Random shot selection yields the worst originality-similarity combination, while greedy and constraint-satisfaction selection raise originality without increasing item redundancy¶
Claim · All claims
Evidence · 1 study (2 entries) · causalr?·q2
Currency · newest study 2024 · not yet checked against its sources · not reviewed by a person
Subclaims¶
Reading the evidence codes
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q2 i? Random shot selection produces mostly low-originality items with the highest similarity peak; greedy and constraint satisfaction achieve lower similarity and higher originality consistently, with similarity remaining generally static as originality increases. → Antonio Laverghetta Jr. 2024
q2 i? In the full last-round univariate comparison, many more item pairs with cosine similarity of 1.0 occur under greedy than constraint satisfaction shot selection. → Antonio Laverghetta Jr. 2024 (2)
Evidence¶
Antonio Laverghetta Jr. 2024¶
Antonio Laverghetta Jr., Simone Luchini, Averie Linell, Roni Reiter-Palmon and Roger Beaty. (2024). The creative psychometric item generator: a framework for item generation and validation using large language models. CREAI 2024: Workshop on Artificial Intelligence and Creativity. https://arxiv.org/abs/2409.00202 doi:10.48550/arxiv.2409.00202
q2 · i? · causal · r?
Numerical analysis of the generated item pool plotted as a joint histogram of originality and mean cosine similarity (Results §4.2, Fig. 4), comparing random, greedy, and constraint-satisfaction shot selection. The article reports random selection obtained "the worst combination of results"; no inferential statistic is printed.
"We observe that random shot selection obtains the worst combination of results: not only are most items low on originality, but the distributionalso peaks the highest on similarity."
Antonio Laverghetta Jr. 2024 (2)¶
Antonio Laverghetta Jr., Simone Luchini, Averie Linell, Roni Reiter-Palmon and Roger Beaty. (2024). The creative psychometric item generator: a framework for item generation and validation using large language models. CREAI 2024: Workshop on Artificial Intelligence and Creativity. https://arxiv.org/abs/2409.00202
q2 · i? · design · r?
Univariate histogram of cosine similarity for all last-round items under greedy versus constraint satisfaction (Results §4.2, Fig. 5). The article reports "many more" duplicate items under greedy selection and notes greedy also peaks at higher density toward the lower end of the distribution.
"Although both methods generate some item pairs with cosine similarities of1.0, there are many more such items for greedy shot selection, indicating a much larger fraction of extremely similar item content."
Discussion¶
Related Claims¶
- CPIG's iterative exemplar selection consistently improves the originality of LLM responses to generated CPS items by the last round of item generation — related
- Uniform (redundant) contexts yield higher semantic similarity ratings than diverse contexts — related
- GNN training homogenizes concept representations, with 62.7% of prerequisite pairs becoming increasingly similar during DGCPL training — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
shot-selection-originality-similarity-tradeoff |
title |
Random shot selection yields the worst originality-similarity combination, while greedy and constraint-satisfaction selection raise originality without increasing item redundancy |
description |
Random shot selection yields the worst originality-similarity combination, while greedy and constraint-satisfaction selection raise originality without increasing item redundancy |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2024 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
2 — antonio-laverghetta-jr-2024, antonio-laverghetta-jr-2024-2 |
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