Papers › Coder Reviewer Reranking for Code Generation

Coder Reviewer Reranking for Code Generation

29 Nov 2022arXiv:2211.16490archive 2025-07-28

Tianyi Zhang, Tao Yu, Tatsunori B. Hashimoto, Mike Lewis, Wen-tau Yih, Daniel Fried, Sida I. Wang

Sampling diverse programs from a code language model and reranking with model likelihood is a popular method for code generation but it is prone to preferring degenerate solutions. Inspired by collaborative programming, we propose Coder-Reviewer reranking. We augment Coder language models from past work, which generate programs given language instructions, with Reviewer models, which evaluate the likelihood of the instruction given the generated programs. We perform an extensive study across six datasets with eight models from three model families. Experimental results show that Coder-Reviewer reranking leads to consistent and significant improvement (up to 17% absolute accuracy gain) over reranking with the Coder model only. When combined with executability filtering, Coder-Reviewer reranking can often outperform the minimum Bayes risk method. Coder-Reviewer reranking is easy to implement by prompting, can generalize to different programming languages, and works well with off-the-shelf hyperparameters.

PaperPDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2211.16490")

Code

Syntology Ran 2 of 2 code samples harvested from 1 repository linked to this paper; 0 have no recorded run. Of those that ran: 1 ran · honoured contract; 1 ran · violated contract.

By repository: official repository: 2 samples from 1 repository, 2 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

facebookresearch/coder_reviewer_reranking officialmentioned in papermentioned on GitHubpytorch report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

2 samples harvested; 2 ran; 1 honoured the contract we drafted; 0 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · honoured contract
1ran · violated contract

Licence: 2 of the 2 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from facebookresearch/coder_reviewer_reranking. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

filter_repeat facebookresearch/coder_reviewer_reranking/sample_selectors.py official repository ran · violated contract fingerprinted licence not identified · pointer only · 64d47c9d4e0d0c5e · report
single_exec_result_matching facebookresearch/coder_reviewer_reranking/sample_selectors.py official repository ran · honoured contract fingerprinted licence not identified · pointer only · e0d0a3c69f5ae939 · report

Tasks

Code GenerationLanguage ModelingLanguage ModellingReranking

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Code Generation MBPP code-davinci-002 175B + Reviewer Accuracy 66.9 #36 of 99 Archive leaderboard report
Code Generation MBPP code-davinci-002 175B + Coder-Reviewer Accuracy 66.4 #37 of 99 Archive leaderboard report
Code Generation MBPP code-davinci-002 175B + MBR-Exec Accuracy 63 #42 of 99 Archive leaderboard report
Code Generation MBPP code-cushman-001 12B + MBR-Exec Accuracy 48.3 #66 of 99 Archive leaderboard report
Code Generation MBPP CodeGen 16B + MBR-Exec Accuracy 47.3 #69 of 99 Archive leaderboard report
Code Generation MBPP CodeGen 16B + Coder-Reviewer Accuracy 46.2 #73 of 99 Archive leaderboard report
Code Generation MBPP CodeGen 16B + Reviewer Accuracy 44.1 #78 of 99 Archive leaderboard report
Code Generation MBPP InCoder 6.7B + MBR-Exec Accuracy 26.7 #92 of 99 Archive leaderboard report
Code Generation MBPP InCoder 6.7B + Coder-Reviewer Accuracy 26.1 #93 of 99 Archive leaderboard report
Code Generation MBPP InCoder 6.7B + Reviewer Accuracy 24.4 #94 of 99 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections