Search Results - "Computing methodologies Machine learning Machine learning approaches Bio-inspired approaches"

GENESYS: A novel evolutionary program synthesis tool with continuous optimization by Mandal, Shantanu, Anderson, Todd A, Turek, Javier, Gottschlich, Justin, Muzahid, Abdullah

“…Automatic software generation based on some specification is known as program synthesis. Most existing approaches formulate program synthesis as a search…”
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A Closer Look at Different Difficulty Levels Code Generation Abilities of ChatGPT by Yan, Dapeng, Gao, Zhipeng, Liu, Zhiming

“…Code generation aims to generate source code implementing human requirements illustrated with natural language specifications. With the rapid development of…”
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PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search by Ahmad, Afzal, Xie, Zhiyao, Zhang, Wei

“…Differentiable Neural Architecture Search (NAS) relies on aggressive weight-sharing to reduce its search cost. This leads to GPU-memory bottlenecks that hamper…”
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Search-Based LLMs for Code Optimization by Gao, Shuzheng, Gao, Cuiyun, Gu, Wenchao, Lyu, Michael R.

“…The code written by developers usually suffers from efficiency problems and contain various performance bugs. These inefficiencies necessitate the research of…”
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Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software by Chen, Zhenpeng, Li, Xinyue, Zhang, Jie M., Sarro, Federica, Liu, Yang

“…Intersectional fairness is a critical requirement for Machine Learning (ML) software, demanding fairness across subgroups defined by multiple protected…”
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CODEMORPH: Mitigating Data Leakage in Large Language Model Assessment by Rao, Hongzhou, Zhao, Yanjie, Zhu, Wenjie, Xiao, Ling, Wang, Meizhen, Wang, Haoyu

“…Concerns about benchmark leakage in large language models for code (Code LLMs) have raised issues of data contamination and inflated evaluation metrics. The…”
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ReChisel: Effective Automatic Chisel Code Generation by LLM with Reflection by Niu, Juxin, Liu, Xiangfeng, Niu, Dan, Wang, Xi, Jiang, Zhe, Guan, Nan

“…Coding with hardware description languages (HDLs) such as Verilog is a time-intensive and laborious task. With the rapid advancement of large language models…”
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GARL: Genetic Algorithm-Augmented Reinforcement Learning to Detect Violations in Marker-Based Autonomous Landing Systems by Liang, Linfeng, Deng, Yao, Morton, Kye, Kallinen, Valtteri, James, Alice, Seth, Avishkar, Kuantama, Endrowednes, Mukhopadhyay, Subhas, Han, Richard, Zheng, Xi

“…Automated Uncrewed Aerial Vehicle (UAV) landing is crucial for autonomous UAV services such as monitoring, surveying, and package delivery. It involves…”
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UniGenCoder: Merging SEQ2SEQ and SEQ2TREE Paradigms for Unified Code Generation by Shao, Liangying, Yan, Yanfu, Poshyvanyk, Denys, Su, Jinsong

“…Deep learning-based code generation has completely transformed the way developers write programs today. Existing approaches to code generation have focused…”
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PrefixRL: Optimization of Parallel Prefix Circuits using Deep Reinforcement Learning by Roy, Rajarshi, Raiman, Jonathan, Kant, Neel, Elkin, Ilyas, Kirby, Robert, Siu, Michael, Oberman, Stuart, Godil, Saad, Catanzaro, Bryan

“…In this work, we present a reinforcement learning (RL) based approach to designing parallel prefix circuits such as adders or priority encoders that are…”
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Code Difference Guided Adversarial Example Generation for Deep Code Models by Tian, Zhao, Chen, Junjie, Jin, Zhi

“…Adversarial examples are important to test and enhance the robustness of deep code models. As source code is discrete and has to strictly stick to complex…”
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UniCoS: A Unified Neural and Accelerator Co-Search Framework for CNNs and ViTs by Fu, Wei, Lou, Wenqi, Tang, Cheng, Wen, Hongbing, Qin, Yunji, Gong, Lei, Wang, Chao, Zhou, Xuehai

“…Current algorithm-hardware co-search works often suffer from lengthy training times and inadequate exploration of hardware design spaces, leading to suboptimal…”
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FixKit: A Program Repair Collection for Python by Smytzek, Marius, Eberlein, Martin, Werk, Kai, Grunske, Lars, Zeller, Andreas

“…In recent years, automatic program repair has gained much attention in the research community. Generally, program repair approaches consider a faulty program…”
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Distilled Lifelong Self-Adaptation for Configurable Systems by Ye, Yulong, Chen, Tao, Li, Miqing

“…Modern configurable systems provide tremendous opportunities for engineering future intelligent software systems. A key difficulty thereof is how to…”
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Resolving Goal-Conflicts and Scaling Synthesis through Mode-Based Decomposition by Brizzio, Matias

“…Reactive synthesis, with its roots in the work of A. Church, presents a transformative approach for the formal methods community. It seeks to translate system…”
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Automated Design of Complex Analog Circuits with Multiagent based Reinforcement Learning by Zhang, Jinxin, Bao, Jiarui, Huang, Zhangcheng, Zeng, Xuan, Lu, Ye

“…Despite the effort of analog circuit design automation, currently complex analog circuit design still requires extensive manual iterations, making it labor…”
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A Tale of Two Domains: Exploring Efficient Architecture Design for Truly Autonomous Things by Hou, Xiaofeng, Xu, Tongqiao, Li, Chao, Xu, Cheng, Liu, Jiacheng, Hu, Yang, Zhao, Jieru, Leng, Jingwen, Cheng, Kwang-Ting, Guo, Minyi

“…Autonomous Things (AuT) refers to a collection of self-sufficient tiny devices capable of performing intelligent computations. Looking ahead, AuT promises to…”
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Dissecting Global Search: A Simple Yet Effective Method to Boost Individual Discrimination Testing and Repair by Quan, Lili, Li, Tianlin, Xie, Xiaofei, Chen, Zhenpeng, Chen, Sen, Jiang, Lingxiao, Li, Xiaohong

“…Deep Learning (DL) has achieved significant success in socially critical decision-making applications but often exhibits unfair behaviors, raising social…”
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Fast and Reliable Program Synthesis via User Interaction by Chen, Yanju, Wang, Chenglong, Wang, Xinyu, Bastani, Osbert, Feng, Yu

“…The performance of programming-by-example systems varies significantly across different tasks and even across different examples in one task. The key issue is…”
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SynergicLearning: Neural Network-Based Feature Extraction for Highly-Accurate Hyperdimensional Learning by Nazemi, Mahdi, Esmaili, Amirhossein, Fayyazi, Arash, Pedram, Massoud

“…Machine learning models differ in terms of accuracy, computational/memory complexity, training time, and adaptability among other characteristics. For example,…”
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