FailureScope clusters evaluation probes by cross-model failure patterns via LOMO to produce stable taxonomies that generalize across single-turn, multi-turn, and adversarial regimes, with reported metrics of Kendall's tau 0.81 and AUC 0.88.
Predictaboard: Benchmarking llm score predictability.arXiv preprint arXiv:2502.14445
2 Pith papers cite this work. Polarity classification is still indexing.
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Proposes RAP, a retrieval-based approximate prior method, to predict performance of symbolic programs and LLM prompts on new tasks using a Bernoulli model and corpus-derived performance distributions.
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FailureScope: Cross-Regime Behavioral Diagnosis of Language Model Weaknesses
FailureScope clusters evaluation probes by cross-model failure patterns via LOMO to produce stable taxonomies that generalize across single-turn, multi-turn, and adversarial regimes, with reported metrics of Kendall's tau 0.81 and AUC 0.88.
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Predicting Performance of Symbolic and Prompt Programs with Examples
Proposes RAP, a retrieval-based approximate prior method, to predict performance of symbolic programs and LLM prompts on new tasks using a Bernoulli model and corpus-derived performance distributions.