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repro-nanoquant-efficient-sub-1-bit-quantization-of-large-language-models
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Add the missing Claim 5 page: rerun the COMPAS case study on real ProPublica data; optimal fair thresholds differ by 0.08-0.13 across groups and forcing a single threshold costs 52-341 utility
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Add the missing Claim 5 page: rerun the COMPAS case study on real ProPublica data; optimal fair thresholds differ by 0.08-0.13 across groups and forcing a single threshold costs 52-341 utility
5 days ago
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Add the missing Claim 5 page: rerun the COMPAS case study on real ProPublica data; optimal fair thresholds differ by 0.08-0.13 across groups and forcing a single threshold costs 52-341 utility
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audit_fair_calibrated.py
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Update logbook: Repro - NanoQuant: Efficient Sub-1-bit Quantization of Large Language Models
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official_claims.json
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outputs_compas_results.json
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requirements.txt
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