron Louis Eidt, Nils Feldhus