Fetching the paper…
Reading the bibliography…
Code generation has been greatly enhanced by the profound advancements in Large Language Models (LLMs) recently.
Attention is all you need
Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez A N, Kaiser L, Polosukhin I · 2017
Earlier work this paper cites.
Improving language understanding by generative pre-training, 2018
OpenAI · 2018
Earlier work this paper cites.
Exploring the limits of transfer learning with a unified text-to-text transformer
Raffel C, Shazeer N, Roberts A, Lee K, Narang S, Matena M, Zhou Y, Li W, Liu P J · 2020
Earlier work this paper cites.
Detecting code clones with graph neural network and flow-augmented abstract syntax tree
Wang W, Li G, Ma B, Xia X, Jin Z · 2020
Earlier work this paper cites.
Learning and evaluating contextual embedding of source code
Kanade A, Maniatis P, Balakrishnan G, Shi K · 2020
Earlier work this paper cites.
CodeBERT: A pre-trained model for programming and natural languages
Feng Z, Guo D, Tang D, Duan N, Feng X, Gong M, Shou L, Qin B, Liu T, Jiang D, Zhou M · 2020
Earlier work this paper cites.
Electra: Pre-training text encoders as discriminators rather than generators
Clark K, Luong M T, Le Q V, Manning C D · 2020
Earlier work this paper cites.
Evaluating large language models trained on code
Chen M, Tworek J, Jun H, Yuan Q, Pinto H P d O, Kaplan J, Edwards H, Burda Y, Joseph N, Brockman G, others · 2021
Earlier work this paper cites.
GPT-Neo: Large scale autoregressive language modeling with mesh-tensorflow
Black S, Gao L, Wang P, Leahy C, Biderman S · 2021
Earlier work this paper cites.
CodeT5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation
Wang Y, Wang W, Joty S, Hoi S C · 2021
Earlier work this paper cites.
Multimodal representation for neural code search
Gu J, Chen Z, Monperrus M · 2021
Earlier work this paper cites.
GraphCodeBERT: Pre-training code representations with data flow
Guo D, Ren S, Lu S, Feng Z, Tang D, Liu S, Zhou L, Duan N, Svyatkovskiy A, Fu S, Tufano M, Deng S K, Clement C, Drain D, Sundaresan N, Yin J, Jiang D, Zhou M · 2021
Earlier work this paper cites.
Unified pre-training for program understanding and generation
Ahmad W, Chakraborty S, Ray B, Chang K W · 2021
Earlier work this paper cites.
SynCoBERT: Syntax-guided multi-modal contrastive pre-training for code representation
Wang X, Wang Y, Mi F, Zhou P, Wan Y, Liu X, Li L, Wu H, Liu J, Jiang X · 2021
Earlier work this paper cites.
Measuring coding challenge competence with APPS
Hendrycks D, Basart S, Kadavath S, Mazeika M, Arora A, Guo E, Burns C, Puranik S, He H, Song D, Steinhardt J · 2021
Cited alongside, same era.
Program synthesis with large language models
Austin J, Odena A, Nye M, Bosma M, Michalewski H, Dohan D, Jiang E, Cai C, Terry M, Le Q, others · 2021
Cited alongside, same era.
Fault-aware neural code rankers
Inala J P, Wang C, Yang M, Codas A, Encarnación M, Lahiri S, Musuvathi M, Gao J · 2022
Cited alongside, same era.
Competition-level code generation with AlphaCode
Li Y, Choi D, Chung J, Kushman N, Schrittwieser J, Leblond R, Eccles T, Keeling J, Gimeno F, Dal Lago A, Hubert T, Choy P, Masson d’Autume d C, Babuschkin I, Chen X, Huang P S, Welbl J, Gowal S, Cherepanov A, Molloy J, Mankowitz D J, Sutherland Robson E, Kohli P, Freitas d N, Kavukcuoglu K, Vinyals O · 2022
Cited alongside, same era.
NS3: Neuro-symbolic semantic code search
Arakelyan S, Hakhverdyan A, Allamanis M, Garcia L, Hauser C, Ren X · 2022
Cited alongside, same era.
ALGO: Synthesizing algorithmic programs with generated oracle verifiers
Zhang K, Wang D, Xia J, Wang W Y, Li L · 2023
Later among the works it cites.
OpenAI · 2023
Later among the works it cites.
Anil R, Dai A M, Firat O, Johnson M, Lepikhin D, Passos A, Shakeri S, Taropa E, Bailey P, Chen Z, others · 2023
Later among the works it cites.
PaLM: Scaling language modeling with pathways
Chowdhery A, Narang S, Devlin J, Bosma M, Mishra G, Roberts A, Barham P, Chung H W, Sutton C, Gehrmann S, others · 2023
Later among the works it cites.
WizardCoder: Empowering code large language models with Evol-Instruct
Luo Z, Xu C, Zhao P, Sun Q, Geng X, Hu W, Tao C, Ma J, Lin Q, Jiang D · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
UniXcoder: Unified cross-modal pre-training for code representation
Guo D, Lu S, Duan N, Wang Y, Zhou M, Yin J · 2022
Cited alongside, same era.
ChatGPT: Optimizing language models for dialogue, 2022
OpenAI · 2022
Cited alongside, same era.
Coder reviewer reranking for code generation
Zhang T, Yu T, Hashimoto T B, Lewis M, Yih W t, Fried D, Wang S I · 2022
Cited alongside, same era.
StarCoder: may the source be with you!
Li R, Allal L B, Zi Y, Muennighoff N, Kocetkov D, Mou C, Marone M, Akiki C, Li J, Chim J, others · 2023
Cited alongside, same era.
CodeGen: An open large language model for code with multi-turn pogram synthesis
Nijkamp E, Pang B, Hayashi H, Tu L, Wang H, Zhou Y, Savarese S, Xiong C · 2023
Cited alongside, same era.
Code LLaMa: Open foundation models for code
Rozière B, Gehring J, Gloeckle F, Sootla S, Gat I, Tan X E, Adi Y, Liu J, Remez T, Rapin J, others · 2023
Cited alongside, same era.
Measuring code maintainability with deep neural networks
Hu Y, Jiang H, Hu Z · 2023
Cited alongside, same era.
Gunasekar S, Zhang Y, Aneja J, Mendes C C T, Del Giorno A, Gopi S, Javaheripi M, Kauffmann P, Rosa d G, Saarikivi O, others · 2023
Later among the works it cites.
CodeGeeX: A pre-trained model for code generation with multilingual benchmarking on HumanEval-X
Zheng Q, Xia X, Zou X, Dong Y, Wang S, Xue Y, Shen L, Wang Z, Wang A, Li Y, Su T, Yang Z, Tang J · 2023
Later among the works it cites.
InCoder: A generative model for code infilling and synthesis
Fried D, Aghajanyan A, Lin J, Wang S, Wallace E, Shi F, Zhong R, Yih S, Zettlemoyer L, Lewis M · 2023
Later among the works it cites.
Teaching large language models to self-debug
Chen X, Lin M, Schärli N, Zhou D · 2023
Later among the works it cites.
Is your code generated by ChatGPT really correct? Rigorous evaluation of large language models for code generation
Liu J, Xia C S, Wang Y, Zhang L · 2023
Later among the works it cites.
Large language models are zero-shot fuzzers: Fuzzing deep-learning libraries via large language models
Deng Y, Xia C S, Peng H, Yang C, Zhang L · 2023
Later among the works it cites.
DeepSeek LLM: Scaling open-source language models with longtermism
Bi X, Chen D, Chen G, Chen S, Dai D, Deng C, Ding H, Dong K, Du Q, Fu Z, others · 2024
Closest in time.
Empirically revisiting and enhancing automatic classification of bug and non-bug issues
Li Z, Pan M, Pei Y, Zhang T, Wang L, Li X · 2024
Closest in time.