OCELOT fuses a debounced force GMM-FSM and kinematic GLRT into an ESEKF to produce accurate leg odometry from IMU, encoders and force sensors while explicitly detecting and rejecting slippage on diverse terrains.
Evidential deep learning to quantify classification uncertainty.Advances in neural information processing systems, 31
2 Pith papers cite this work. Polarity classification is still indexing.
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Presents a distributional model of linguistic confidence, Faithfulness Divergence metric, and RALC pipeline that boosts faithfulness and calibration on QA benchmarks across LLM families.
citing papers explorer
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OCELOT: Odometry and Contact Estimation for Legged Robots
OCELOT fuses a debounced force GMM-FSM and kinematic GLRT into an ESEKF to produce accurate leg odometry from IMU, encoders and force sensors while explicitly detecting and rejecting slippage on diverse terrains.
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Retrieval-Augmented Linguistic Calibration
Presents a distributional model of linguistic confidence, Faithfulness Divergence metric, and RALC pipeline that boosts faithfulness and calibration on QA benchmarks across LLM families.