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.
ErrorMap and ErrorAtlas: Charting the failure landscape of large language models
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Token-level contrastive attribution yields informative signals for some LLM benchmark failures but is not universally applicable across datasets and models.
An external zero-shot monitor detects nine unsafe reasoning behaviors in LLMs at 87% step-level accuracy with low false positives and low latency.
The Workload-Router-Pool architecture is a 3D framework for LLM inference optimization that synthesizes prior vLLM work into a 3x3 interaction matrix and proposes 21 research directions at the intersections.
citing papers explorer
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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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Contrastive Attribution in the Wild: An Interpretability Analysis of LLM Failures on Realistic Benchmarks
Token-level contrastive attribution yields informative signals for some LLM benchmark failures but is not universally applicable across datasets and models.
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Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models
An external zero-shot monitor detects nine unsafe reasoning behaviors in LLMs at 87% step-level accuracy with low false positives and low latency.
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The Workload-Router-Pool Architecture for LLM Inference Optimization: A Vision Paper from the vLLM Semantic Router Project
The Workload-Router-Pool architecture is a 3D framework for LLM inference optimization that synthesizes prior vLLM work into a 3x3 interaction matrix and proposes 21 research directions at the intersections.