Papers with diagnostic metric

3 papers
An Empirical Study of Position Bias in Modern Information Retrieval (2025.findings-emnlp)

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Challenge: a new evaluation framework is used to assess the extent and impact of position bias in information retrieval.
Approach: They introduce a position-aware retrieval benchmark and a diagnostic metric to quantify position bias . they compare models with BM25, dense embedding models, ColBERT-style late-interaction models .
Outcome: The proposed framework evaluates retrieval models for position bias from a worst-case perspective.
Probing the Safety Robustness of LLMs in Latent Space (2026.acl-long)

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Challenge: Despite substantial progress in safety alignment techniques, aligned large language models can still produce unsafe responses under minor internal perturbations.
Approach: They introduce Activation Steering Attack (ASA) and leverage the Negative Log-Likelihood (NLL) as a diagnostic signal to probe the local sensitivity of safety behaviors in latent space.
Outcome: The proposed method is model-agnostic and supervision-free, enabling a general and reproducible diagnostic metric for analyzing safety robustness.
From Passive Metric to Active Signal: The Evolving Role of Uncertainty Quantification in Large Language Models (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have remarkable capabilities, but unreliability remains a barrier to deployment in high-stakes domains.
Approach: They propose to transform uncertainty from a passive diagnostic metric to an active control signal guiding real-time model behavior.
Outcome: The proposed model evolution from passive diagnostic metric to active control signal is critical for high-stakes applications.

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