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UMich FATML · GitHub
UMich FATML
Fairness, Accountability, and Transparency in Machine Learning @ UMich
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code for "A transfer learning framework for weak to strong generalization" by Somerstep et al.
Jupyter Notebook
code for "Prompt Exploration with Prompt Regression" by Feffer et al
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code for "Large Language Model Routing with Benchmark Datasets" by Shnitzer et al.
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code for "Individually Fair Rankings" by Bower et al
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code for "SenSeI: Sensitive Set Invariance for Enforcing Individual Fairness" by Yurochkin and Sun
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mini-swe-agent
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SWE-agent/mini-swe-agent
The 100 line AI agent that solves GitHub issues or helps you in your command line. Radically simple, no huge configs, no giant monorepo—but scores >70% on SWE-bench verified!
UMich-FATML/mini-swe-agent’s past year of commit activity
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MIT
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Updated Nov 10, 2025
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Updated Sep 24, 2025
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Updated Jun 6, 2025
w2s-refinement
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code for "A transfer learning framework for weak to strong generalization" by Somerstep et al.
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prompt-regression
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code for "Prompt Exploration with Prompt Regression" by Feffer et al
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llm-routing
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code for "Large Language Model Routing with Benchmark Datasets" by Shnitzer et al.
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adversarial-supports
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code for "On sensitivity of meta-learning to support data" by Agarwal et al
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Apache-2.0
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no-tradeoff
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code for "Does enforcing fairness mitigate biases caused by subpopulation shift?" by Maity et al
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SenSTIR
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code for "Individually Fair Rankings" by Bower et al
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Updated Jun 4, 2025
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