The paper introduces a novel framework to quantify faithful confidence expression (FC) in Large Reasoning Models (LRMs), finding that FC remains a significant and challenging reliability target for th…

The paper introduces CalArena, a large-scale, standardized benchmark covering nearly 2000 experiments to comprehensively evaluate post-hoc calibration methods, finding that smooth calibration function…

The paper proposes CAGE-CAL, a counterfactual graph calibration framework, to accurately assess the reliability and detect over-confidence in multi-agent LLM systems after agents communicate.

This paper evaluates the effectiveness of Bayesian workflow for verifying statistical correctness of probabilistic programs written by language models, and compares it to unit tests and no feedback.

This paper studies the behavior of mixture-of-experts (MoE) models under distribution shift and proposes an adversarial reweighting method to improve their calibration.

The paper formalizes the concept of calibration for probabilistic label ranking, demonstrating that popular models are often poorly calibrated and that calibration captures a meaningful quality dimens…

This paper introduces Reliability-Aware Prototype Calibration (RPC), a post-hoc score calibration method for pose-flow video anomaly detectors in a frozen-detector setting.

Low-Pass Flow Matching introduces a spectral bias into the flow matching process, allowing it to better model natural data by transitioning from a standard source spectrum to a frequency-decaying bias…

The paper introduces FORCEBENCH, a new stress test designed to evaluate whether cited sources genuinely warrant the strength of a claim, revealing that standard citation evaluation methods often fail…

This paper introduces Camera-Centric VLA, a new model for Vision-Language-Action policies that predicts camera-centric actions and hand-eye matrix, allowing the policy to figure out camera geometry on…

This paper compares the downlink spectral efficiency of multi-user large antenna systems with global and local calibration approaches, and demonstrates that global calibration outperforms local calibr…

This paper proposes a simple real-time monitor for LLMs that turns an external verifier signal into an alarm decision by thresholding, showing competitiveness with advanced monitors in mathematical re…

This paper proposes a framework for on-site calibration of Reconfigurable Intelligent Surface (RIS) beam response models to reduce positioning error floor.

CALIBURN introduces a novel, five-component streaming pipeline for intrusion detection that allows operators to specify alerting behavior using cost and budget constraints, achieving state-of-the-art…

The paper identifies a fundamental mismatch between standard pairwise ranking metrics (like AP and FPR-95) and the true assignment objective in multi-view object association, proposing a Sinkhorn-base…

The paper proposes a novel geometric embedding hashing method to recover object correspondences (vector links) between two embedding clouds generated by different black-box encoders using only a small…

This paper analyzes the effects of calibration errors on downlink beamforming in a repeater-assisted massive MIMO system and derives analytical expressions for the downlink spectral efficiency.