allenai/Sera-4.5A-Full-T2

Dataset

This dataset contains 66337 trajectories. Data was generated from the *second* rollout of SVG on 121 SWE-smith codebases using GLM-4.5-Air as teacher and includes three SVG runs per function. Sera-4.5-Lite-T2 is a subset of this dataset and was used to train SERA-32B-GA.

3

12 commits

1 linked in READMEs

updated Mar 9, 2026

See the code

README

This dataset contains 66337 trajectories. Data was generated from the second rollout of SVG on 121 SWE-smith codebases using GLM-4.5-Air as teacher and includes three SVG runs per function. Sera-4.5-Lite-T2 is a subset of this dataset and was used to train SERA-32B-GA.

Schema:

messages: Generated trajectory
instance_id: ID of trajectory
rollout_patch: Created patch to the codebase from the current trajectory
func_name: Name of function sampled from codebase to start the pipeline
func_path: File path to the sampled function
line_level_recall: Minimum patch verification threshold that is satisfied
problem_statement: Problem statement provided to the model
target_patch: Ground truth patch (empty if T1) 
docker_image: Docker image used

Verification:
Verification can be done on T2 trajectories by comparing generated rollout patches against the target ground truth patch from T1 trajectories.
We do not verify in our main experiments but provide the metadata to do so in target_patch and rollout_patch.

Note: Apply json.loads() to the messages column to load.

Sera-4.5A-Full-T2 is licensed under the Open Data Commons Attribution License v1.0 (ODC-By). It is intended for research and educational use. For more information, please see our Responsible Use Guidelines.

Contributors

ethanlshen

12 commits

allenai/Sera-4.5A-Full-T2

Dataset

This dataset contains 66337 trajectories. Data was generated from the *second* rollout of SVG on 121 SWE-smith codebases using GLM-4.5-Air as teacher and includes three SVG runs per function. Sera-4.5-Lite-T2 is a subset of this dataset and was used to train SERA-32B-GA.

3

12 commits

1 linked in READMEs

updated Mar 9, 2026

See the code

README

This dataset contains 66337 trajectories. Data was generated from the second rollout of SVG on 121 SWE-smith codebases using GLM-4.5-Air as teacher and includes three SVG runs per function. Sera-4.5-Lite-T2 is a subset of this dataset and was used to train SERA-32B-GA.

Schema:

messages: Generated trajectory
instance_id: ID of trajectory
rollout_patch: Created patch to the codebase from the current trajectory
func_name: Name of function sampled from codebase to start the pipeline
func_path: File path to the sampled function
line_level_recall: Minimum patch verification threshold that is satisfied
problem_statement: Problem statement provided to the model
target_patch: Ground truth patch (empty if T1) 
docker_image: Docker image used

Verification:
Verification can be done on T2 trajectories by comparing generated rollout patches against the target ground truth patch from T1 trajectories.
We do not verify in our main experiments but provide the metadata to do so in target_patch and rollout_patch.

Note: Apply json.loads() to the messages column to load.

Sera-4.5A-Full-T2 is licensed under the Open Data Commons Attribution License v1.0 (ODC-By). It is intended for research and educational use. For more information, please see our Responsible Use Guidelines.

Contributors

ethanlshen

12 commits