6 citations · 8 across the 8 of their papers we have counts for
8 papers
AutoICE: Automatically Synthesizing Verifiable C Code via LLM-driven Evolution
Weilin Luo, Xueyi Liang, Haotian Deng +2
Automatically synthesizing verifiable code from natural language requirements ensures software correctness and reliability while significantly lowering the barrier to adopting the…
SCoRE: Benchmarking Long-Chain Reasoning in Commonsense Scenarios
Weidong Zhan, Yue Wang, Nan Hu +12
Currently, long-chain reasoning remains a key challenge for large language models (LLMs) because natural texts lack sufficient explicit reasoning data. However, existing benchmarks…
Reinforcement Learning with Knowledge Representation and Reasoning: A Brief Survey
Chao Yu, Shicheng Ye, Hankz Hankui Zhuo
Reinforcement Learning (RL) has achieved tremendous development in recent years, but still faces significant obstacles in addressing complex real-life problems due to the issues of…
A Noise-tolerant Differentiable Learning Approach for Single Occurrence Regular Expression with Interleaving
Rongzhen Ye, Tianqu Zhuang, Hai Wan +3
We study the problem of learning a single occurrence regular expression with interleaving (SOIRE) from a set of text strings possibly with noise. SOIRE fully supports interleaving…
How to Identify Boundary Conditions with Contrasty Metric?
Weilin Luo, Hai Wan, Xiaotong Song +3
The boundary conditions (BCs) have shown great potential in requirements engineering because a BC captures the particular combination of circumstances, i.e., divergence, in which t…
Structural Similarity of Boundary Conditions and an Efficient Local Search Algorithm for Goal Conflict Identification
Hongzhen Zhong, Hai Wan, Weilin Luo +3
In goal-oriented requirements engineering, goal conflict identification is of fundamental importance for requirements analysis. The task aims to find the feasible situations which…
CoAPI: An Efficient Two-Phase Algorithm Using Core-Guided Over-Approximate Cover for Prime Compilation of Non-Clausal Formulae
Weilin Luo, Hai Wan, Hongzhen Zhong +1
Prime compilation, i.e., the generation of all prime implicates or implicants (primes for short) of formulae, is a prominent fundamental issue for AI. Recently, the prime compilati…
Combining Reinforcement Learning and Configuration Checking for Maximum k-plex Problem
Peilin Chen, Hai Wan, Shaowei Cai +2
The Maximum k-plex Problem is an important combinatorial optimization problem with increasingly wide applications. Due to its exponential time complexity, many heuristic methods ha…