Saved in:
| Main Authors: | Li, Yinghao, Qiang, Rushi, Moukheiber, Lama, Zhang, Chao |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2503.19168 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
EchoQA: A Large Collection of Instruction Tuning Data for Echocardiogram Reports
by: Moukheiber, Lama, et al.
Published: (2025)
by: Moukheiber, Lama, et al.
Published: (2025)
Unmasking Societal Biases in Respiratory Support for ICU Patients through Social Determinants of Health
by: Moukheiber, Mira, et al.
Published: (2025)
by: Moukheiber, Mira, et al.
Published: (2025)
Looking Beyond What You See: An Empirical Analysis on Subgroup Intersectional Fairness for Multi-label Chest X-ray Classification Using Social Determinants of Racial Health Inequities
by: Moukheiber, Dana, et al.
Published: (2024)
by: Moukheiber, Dana, et al.
Published: (2024)
BiLoRA: A Bi-level Optimization Framework for Overfitting-Resilient Low-Rank Adaptation of Large Pre-trained Models
by: Qiang, Rushi, et al.
Published: (2024)
by: Qiang, Rushi, et al.
Published: (2024)
Assessing Logical Puzzle Solving in Large Language Models: Insights from a Minesweeper Case Study
by: Li, Yinghao, et al.
Published: (2023)
by: Li, Yinghao, et al.
Published: (2023)
A Simple but Effective Approach to Improve Structured Language Model Output for Information Extraction
by: Li, Yinghao, et al.
Published: (2024)
by: Li, Yinghao, et al.
Published: (2024)
Recurrent Confidence Chain: Temporal-Aware Uncertainty Quantification in Large Language Models
by: Mao, Zhenjiang, et al.
Published: (2026)
by: Mao, Zhenjiang, et al.
Published: (2026)
Uncertainty Quantification for Large Language Diffusion Models
by: Vazhentsev, Artem, et al.
Published: (2026)
by: Vazhentsev, Artem, et al.
Published: (2026)
Uncertainty-Aware Attention Heads: Efficient Unsupervised Uncertainty Quantification for LLMs
by: Vazhentsev, Artem, et al.
Published: (2025)
by: Vazhentsev, Artem, et al.
Published: (2025)
Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models
by: Chen, Zizhang, et al.
Published: (2024)
by: Chen, Zizhang, et al.
Published: (2024)
Towards Better Instruction Following Retrieval Models
by: Zhuang, Yuchen, et al.
Published: (2025)
by: Zhuang, Yuchen, et al.
Published: (2025)
CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought
by: Zhang, Boxuan, et al.
Published: (2025)
by: Zhang, Boxuan, et al.
Published: (2025)
Uncertainty Quantification for In-Context Learning of Large Language Models
by: Ling, Chen, et al.
Published: (2024)
by: Ling, Chen, et al.
Published: (2024)
SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models
by: Gao, Xiang, et al.
Published: (2024)
by: Gao, Xiang, et al.
Published: (2024)
HYDRA: Model Factorization Framework for Black-Box LLM Personalization
by: Zhuang, Yuchen, et al.
Published: (2024)
by: Zhuang, Yuchen, et al.
Published: (2024)
Shifting Attention to Relevance: Towards the Predictive Uncertainty Quantification of Free-Form Large Language Models
by: Duan, Jinhao, et al.
Published: (2023)
by: Duan, Jinhao, et al.
Published: (2023)
Matryoshka Pilot: Learning to Drive Black-Box LLMs with LLMs
by: Li, Changhao, et al.
Published: (2024)
by: Li, Changhao, et al.
Published: (2024)
Uncertainty Quantification and Confidence Calibration in Large Language Models: A Survey
by: Liu, Xiaoou, et al.
Published: (2025)
by: Liu, Xiaoou, et al.
Published: (2025)
ESI: Epistemic Uncertainty Quantification via Semantic-preserving Intervention for Large Language Models
by: Li, Mingda, et al.
Published: (2025)
by: Li, Mingda, et al.
Published: (2025)
Evaluating Uncertainty Quantification Methods in Argumentative Large Language Models
by: Zhou, Kevin, et al.
Published: (2025)
by: Zhou, Kevin, et al.
Published: (2025)
Prompt-Dependent Ranking of Large Language Models with Uncertainty Quantification
by: Menendez, Angel Rodrigo Avelar, et al.
Published: (2026)
by: Menendez, Angel Rodrigo Avelar, et al.
Published: (2026)
AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning
by: Zhang, Ruiyi, et al.
Published: (2024)
by: Zhang, Ruiyi, et al.
Published: (2024)
The Consistency Hypothesis in Uncertainty Quantification for Large Language Models
by: Xiao, Quan, et al.
Published: (2025)
by: Xiao, Quan, et al.
Published: (2025)
Agentic Uncertainty Quantification
by: Zhang, Jiaxin, et al.
Published: (2026)
by: Zhang, Jiaxin, et al.
Published: (2026)
Inv-Entropy: A Fully Probabilistic Framework for Uncertainty Quantification in Language Models
by: Song, Haoyi, et al.
Published: (2025)
by: Song, Haoyi, et al.
Published: (2025)
TPD: Enhancing Student Language Model Reasoning via Principle Discovery and Guidance
by: Wang, Haorui, et al.
Published: (2024)
by: Wang, Haorui, et al.
Published: (2024)
ProgGen: Generating Named Entity Recognition Datasets Step-by-step with Self-Reflexive Large Language Models
by: Heng, Yuzhao, et al.
Published: (2024)
by: Heng, Yuzhao, et al.
Published: (2024)
Uncertainty Quantification of Large Language Models through Multi-Dimensional Responses
by: Chen, Tiejin, et al.
Published: (2025)
by: Chen, Tiejin, et al.
Published: (2025)
Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models
by: Lin, Zhen, et al.
Published: (2023)
by: Lin, Zhen, et al.
Published: (2023)
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
by: Vashurin, Roman, et al.
Published: (2024)
by: Vashurin, Roman, et al.
Published: (2024)
Uncertainty Quantification in Large Language Models Through Convex Hull Analysis
by: Catak, Ferhat Ozgur, et al.
Published: (2024)
by: Catak, Ferhat Ozgur, et al.
Published: (2024)
COPU: Conformal Prediction for Uncertainty Quantification in Natural Language Generation
by: Wang, Sean, et al.
Published: (2025)
by: Wang, Sean, et al.
Published: (2025)
Uncertainty Quantification for Hallucination Detection in Large Language Models: Foundations, Methodology, and Future Directions
by: Kang, Sungmin, et al.
Published: (2025)
by: Kang, Sungmin, et al.
Published: (2025)
LUQ: Long-text Uncertainty Quantification for LLMs
by: Zhang, Caiqi, et al.
Published: (2024)
by: Zhang, Caiqi, et al.
Published: (2024)
SIMBA UQ: Similarity-Based Aggregation for Uncertainty Quantification in Large Language Models
by: Bhattacharjya, Debarun, et al.
Published: (2025)
by: Bhattacharjya, Debarun, et al.
Published: (2025)
URAG: A Benchmark for Uncertainty Quantification in Retrieval-Augmented Large Language Models
by: Nguyen, Vinh, et al.
Published: (2026)
by: Nguyen, Vinh, et al.
Published: (2026)
Token-Level Density-Based Uncertainty Quantification Methods for Eliciting Truthfulness of Large Language Models
by: Vazhentsev, Artem, et al.
Published: (2025)
by: Vazhentsev, Artem, et al.
Published: (2025)
Exploring the Impact of Temperature on Large Language Models:Hot or Cold?
by: Li, Lujun, et al.
Published: (2025)
by: Li, Lujun, et al.
Published: (2025)
UQLM: A Python Package for Uncertainty Quantification in Large Language Models
by: Bouchard, Dylan, et al.
Published: (2025)
by: Bouchard, Dylan, et al.
Published: (2025)
Semantic Token Clustering for Efficient Uncertainty Quantification in Large Language Models
by: Cao, Qi, et al.
Published: (2026)
by: Cao, Qi, et al.
Published: (2026)
Similar Items
-
EchoQA: A Large Collection of Instruction Tuning Data for Echocardiogram Reports
by: Moukheiber, Lama, et al.
Published: (2025) -
Unmasking Societal Biases in Respiratory Support for ICU Patients through Social Determinants of Health
by: Moukheiber, Mira, et al.
Published: (2025) -
Looking Beyond What You See: An Empirical Analysis on Subgroup Intersectional Fairness for Multi-label Chest X-ray Classification Using Social Determinants of Racial Health Inequities
by: Moukheiber, Dana, et al.
Published: (2024) -
BiLoRA: A Bi-level Optimization Framework for Overfitting-Resilient Low-Rank Adaptation of Large Pre-trained Models
by: Qiang, Rushi, et al.
Published: (2024) -
Assessing Logical Puzzle Solving in Large Language Models: Insights from a Minesweeper Case Study
by: Li, Yinghao, et al.
Published: (2023)