A Survey of Neural Code Intelligence: Paradigms, Advances and Beyond
Qiushi Sun, Zhirui Chen, Fangzhi Xu, Kanzhi Cheng, Chang Ma, Zhangyue, Yin, Jianing Wang, Chengcheng Han, Renyu Zhu, Shuai Yuan, Qipeng Guo, Xipeng, Qiu, Pengcheng Yin, Xiaoli Li, Fei Yuan, Lingpeng Kong, Xiang Li, Zhiyong Wu

TL;DR
This survey comprehensively reviews the evolution, current state, and future directions of neural code intelligence, highlighting paradigm shifts, technical advances, and cross-domain opportunities in leveraging deep learning for understanding and generating code.
Contribution
It provides a systematic, chronological overview of over 50 models and 680 works, analyzing paradigm shifts, technical transitions, and emerging synergies in neural code intelligence.
Findings
Shift from RNN-based models to Large Language Models
Expansion from specific tasks to complex real-world challenges
Identification of cross-domain opportunities and future research directions
Abstract
Neural Code Intelligence -- leveraging deep learning to understand, generate, and optimize code -- holds immense potential for transformative impacts on the whole society. Bridging the gap between Natural Language and Programming Language, this domain has drawn significant attention from researchers in both research communities over the past few years. This survey presents a systematic and chronological review of the advancements in code intelligence, encompassing over 50 representative models and their variants, more than 20 categories of tasks, and an extensive coverage of over 680 related works. We follow the historical progression to trace the paradigm shifts across different research phases (e.g., from modeling code with recurrent neural networks to the era of Large Language Models). Concurrently, we highlight the major technical transitions in models, tasks, and evaluations…
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Code & Models
- 🤗internlm/JanusCoder-8Bmodel· 43 dl· ♡ 1343 dl♡ 13
- 🤗internlm/JanusCoder-14Bmodel· 22 dl· ♡ 3422 dl♡ 34
- 🤗internlm/JanusCoderV-7Bmodel· 62 dl· ♡ 1462 dl♡ 14
- 🤗internlm/JanusCoderV-8Bmodel· 70 dl· ♡ 1370 dl♡ 13
- 🤗cyankiwi/JanusCoder-14B-AWQ-4bitmodel· 10 dl10 dl
- 🤗cyankiwi/JanusCoder-14B-AWQ-8bitmodel· 1 dl1 dl
- 🤗cyankiwi/JanusCoder-8B-AWQ-8bitmodel· 1 dl1 dl
- 🤗cyankiwi/JanusCoder-8B-AWQ-4bitmodel· 9 dl9 dl
- 🤗unsloth/JanusCoder-8B-GGUFmodel· 357 dl· ♡ 3357 dl♡ 3
- 🤗unsloth/JanusCoder-8Bmodel· 18 dl18 dl
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Taxonomy
TopicsMachine Learning in Bioinformatics · Evolutionary Algorithms and Applications · Computability, Logic, AI Algorithms
