Tossup
Description acceptable. Over 100 implementations of a strategy for this task are surveyed in a 2024 paper by Gao et al. that categorizes them as Naive, Advanced, or Modular. Novel embeddings of query-specific documents are indexed and used in the “retrieval-augmented” form of this task. This task is performed by applying Brownian noise to points in a latent space and then decoding in diffusion models. A game-theoretic agent improves at this task while competing against a discriminator in a type of “adversarial” neural network. This task names a framework consisting of unsupervised “pre-training” followed by supervised “fine-tuning.” Nonsensical outputs during this task are called “hallucinations.” For 10 points, what task names a form of AI commonly used to produce text and images that is the “G” in GPT? ■END■
Buzzes
Summary
| Tournament | Edition | TUH | Conv. % | Neg % | Average Buzz |
|---|---|---|---|---|---|
| California | 2025-02-01 | 3 | 100% | 33% | 99.00 |
| Lower Mid-Atlantic | 2025-02-01 | 6 | 100% | 33% | 114.33 |
| Midwest | 2025-02-01 | 6 | 100% | 33% | 93.67 |
| Northeast | 2025-02-01 | 5 | 100% | 20% | 95.60 |
| Pacific Northwest | 2025-02-01 | 2 | 100% | 50% | 116.00 |
| South Central | 2025-02-01 | 2 | 100% | 0% | 44.00 |
| Southeast | 2025-02-01 | 1 | 100% | 100% | 128.00 |
| UK | 2025-02-01 | 5 | 100% | 60% | 108.60 |
| Upper Mid-Atlantic | 2025-02-01 | 8 | 100% | 0% | 85.88 |