Copertina

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Li, Miaomiao, Chen, Hao, Wang, Yang, Zhu, Tingyuan, Zhang, Weijia, Zhu, Kaijie, Wong, Kam-Fai, Wang, Jindong
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence Computation and Language
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Counterspeech for Mitigating the Influence of Media Bias: Comparing Human and LLM-Generated Responses
di: Lin, Luyang, et al.
Pubblicazione: (2025)

CompeteAI: Understanding the Competition Dynamics in Large Language Model-based Agents
di: Zhao, Qinlin, et al.
Pubblicazione: (2023)

A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Models
di: Wang, Hongru, et al.
Pubblicazione: (2023)

DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks
di: Zhu, Kaijie, et al.
Pubblicazione: (2023)

PromptBench: A Unified Library for Evaluation of Large Language Models
di: Zhu, Kaijie, et al.
Pubblicazione: (2023)

Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks
di: Chen, Hao, et al.
Pubblicazione: (2023)

Dynamic Evaluation of Large Language Models by Meta Probing Agents
di: Zhu, Kaijie, et al.
Pubblicazione: (2024)

UniMS-RAG: A Unified Multi-source Retrieval-Augmented Generation for Personalized Dialogue Systems
di: Wang, Hongru, et al.
Pubblicazione: (2024)

UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation
di: Zhou, Hanzhang, et al.
Pubblicazione: (2024)

Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models
di: Wang, Lingzhi, et al.
Pubblicazione: (2024)

AgentReview: Exploring Peer Review Dynamics with LLM Agents
di: Jin, Yiqiao, et al.
Pubblicazione: (2024)

Routing-Aligned Fine-Tuning for Multilingual Downstream Tasks in Mixture-of-Experts Models
di: Deng, Guanzhi, et al.
Pubblicazione: (2026)

LLM-Guided Synthetic Augmentation (LGSA) for Mitigating Bias in AI Systems
di: Karri, Sai Suhruth Reddy, et al.
Pubblicazione: (2025)

A GAN and LLM-Driven Data Augmentation Framework for Dynamic Linguistic Pattern Modeling in Chinese Sarcasm Detection
di: Wang, Wenxian, et al.
Pubblicazione: (2026)

Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models
di: Wang, Rui, et al.
Pubblicazione: (2025)

IndiVec: An Exploration of Leveraging Large Language Models for Media Bias Detection with Fine-Grained Bias Indicators
di: Lin, Luyang, et al.
Pubblicazione: (2024)

OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst
di: Cao, Jingtao, et al.
Pubblicazione: (2024)

Evaluating LLM-based Agents for Multi-Turn Conversations: A Survey
di: Guan, Shengyue, et al.
Pubblicazione: (2025)

WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentation
di: Zhao, Zhengyi, et al.
Pubblicazione: (2025)

Learning from "Silly" Questions Improves Large Language Models, But Only Slightly
di: Zhu, Tingyuan, et al.
Pubblicazione: (2024)

Mitigating Translationese Bias in Multilingual LLM-as-a-Judge via Disentangled Information Bottleneck
di: Zhang, Hongbin, et al.
Pubblicazione: (2026)

Context-Aware Counterfactual Data Augmentation for Gender Bias Mitigation in Language Models
di: Parihar, Shweta, et al.
Pubblicazione: (2026)

TrustJudge: Inconsistencies of LLM-as-a-Judge and How to Alleviate Them
di: Wang, Yidong, et al.
Pubblicazione: (2025)

BRIDGE the Gap: Mitigating Bias Amplification in Automated Scoring of English Language Learners via Inter-group Data Augmentation
di: Wang, Yun, et al.
Pubblicazione: (2026)

FedEval-LLM: Federated Evaluation of Large Language Models on Downstream Tasks with Collective Wisdom
di: He, Yuanqin, et al.
Pubblicazione: (2024)

Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement
di: Xu, Wenda, et al.
Pubblicazione: (2024)

Mitigating Biases of Large Language Models in Stance Detection with Counterfactual Augmented Calibration
di: Li, Ang, et al.
Pubblicazione: (2024)

On Catastrophic Inheritance of Large Foundation Models
di: Chen, Hao, et al.
Pubblicazione: (2024)

Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
di: Dong, Guanting, et al.
Pubblicazione: (2024)

HyperbolicRAG: Enhancing Retrieval-Augmented Generation with Hyperbolic Representations
di: Cao, Linxiao, et al.
Pubblicazione: (2025)

Quantifying and Mitigating Self-Preference Bias of LLM Judges
di: Yang, Jinming, et al.
Pubblicazione: (2026)

Understanding and Mitigating Tokenization Bias in Language Models
di: Phan, Buu, et al.
Pubblicazione: (2024)

LLM-Driven Multi-Turn Task-Oriented Dialogue Synthesis for Realistic Reasoning
di: Zhu, Yu, et al.
Pubblicazione: (2026)

Anchor-based Large Language Models
di: Pang, Jianhui, et al.
Pubblicazione: (2024)

VLEU: a Method for Automatic Evaluation for Generalizability of Text-to-Image Models
di: Cao, Jingtao, et al.
Pubblicazione: (2024)

A Survey on Evaluation of Large Language Models
di: Chang, Yupeng, et al.
Pubblicazione: (2023)

CyclicJudge: Mitigating Judge Bias Efficiently in LLM-based Evaluation
di: Zhu, Ziyi, et al.
Pubblicazione: (2026)

Self-Guard: Empower the LLM to Safeguard Itself
di: Wang, Zezhong, et al.
Pubblicazione: (2023)

Detecting and Mitigating Bias in LLMs through Knowledge Graph-Augmented Training
di: Kumar, Rajeev, et al.
Pubblicazione: (2025)

PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering
di: Du, Yiming, et al.
Pubblicazione: (2024)