Search Results for author: Daoguang Zan

Found 11 papers, 7 papers with code

CodeS: Natural Language to Code Repository via Multi-Layer Sketch

1 code implementation25 Mar 2024 Daoguang Zan, Ailun Yu, Wei Liu, Dong Chen, Bo Shen, Wei Li, Yafen Yao, Yongshun Gong, Xiaolin Chen, Bei guan, Zhiguang Yang, Yongji Wang, Qianxiang Wang, Lizhen Cui

For feedback-based evaluation, we develop a VSCode plugin for CodeS and engage 30 participants in conducting empirical studies.

Benchmarking

PanGu-Coder2: Boosting Large Language Models for Code with Ranking Feedback

no code implementations27 Jul 2023 Bo Shen, Jiaxin Zhang, Taihong Chen, Daoguang Zan, Bing Geng, An Fu, Muhan Zeng, Ailun Yu, Jichuan Ji, Jingyang Zhao, Yuenan Guo, Qianxiang Wang

In this paper, we propose a novel RRTF (Rank Responses to align Test&Teacher Feedback) framework, which can effectively and efficiently boost pre-trained large language models for code generation.

Code Generation

Hierarchical and Contrastive Representation Learning for Knowledge-aware Recommendation

no code implementations15 Apr 2023 Bingchao Wu, Yangyuxuan Kang, Daoguang Zan, Bei guan, Yongji Wang

Specifically, for avoiding the exponential expansion of neighbors, we propose a hierarchical message aggregation mechanism to interact separately with low-order neighbors and meta-path-constrained high-order neighbors.

Contrastive Learning Knowledge-Aware Recommendation +1

RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation

1 code implementation22 Mar 2023 Fengji Zhang, Bei Chen, Yue Zhang, Jacky Keung, Jin Liu, Daoguang Zan, Yi Mao, Jian-Guang Lou, Weizhu Chen

The task of repository-level code completion is to continue writing the unfinished code based on a broader context of the repository.

Code Completion Language Modelling +1

Large Language Models Meet NL2Code: A Survey

no code implementations19 Dec 2022 Daoguang Zan, Bei Chen, Fengji Zhang, Dianjie Lu, Bingchao Wu, Bei guan, Yongji Wang, Jian-Guang Lou

The task of generating code from a natural language description, or NL2Code, is considered a pressing and significant challenge in code intelligence.

When Language Model Meets Private Library

1 code implementation31 Oct 2022 Daoguang Zan, Bei Chen, Zeqi Lin, Bei guan, Yongji Wang, Jian-Guang Lou

In this paper, we investigate how to equip pre-trained language models with the ability of code generation for private libraries.

Code Generation Language Modelling +1

CodeT: Code Generation with Generated Tests

1 code implementation21 Jul 2022 Bei Chen, Fengji Zhang, Anh Nguyen, Daoguang Zan, Zeqi Lin, Jian-Guang Lou, Weizhu Chen

A natural way to evaluate the quality and correctness of a code solution is to run it against a set of test cases, but the manual creation of such test cases is often costly and time-consuming.

 Ranked #1 on Code Generation on APPS (Introductory Pass@1 metric)

Code Generation

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