10 citations · 14 across the 6 of their papers we have counts for
7 papers
GeoChallenge: A Multi-Answer Multiple-Choice Benchmark for Geometric Reasoning with Diagrams
Yushun Zhang, Weiping Fu, Zesheng Yang +6
Evaluating the symbolic reasoning of large language models (LLMs) calls for geometry benchmarks that require multi-step proofs grounded in both text and diagrams. However, existing…
ZX-DB: A Graph Database for Quantum Circuit Simplification and Rewriting via the ZX-Calculus
Valter Uotila, Cong Yu, Bo Zhao
Quantum computing is an emerging computational paradigm with the potential to outperform classical computers in solving a variety of problems. To achieve this, quantum programs are…
Twirlator: A Pipeline for Analyzing Subgroup Symmetry Effects in Quantum Machine Learning Ansatzes
Valter Uotila, Väinö Mehtola, Ilmo Salmenperä +1
Symmetry is a strong inductive bias in geometric deep learning and its quantum counterpart, and has attracted increasing attention for improving the trainability of QML models. Yet…
QUASAR: Quantum Assembly Code Generation Using Tool-Augmented LLMs via Agentic RL
Cong Yu, Valter Uotila, Shilong Deng +5
Designing and optimizing task-specific quantum circuits are crucial to leverage the advantage of quantum computing. Recent large language model (LLM)-based quantum circuit generati…
Higher-Order Portfolio Optimization with Quantum Approximate Optimization Algorithm
Valter Uotila, Julia Ripatti, Bo Zhao
Portfolio optimization is one of the most studied optimization problems at the intersection of quantum computing and finance. In this work, we develop the first quantum formulation…
SHARP: Shared State Reduction for Efficient Matching of Sequential Patterns
Cong Yu, Tuo Shi, Matthias Weidlich +1
The detection of sequential patterns in data is a basic functionality of modern data processing systems for complex event processing (CEP), OLAP, and retrieval-augmented generation…
Agent-Q: Fine-Tuning Large Language Models for Quantum Circuit Generation and Optimization
Linus Jern, Valter Uotila, Cong Yu +1
Large language models (LLMs) have achieved remarkable outcomes in complex problems, including math, coding, and analyzing large amounts of scientific reports. Yet, few works have e…