Saved in:
| Main Authors: | Tao, Linwei, Luo, Haoyang, Dong, Minjing, Xu, Chang |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2603.22879 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors
by: Tao, Linwei, et al.
Published: (2024)
by: Tao, Linwei, et al.
Published: (2024)
A Benchmark Study on Calibration
by: Tao, Linwei, et al.
Published: (2023)
by: Tao, Linwei, et al.
Published: (2023)
Sample Margin-Aware Recalibration of Temperature Scaling
by: Guo, Haolan, et al.
Published: (2025)
by: Guo, Haolan, et al.
Published: (2025)
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
by: Luo, Haoyang, et al.
Published: (2025)
by: Luo, Haoyang, et al.
Published: (2025)
WATS: Calibrating Graph Neural Networks with Wavelet-Aware Temperature Scaling
by: Li, Xiaoyang, et al.
Published: (2025)
by: Li, Xiaoyang, et al.
Published: (2025)
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
by: Lin, Jinxu, et al.
Published: (2024)
by: Lin, Jinxu, et al.
Published: (2024)
Revisiting Uncertainty Estimation and Calibration of Large Language Models
by: Tao, Linwei, et al.
Published: (2025)
by: Tao, Linwei, et al.
Published: (2025)
Feature Clipping for Uncertainty Calibration
by: Tao, Linwei, et al.
Published: (2024)
by: Tao, Linwei, et al.
Published: (2024)
Uncertainty Weighted Gradients for Model Calibration
by: Lin, Jinxu, et al.
Published: (2025)
by: Lin, Jinxu, et al.
Published: (2025)
Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
by: Zhu, Younan, et al.
Published: (2025)
by: Zhu, Younan, et al.
Published: (2025)
Combining Priors with Experience: Confidence Calibration Based on Binomial Process Modeling
by: Dong, Jinzong, et al.
Published: (2024)
by: Dong, Jinzong, et al.
Published: (2024)
Your Pre-trained LLM is Secretly an Unsupervised Confidence Calibrator
by: Luo, Beier, et al.
Published: (2025)
by: Luo, Beier, et al.
Published: (2025)
Confidence Calibration in Large Language Models
by: Michael, Noam, et al.
Published: (2026)
by: Michael, Noam, et al.
Published: (2026)
Confidence Calibration of Classifiers with Many Classes
by: LeCoz, Adrien, et al.
Published: (2024)
by: LeCoz, Adrien, et al.
Published: (2024)
Learning Quantifiable Visual Explanations Without Ground-Truth
by: Singh, Amritpal, et al.
Published: (2026)
by: Singh, Amritpal, et al.
Published: (2026)
Synthetic Data and the Shifting Ground of Truth
by: Offenhuber, Dietmar
Published: (2025)
by: Offenhuber, Dietmar
Published: (2025)
Privacy Reasoning in Ambiguous Contexts
by: Yi, Ren, et al.
Published: (2025)
by: Yi, Ren, et al.
Published: (2025)
GT-Space: Enhancing Heterogeneous Collaborative Perception with Ground Truth Feature Space
by: Wang, Wentao, et al.
Published: (2026)
by: Wang, Wentao, et al.
Published: (2026)
Fairness Evaluation for Uplift Modeling in the Absence of Ground Truth
by: Kadioglu, Serdar, et al.
Published: (2024)
by: Kadioglu, Serdar, et al.
Published: (2024)
Ranking Large Language Models without Ground Truth
by: Dhurandhar, Amit, et al.
Published: (2024)
by: Dhurandhar, Amit, et al.
Published: (2024)
Evaluating Model Explanations without Ground Truth
by: Rawal, Kaivalya, et al.
Published: (2025)
by: Rawal, Kaivalya, et al.
Published: (2025)
Illusions of Confidence? Diagnosing LLM Truthfulness via Neighborhood Consistency
by: Xu, Haoming, et al.
Published: (2026)
by: Xu, Haoming, et al.
Published: (2026)
BEVDiffuser: Plug-and-Play Diffusion Model for BEV Denoising with Ground-Truth Guidance
by: Ye, Xin, et al.
Published: (2025)
by: Ye, Xin, et al.
Published: (2025)
How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence
by: Du, Hongzhe, et al.
Published: (2025)
by: Du, Hongzhe, et al.
Published: (2025)
xaitimesynth: A Python Package for Evaluating Attribution Methods for Time Series with Synthetic Ground Truth
by: Baer, Gregor
Published: (2026)
by: Baer, Gregor
Published: (2026)
Variance-Bounded Evaluation of Entity-Centric AI Systems Without Ground Truth: Theory and Measurement
by: Ding, Kaihua
Published: (2025)
by: Ding, Kaihua
Published: (2025)
Conformalized Credal Regions for Classification with Ambiguous Ground Truth
by: Caprio, Michele, et al.
Published: (2024)
by: Caprio, Michele, et al.
Published: (2024)
CALICO: Confident Active Learning with Integrated Calibration
by: Querol, Lorenzo S., et al.
Published: (2024)
by: Querol, Lorenzo S., et al.
Published: (2024)
MICE for CATs: Model-Internal Confidence Estimation for Calibrating Agents with Tools
by: Subramani, Nishant, et al.
Published: (2025)
by: Subramani, Nishant, et al.
Published: (2025)
Calibrating Bayesian Learning via Regularization, Confidence Minimization, and Selective Inference
by: Huang, Jiayi, et al.
Published: (2024)
by: Huang, Jiayi, et al.
Published: (2024)
Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical Argumentation
by: Shi, Minjing, et al.
Published: (2026)
by: Shi, Minjing, et al.
Published: (2026)
TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning
by: Wei, Zhepei, et al.
Published: (2025)
by: Wei, Zhepei, et al.
Published: (2025)
From Ground Truth to Measurement: A Statistical Framework for Human Labeling
by: Chew, Robert, et al.
Published: (2026)
by: Chew, Robert, et al.
Published: (2026)
Margin-Adaptive Confidence Ranking for Reliable LLM Judgement
by: Jin, Gaojie, et al.
Published: (2026)
by: Jin, Gaojie, et al.
Published: (2026)
Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
by: Sim, Rachael Hwee Ling, et al.
Published: (2026)
by: Sim, Rachael Hwee Ling, et al.
Published: (2026)
Graph-based Confidence Calibration for Large Language Models
by: Li, Yukun, et al.
Published: (2024)
by: Li, Yukun, et al.
Published: (2024)
Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards
by: Ma, Zhengzhao, et al.
Published: (2026)
by: Ma, Zhengzhao, et al.
Published: (2026)
SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration
by: Wen, Zhuofan, et al.
Published: (2026)
by: Wen, Zhuofan, et al.
Published: (2026)
When Bias Pretends to Be Truth: How Spurious Correlations Undermine Hallucination Detection in LLMs
by: Wang, Shaowen, et al.
Published: (2025)
by: Wang, Shaowen, et al.
Published: (2025)
MCNet: Monotonic Calibration Networks for Expressive Uncertainty Calibration in Online Advertising
by: Dai, Quanyu, et al.
Published: (2025)
by: Dai, Quanyu, et al.
Published: (2025)
Similar Items
-
Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors
by: Tao, Linwei, et al.
Published: (2024) -
A Benchmark Study on Calibration
by: Tao, Linwei, et al.
Published: (2023) -
Sample Margin-Aware Recalibration of Temperature Scaling
by: Guo, Haolan, et al.
Published: (2025) -
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
by: Luo, Haoyang, et al.
Published: (2025) -
WATS: Calibrating Graph Neural Networks with Wavelet-Aware Temperature Scaling
by: Li, Xiaoyang, et al.
Published: (2025)