Empirical evaluation of three LLMs finds prevalent overconfidence in insecure code generation, with security calibration outperforming functional calibration but both degrading in repository-level settings.
On calibration of modern neural networks
6 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 6representative citing papers
Semantic-level and verification-based uncertainty methods outperform token-level baselines for audio reasoning in ALLMs, but their relative performance on hallucination and unanswerable-question benchmarks is model- and task-dependent.
HyperNSD models hypergraph node states as an incidence-aware SDE whose pathwise variability yields competitive uncertainty estimates for OOD and misclassification detection.
Iterative receiver algorithms for PNC relays in multi-hop UWA networks achieve low BER of 10^{-5} in simulations and superior performance in lake and sea trials compared to baselines.
BiRG-LoRA achieves 69.31% macro-average accuracy across CMB, CMExam, MedQA, and MedMCQA, outperforming MoELoRA by 0.89 points with 28.1% fewer trainable parameters under a matched Qwen3-8B protocol.
MUSE applies Mamba sequential modeling to produce real-time uncertainty estimates for visual-inertial state estimation from asynchronous multimodal sensors.
citing papers explorer
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An Empirical Study of Security Calibration in Large Language Models for Code
Empirical evaluation of three LLMs finds prevalent overconfidence in insecure code generation, with security calibration outperforming functional calibration but both degrading in repository-level settings.
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Walking Through Uncertainty: An Empirical Study of Uncertainty Estimation for Audio-Aware Large Language Models
Semantic-level and verification-based uncertainty methods outperform token-level baselines for audio reasoning in ALLMs, but their relative performance on hallucination and unanswerable-question benchmarks is model- and task-dependent.
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Hypergraph Neural Stochastic Diffusion: An SDE Framework for Uncertainty Estimation
HyperNSD models hypergraph node states as an incidence-aware SDE whose pathwise variability yields competitive uncertainty estimates for OOD and misclassification detection.
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Iterative Receiver Processing at Relays in PNC-Enabled Multi-Hop Underwater Acoustic Networks
Iterative receiver algorithms for PNC relays in multi-hop UWA networks achieve low BER of 10^{-5} in simulations and superior performance in lake and sea trials compared to baselines.
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Clinically Structured Rank-Gated LoRA for Cross-Benchmark Medical Question Answering
BiRG-LoRA achieves 69.31% macro-average accuracy across CMB, CMExam, MedQA, and MedMCQA, outperforming MoELoRA by 0.89 points with 28.1% fewer trainable parameters under a matched Qwen3-8B protocol.
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MUSE: Multimodal Uncertainty Quantification of State Estimation
MUSE applies Mamba sequential modeling to produce real-time uncertainty estimates for visual-inertial state estimation from asynchronous multimodal sensors.