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cs.CL2025
Shrinking the Generation-Verification Gap with Weak Verifiers
Jon Saad-Falcon, E. Kelly Buchanan, Mayee F. Chen +9
Verifiers can improve language model capabilities by scoring and ranking responses from generated candidates. Currently, high-quality verifiers are either unscalable (e.g., humans)…
cs.CL2024★ 3 cited
The ALCHEmist: Automated Labeling 500x CHEaper Than LLM Data Annotators
Tzu-Heng Huang, Catherine Cao, Vaishnavi Bhargava +1
Large pretrained models can be used as annotators, helping replace or augment crowdworkers and enabling distilling generalist models into smaller specialist models. Unfortunately,…