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Related papers: LLM-Guided Search for Deletion-Correcting Codes

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Large language models (LLMs) alignment aims to ensure that the behavior of LLMs meets human preferences. While collecting data from multiple fine-grained, aspect-specific preferences becomes more and more feasible, existing alignment…

Machine Learning · Computer Science 2026-03-03 Jia Zhang , Yao Liu , Chen-Xi Zhang , Yi Liu , Yi-Xuan Jin , Lan-Zhe Guo , Yu-Feng Li

Recent research suggests that tree search algorithms (e.g. Monte Carlo Tree Search) can dramatically boost LLM performance on complex mathematical reasoning tasks. However, they often require more than 10 times the computational resources…

Computation and Language · Computer Science 2024-07-02 Ante Wang , Linfeng Song , Ye Tian , Baolin Peng , Dian Yu , Haitao Mi , Jinsong Su , Dong Yu

List decoding of insertions and deletions in the Levenshtein metric is considered. The Levenshtein distance between two sequences is the minimum number of insertions and deletions needed to turn one of the sequences into the other. In this…

Information Theory · Computer Science 2017-11-20 Antonia Wachter-Zeh

Code editing encompasses a variety of pragmatic tasks that developers deal with daily. Despite its relevance and practical usefulness, automatic code editing remains an underexplored area in the evolution of deep learning models, partly due…

Computation and Language · Computer Science 2024-02-29 Kaixin Li , Qisheng Hu , Xu Zhao , Hui Chen , Yuxi Xie , Tiedong Liu , Qizhe Xie , Junxian He

Feature transformation aims to reconstruct the feature space of raw features to enhance the performance of downstream models. However, the exponential growth in the combinations of features and operations poses a challenge, making it…

Machine Learning · Computer Science 2024-12-19 Nanxu Gong , Chandan K. Reddy , Wangyang Ying , Haifeng Chen , Yanjie Fu

Large language models have shown good potential in supporting software development tasks. This is why more and more developers turn to LLMs (e.g. ChatGPT) to support them in fixing their buggy code. While this can save time and effort, many…

Software Engineering · Computer Science 2024-09-06 Yacine Majdoub , Eya Ben Charrada

In this work we consider Code World Models, world models generated by a Large Language Model (LLM) in the form of Python code for model-based Reinforcement Learning (RL). Calling code instead of LLMs for planning has potential to be more…

Artificial Intelligence · Computer Science 2024-10-31 Nicola Dainese , Matteo Merler , Minttu Alakuijala , Pekka Marttinen

The use of large language models (LLMs) for automated code generation has emerged as a significant focus within AI research. As these pretrained models continue to evolve, their ability to understand and generate complex code structures has…

Software Engineering · Computer Science 2025-05-06 Nazmus Ashrafi , Salah Bouktif , Mohammed Mediani

Large Language Models (LLMs) demonstrate exceptional reasoning abilities, enabling strong generalization across diverse tasks such as commonsense reasoning and instruction following. However, as LLMs scale, inference costs become…

Computation and Language · Computer Science 2025-02-06 Rhea Sanjay Sukthanker , Benedikt Staffler , Frank Hutter , Aaron Klein

The increasing development of LLMs in code generation has drawn significant attention among researchers. To enhance LLM-based code generation ability, current efforts are predominantly directed towards collecting high-quality datasets and…

Despite the recent advancement in Retrieval-Augmented Generation (RAG) systems, most retrieval methodologies are often developed for factual retrieval, which assumes query and positive documents are semantically similar. In this paper, we…

Information Retrieval · Computer Science 2025-04-10 Luo Ji , Feixiang Guo , Teng Chen , Qingqing Gu , Xiaoyu Wang , Ningyuan Xi , Yihong Wang , Peng Yu , Yue Zhao , Hongyang Lei , Zhonglin Jiang , Yong Chen

Large language models (LLMs) for code have become indispensable in various domains, including code generation, reasoning tasks and agent systems. While open-access code LLMs are increasingly approaching the performance levels of proprietary…

There has been a growing interest in using Large Language Models (LLMs) for code review thanks to their proven proficiency in code comprehension. The primary objective of most review scenarios is to generate desired review comments (DRCs)…

Software Engineering · Computer Science 2025-01-07 Yongda Yu , Lei Zhang , Guoping Rong , Haifeng Shen , Jiahao Zhang , Haoxiang Yan , Guohao Shi , Dong Shao , Ruiqi Pan , Yuan Li , Qiushi Wang , Zhao Tian

Feature selection is a crucial step in machine learning, especially for high-dimensional datasets, where irrelevant and redundant features can degrade model performance and increase computational costs. This paper proposes a novel…

Neural and Evolutionary Computing · Computer Science 2024-10-30 Azam Asilian Bidgoli , Shahryar Rahnamayan

We improve Levenshtein's upper bound for the cardinality of a code of length four that is capable of correcting single deletions over an alphabet of even size. We also illustrate that the new upper bound is sharp. Furthermore we construct…

Information Theory · Computer Science 2010-03-23 Hyun Kwang Kim , Joon Yop Lee , Dong Yeol Oh

In this work, we evaluate 10 open-source instructed LLMs on four representative code comprehension and generation tasks. We have the following main findings. First, for the zero-shot setting, instructed LLMs are very competitive on code…

Computation and Language · Computer Science 2023-08-03 Zhiqiang Yuan , Junwei Liu , Qiancheng Zi , Mingwei Liu , Xin Peng , Yiling Lou

Decompilation aims to convert binary code to high-level source code, but traditional tools like Ghidra often produce results that are difficult to read and execute. Motivated by the advancements in Large Language Models (LLMs), we propose…

Programming Languages · Computer Science 2025-08-06 Hanzhuo Tan , Qi Luo , Jing Li , Yuqun Zhang

Combining Large Language Models (LLMs) with heuristic search algorithms like A* holds the promise of enhanced LLM reasoning and scalable inference. To accelerate training and reduce computational demands, we investigate the coreset…

Artificial Intelligence · Computer Science 2024-10-25 Devaansh Gupta , Boyang Li

Analyzing network topologies and communication graphs plays a crucial role in contemporary network management. However, the absence of a cohesive approach leads to a challenging learning curve, heightened errors, and inefficiencies. In this…

Networking and Internet Architecture · Computer Science 2023-08-14 Sathiya Kumaran Mani , Yajie Zhou , Kevin Hsieh , Santiago Segarra , Ranveer Chandra , Srikanth Kandula

Large language models (LLMs) have shown significant advancements in code generation, but still face challenges on tasks beyond their basic capabilities. Recently, the notion of self-debugging has been proposed to boost the performance of…

Software Engineering · Computer Science 2025-01-23 Xiancai Chen , Zhengwei Tao , Kechi Zhang , Changzhi Zhou , Wanli Gu , Yuanpeng He , Mengdi Zhang , Xunliang Cai , Haiyan Zhao , Zhi Jin