Data Contamination Calibration for Black-box LLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Ye, Wentao, Hu, Jiaqi, Li, Liyao, Wang, Haobo, Chen, Gang, Zhao, Junbo |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Cross-Table Masked Pretraining for Web Data Mining
by: Ye, Chao, et al.
Published: (2023)
by: Ye, Chao, et al.
Published: (2023)
An Invariant Latent Space Perspective on Language Model Inversion
by: Ye, Wentao, et al.
Published: (2025)
by: Ye, Wentao, et al.
Published: (2025)
FLaG: Fine-Grained Latent Grouping for Hallucination Detection
by: Ye, Wentao, et al.
Published: (2026)
by: Ye, Wentao, et al.
Published: (2026)
SPA++: Generalized Graph Spectral Alignment for Versatile Domain Adaptation
by: Xiao, Zhiqing, et al.
Published: (2025)
by: Xiao, Zhiqing, et al.
Published: (2025)
CYCLE-INSTRUCT: Fully Seed-Free Instruction Tuning via Dual Self-Training and Cycle Consistency
by: Shen, Zhanming, et al.
Published: (2025)
by: Shen, Zhanming, et al.
Published: (2025)
From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
by: Chen, Hao, et al.
Published: (2026)
by: Chen, Hao, et al.
Published: (2026)
DREAM: Domain-agnostic Reverse Engineering Attributes of Black-box Model
by: Li, Rongqing, et al.
Published: (2024)
by: Li, Rongqing, et al.
Published: (2024)
TableGPT-R1: Advancing Tabular Reasoning Through Reinforcement Learning
by: Yang, Saisai, et al.
Published: (2025)
by: Yang, Saisai, et al.
Published: (2025)
Towards Robust Incremental Learning under Ambiguous Supervision
by: Wang, Rui, et al.
Published: (2025)
by: Wang, Rui, et al.
Published: (2025)
Supervised Fine-Tuning Needs to Unlock the Potential of Token Priority
by: Shen, Zhanming, et al.
Published: (2026)
by: Shen, Zhanming, et al.
Published: (2026)
Prompt Candidates, then Distill: A Teacher-Student Framework for LLM-driven Data Annotation
by: Xia, Mingxuan, et al.
Published: (2025)
by: Xia, Mingxuan, et al.
Published: (2025)
OpenBox: A Python Toolkit for Generalized Black-box Optimization
by: Jiang, Huaijun, et al.
Published: (2023)
by: Jiang, Huaijun, et al.
Published: (2023)
Instruction Learning Paradigms: A Dual Perspective on White-box and Black-box LLMs
by: Ren, Yanwei, et al.
Published: (2025)
by: Ren, Yanwei, et al.
Published: (2025)
FLoE: Fisher-Based Layer Selection for Efficient Sparse Adaptation of Low-Rank Experts
by: Wang, Xinyi, et al.
Published: (2025)
by: Wang, Xinyi, et al.
Published: (2025)
Unlocking the Black Box: A Five-Dimensional Framework for Evaluating Explainable AI in Credit Risk
by: Ye, Rongbin, et al.
Published: (2025)
by: Ye, Rongbin, et al.
Published: (2025)
Distributed Black-box Attack: Do Not Overestimate Black-box Attacks
by: Wu, Han, et al.
Published: (2022)
by: Wu, Han, et al.
Published: (2022)
DALD: Improving Logits-based Detector without Logits from Black-box LLMs
by: Zeng, Cong, et al.
Published: (2024)
by: Zeng, Cong, et al.
Published: (2024)
Quantifying Data Contamination in Psychometric Evaluations of LLMs
by: Han, Jongwook, et al.
Published: (2025)
by: Han, Jongwook, et al.
Published: (2025)
The Effects of Data Augmentation on Confidence Estimation for LLMs
by: Wang, Rui, et al.
Published: (2025)
by: Wang, Rui, et al.
Published: (2025)
Learning to Correct for QA Reasoning with Black-box LLMs
by: Kim, Jaehyung, et al.
Published: (2024)
by: Kim, Jaehyung, et al.
Published: (2024)
Harnessing Feature Resonance under Arbitrary Target Alignment for Out-of-Distribution Node Detection
by: Yang, Shenzhi, et al.
Published: (2025)
by: Yang, Shenzhi, et al.
Published: (2025)
On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
by: Cai, Yi, et al.
Published: (2023)
by: Cai, Yi, et al.
Published: (2023)
Predicting the Performance of Black-box LLMs through Follow-up Queries
by: Sam, Dylan, et al.
Published: (2025)
by: Sam, Dylan, et al.
Published: (2025)
The Illusion of Reasoning: Exposing Evasive Data Contamination in LLMs via Zero-CoT Truncation
by: Lan, Yifan, et al.
Published: (2026)
by: Lan, Yifan, et al.
Published: (2026)
Traceable Black-box Watermarks for Federated Learning
by: Xu, Jiahao, et al.
Published: (2025)
by: Xu, Jiahao, et al.
Published: (2025)
TableGPT2: A Large Multimodal Model with Tabular Data Integration
by: Su, Aofeng, et al.
Published: (2024)
by: Su, Aofeng, et al.
Published: (2024)
TraPO: A Semi-Supervised Reinforcement Learning Framework for Boosting LLM Reasoning
by: Yang, Shenzhi, et al.
Published: (2025)
by: Yang, Shenzhi, et al.
Published: (2025)
Training-Trajectory-Aware Token Selection
by: Shen, Zhanming, et al.
Published: (2026)
by: Shen, Zhanming, et al.
Published: (2026)
Navigate Complex Physical Worlds via Geometrically Constrained LLM
by: Huang, Yongqiang, et al.
Published: (2024)
by: Huang, Yongqiang, et al.
Published: (2024)
Black-box Optimization with Simultaneous Statistical Inference for Optimal Performance
by: Lian, Teng, et al.
Published: (2025)
by: Lian, Teng, et al.
Published: (2025)
Task-free Adaptive Meta Black-box Optimization
by: Wang, Chao, et al.
Published: (2026)
by: Wang, Chao, et al.
Published: (2026)
Dynamic Black-box Backdoor Attacks on IoT Sensory Data
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025)
by: Chathoth, Ajesh Koyatan, et al.
Published: (2025)
Can LLMs Learn to Reason Robustly under Noisy Supervision?
by: Yang, Shenzhi, et al.
Published: (2026)
by: Yang, Shenzhi, et al.
Published: (2026)
Toward Real-World Table Agents: Capabilities, Workflows, and Design Principles for LLM-based Table Intelligence
by: Tian, Jiaming, et al.
Published: (2025)
by: Tian, Jiaming, et al.
Published: (2025)
Non-collective Calibrating Strategy for Time Series Forecasting
by: Wang, Bin, et al.
Published: (2025)
by: Wang, Bin, et al.
Published: (2025)
Network Threat Detection: Addressing Class Imbalanced Data with Deep Forest
by: Chen, Jiaqi, et al.
Published: (2025)
by: Chen, Jiaqi, et al.
Published: (2025)
When Does Trimming Help Conformal Prediction? A Retained-Law Diagnostic under Calibration Contamination
by: Wang, Congye
Published: (2026)
by: Wang, Congye
Published: (2026)
Improving Black-box Robustness with In-Context Rewriting
by: O'Brien, Kyle, et al.
Published: (2024)
by: O'Brien, Kyle, et al.
Published: (2024)
The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination
by: Sun, Yifan, et al.
Published: (2025)
by: Sun, Yifan, et al.
Published: (2025)
FastBUS: A Fast Bayesian Framework for Unified Weakly-Supervised Learning
by: Wang, Ziquan, et al.
Published: (2026)
by: Wang, Ziquan, et al.
Published: (2026)
Similar Items
-
Towards Cross-Table Masked Pretraining for Web Data Mining
by: Ye, Chao, et al.
Published: (2023) -
An Invariant Latent Space Perspective on Language Model Inversion
by: Ye, Wentao, et al.
Published: (2025) -
FLaG: Fine-Grained Latent Grouping for Hallucination Detection
by: Ye, Wentao, et al.
Published: (2026) -
SPA++: Generalized Graph Spectral Alignment for Versatile Domain Adaptation
by: Xiao, Zhiqing, et al.
Published: (2025) -
CYCLE-INSTRUCT: Fully Seed-Free Instruction Tuning via Dual Self-Training and Cycle Consistency
by: Shen, Zhanming, et al.
Published: (2025)