1 citations · 2 across the 9 of their papers we have counts for
9 papers
TIPCODER: Reinforcement Learning Boosted Test-time Instruction Proposer for Code Generation
Minyu Chen, Sihao Wu, Ling-I Wu +5
Test-time scaling for code generation typically explores the solution space by sampling multiple programs from a fixed instruction. We study a complementary direction: instance-lev…
Looped World Models
Hongyuan Adam Lu, Z. L. Victor Wei, Qun Zhang +28
Current world models face a fundamental tension: faithful long-horizon simulation demands deep computation, but deeper models are expensive to deploy and prone to compounding error…
Teacher-Aware Evolution of Heuristic Programs from Learned Optimization Policies
Minyu Chen, Song Qin, Ling-I Wu +2
LLM-based automatic heuristic design has shown promise for generating executable heuristics for combinatorial optimization, but existing methods mainly rely on delayed endpoint per…
DaSAThco: Data-Aware SAT Heuristics Combinations Optimization via Large Language Models
Minyu Chen, Guoqiang Li
The performance of Conflict-Driven Clause Learning solvers hinges on internal heuristics, yet the heterogeneity of SAT problems makes a single, universally optimal configuration un…
DCE-LLM: Dead Code Elimination with Large Language Models
Minyu Chen, Guoqiang Li, Ling-I Wu +1
Dead code introduces several challenges in software development, such as increased binary size and maintenance difficulties. It can also obscure logical errors and be exploited for…
ARCEAK: An Automated Rule Checking Framework Enhanced with Architectural Knowledge
Junyong Chen, Ling-I Wu, Minyu Chen +4
Automated Rule Checking (ARC) plays a crucial role in advancing the construction industry by addressing the laborious, inconsistent, and error-prone nature of traditional model rev…
Enhancing Automated Loop Invariant Generation for Complex Programs with Large Language Models
Ruibang Liu, Minyu Chen, Ling-I Wu +2
Automated program verification has always been an important component of building trustworthy software. While the analysis of real-world programs remains a theoretical challenge, t…
Can Language Models Pretend Solvers? Logic Code Simulation with LLMs
Minyu Chen, Guoqiang Li, Ling-I Wu +4
Transformer-based large language models (LLMs) have demonstrated significant potential in addressing logic problems. capitalizing on the great capabilities of LLMs for code-related…
AC4: Algebraic Computation Checker for Circuit Constraints in ZKPs
Qizhe Yang, Boxuan Liang, Hao Chen +1
Zero-knowledge proof (ZKP) systems have surged attention and held a fundamental role in contemporary cryptography. Zero-knowledge succinct non-interactive argument of knowledge (zk…