Comments (4)
We're still reviewing the process for evaluating submissions.
For now, we'd prefer results with a public or soon-to-be-public paper or technical report and the generated patches we can use to verify performance.
Each submission should include a description of the evaluation setting which will be categorized as assisted or unassisted.
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We're still reviewing the process for evaluating submissions. For now, we'd prefer results with a public or soon-to-be-public paper or technical report and the generated patches we can use to verify performance. Each submission should include a description of the evaluation setting which will be categorized as assisted or unassisted.
hello Carlos! @carlosejimenez
I wanted to follow up on the experimental results we submitted via email two days ago. We are keen to understand the review process as it's crucial for our project's next steps. I would greatly appreciate any information you could provide on this matter. Thank you very much for your understanding and support, and I look forward to your prompt response.
Thanks in advance!
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@zhimin-z @itaowei just a small update - thanks for your patience, we will be finalizing this and posting about it by the end of this month.
In short, it will require sending us 1. your execution .log
files and 2. the predictions generated by your model. We will use both to verify the reported numbers, and we will also make them accessible via the SWE-bench leaderboard on the website!
from swe-bench.
@zhimin-z @itaowei just a small update - thanks for your patience, we will be finalizing this and posting about it by the end of this month.
In short, it will require sending us 1. your execution
.log
files and 2. the predictions generated by your model. We will use both to verify the reported numbers, and we will also make them accessible via the SWE-bench leaderboard on the website!
Got it. Thanks!
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Related Issues (20)
- Running create_text_dataset.py gets Killed and takes too long HOT 2
- conda activate && conda install gxx_linux-64 gcc_linux-64 make -y' returned non-zero exit status 2 and Syntax error: "(" unexpected HOT 8
- Adding LLM tokens to the generated inference for cost calculation
- Remove `pre_install` from install specs
- `/bin/sh: pytest: command not found` when running evaluations HOT 2
- Repository not found while running python3 create_text_dataset.py HOT 1
- Dataset field & set up reliable environment
- swe-bench eval stops running after a point HOT 1
- improve eval performance by caching per-repo/version conda environments
- get_eval_refs doesn't work with a dataset that's been `save_to_disk`'d HOT 2
- environment is lost when running pip install
- Reproducer Docker image
- Dockerization of run_evaluation.py HOT 5
- Why AutoCodeRover not mentioned? HOT 1
- Is it possible to evaluate the train set?
- run_live.py: clone_repo() takes 3 positional arguments but 5 were given
- swe-bench eval stops running after a point HOT 2
- Has anyone successfully ran an eval on patches against early versions of astropy, sympy, scipy etc? I'm really struggling to run things from earlier python versions HOT 2
- Using `uv pip` instead of `pip` for significant speedup HOT 1
- How can one participate in the SWE-bench leaderboard? HOT 2
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