Imagen de Portada

Stackelberg Self-Annotation: A Robust Approach to Data-Efficient LLM Alignment

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Chu, Xu, Zhang, Zhixin, Jia, Tianyu, Jin, Yujie
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Data Selection for LLM Alignment Using Fine-Grained Preferences
por: Zhang, Jia, et al.
Publicado: (2025)

Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment
por: Kim, Dongyoung, et al.
Publicado: (2024)

Reward Shaping for Inference-Time Alignment: A Stackelberg Game Perspective
por: Wang, Haichuan, et al.
Publicado: (2026)

Convergence Acceleration in Wireless Federated Learning: A Stackelberg Game Approach
por: Wang, Kaidi, et al.
Publicado: (2022)

PluralLLM: Pluralistic Alignment in LLMs via Federated Learning
por: Srewa, Mahmoud, et al.
Publicado: (2025)

Robust LLM Alignment via Distributionally Robust Direct Preference Optimization
por: Xu, Zaiyan, et al.
Publicado: (2025)

DrugSAGE:Self-evolving Agent Experience for Efficient State-of-the-Art Drug Discovery
por: Zhang, Yikun, et al.
Publicado: (2026)

Conformal Thresholded Intervals for Efficient Regression
por: Luo, Rui, et al.
Publicado: (2024)

Adversarial Preference Learning for Robust LLM Alignment
por: Wang, Yuanfu, et al.
Publicado: (2025)

SMART: Towards Pre-trained Missing-Aware Model for Patient Health Status Prediction
por: Yu, Zhihao, et al.
Publicado: (2024)

Robust Reward Alignment via Hypothesis Space Batch Cutting
por: Xie, Zhixian, et al.
Publicado: (2025)

Unsupervised Conformal Inference: Bootstrapping and Alignment to Control LLM Uncertainty
por: Pang, Lingyou, et al.
Publicado: (2025)

Data-Centric Human Preference with Rationales for Direct Preference Alignment
por: Just, Hoang Anh, et al.
Publicado: (2024)

D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning
por: Zhang, Jia, et al.
Publicado: (2025)

IntelliCare: Improving Healthcare Analysis with Variance-Controlled Patient-Level Knowledge from Large Language Models
por: Yu, Zhihao, et al.
Publicado: (2024)

From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
por: Chen, Hao, et al.
Publicado: (2026)

Volume-Sorted Prediction Set: Efficient Conformal Prediction for Multi-Target Regression
por: Luo, Rui, et al.
Publicado: (2025)

SCAN: Self-Denoising Monte Carlo Annotation for Robust Process Reward Learning
por: Ding, Yuyang, et al.
Publicado: (2025)

ALMA: Alignment with Minimal Annotation
por: Yasunaga, Michihiro, et al.
Publicado: (2024)

Conformal Feedback Alignment: Quantifying Answer-Level Reliability for Robust LLM Alignment
por: Chen, Tiejin, et al.
Publicado: (2026)

Adaptive Ensembles of Fine-Tuned Transformers for LLM-Generated Text Detection
por: Lai, Zhixin, et al.
Publicado: (2024)

Online Distributionally Robust LLM Alignment via Regression to Relative Reward
por: Sahu, Sharan, et al.
Publicado: (2025)

Revisiting Robustness for LLM Safety Alignment via Selective Geometry Control
por: Yang, Yonghui, et al.
Publicado: (2026)

Multimodal-Guided Dynamic Dataset Pruning for Robust and Efficient Data-Centric Learning
por: Yang, Suorong, et al.
Publicado: (2025)

Rubric-Conditioned LLM Grading: Alignment, Uncertainty, and Robustness
por: Deng, Haotian, et al.
Publicado: (2025)

Contextual Optimization under Covariate Shift: A Robust Approach by Intersecting Wasserstein Balls
por: Wang, Tianyu, et al.
Publicado: (2024)

Reducing the Safety Tax in LLM Safety Alignment with On-Policy Self-Distillation
por: Fu, Yu, et al.
Publicado: (2026)

Prior-Informed Zeroth-Order Optimization with Adaptive Direction Alignment for Memory-Efficient LLM Fine-Tuning
por: Jin, Feihu, et al.
Publicado: (2026)

LLM Chain Ensembles for Scalable and Accurate Data Annotation
por: Farr, David, et al.
Publicado: (2024)

Rethinking Neural Network Learning Rates: A Stackelberg Perspective
por: Zeng, Sihan, et al.
Publicado: (2026)

TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety Alignment
por: Tan, Zhewen, et al.
Publicado: (2026)

Meta Stackelberg Game: Robust Federated Learning against Adaptive and Mixed Poisoning Attacks
por: Li, Tao, et al.
Publicado: (2024)

CluCERT: Certifying LLM Robustness via Clustering-Guided Denoising Smoothing
por: Wang, Zixia, et al.
Publicado: (2025)

AnnotatedTables: A Large Tabular Dataset with Language Model Annotations
por: Hu, Yaojie, et al.
Publicado: (2024)

Weakly Supervised Anomaly Detection via Knowledge-Data Alignment
por: Zhao, Haihong, et al.
Publicado: (2024)

Gradient Compression May Hurt Generalization: A Remedy by Synthetic Data Guided Sharpness Aware Minimization
por: Gu, Yujie, et al.
Publicado: (2026)

RobustExplain: Evaluating Robustness of LLM-Based Explanation Agents for Recommendation
por: Zhang, Guilin, et al.
Publicado: (2026)

Advantage Alignment Algorithms
por: Duque, Juan Agustin, et al.
Publicado: (2024)

Align-Pro: A Principled Approach to Prompt Optimization for LLM Alignment
por: Trivedi, Prashant, et al.
Publicado: (2025)

Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment
por: Xie, Huanyi, et al.
Publicado: (2025)