Cover Image

Bias Amplification in Language Model Evolution: An Iterated Learning Perspective

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Ren, Yi, Guo, Shangmin, Qiu, Linlu, Wang, Bailin, Sutherland, Danica J.
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Learning Dynamics of LLM Finetuning
by: Ren, Yi, et al.
Published: (2024)

Understanding Simplicity Bias towards Compositional Mappings via Learning Dynamics
by: Ren, Yi, et al.
Published: (2024)

Decoding-time Realignment of Language Models
by: Liu, Tianlin, et al.
Published: (2024)

Lookback Lens: Detecting and Mitigating Contextual Hallucinations in Large Language Models Using Only Attention Maps
by: Chuang, Yung-Sung, et al.
Published: (2024)

The Surprising Effectiveness of Test-Time Training for Few-Shot Learning
by: Akyürek, Ekin, et al.
Published: (2024)

ELF: Embedded Language Flows
by: Hu, Keya, et al.
Published: (2026)

Understanding and Mitigating Spurious Signal Amplification in Test-Time Reinforcement Learning for Math Reasoning
by: Yu, Yongcan, et al.
Published: (2026)

Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models
by: Tang, Haoyu, et al.
Published: (2024)

Instruction Learning Paradigms: A Dual Perspective on White-box and Black-box LLMs
by: Ren, Yanwei, et al.
Published: (2025)

Iterative Learning of Computable Phenotypes for Treatment Resistant Hypertension using Large Language Models
by: Aldeia, Guilherme Seidyo Imai, et al.
Published: (2025)

Sociodemographic Bias in Language Models: A Survey and Forward Path
by: Gupta, Vipul, et al.
Published: (2023)

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

Diagnosing Retrieval Bias Under Multiple In-Context Knowledge Updates in Large Language Models
by: Qiao, Boyu, et al.
Published: (2026)

GPTQT: Quantize Large Language Models Twice to Push the Efficiency
by: Guo, Yipin, et al.
Published: (2024)

A Meta-Learning Perspective on Transformers for Causal Language Modeling
by: Wu, Xinbo, et al.
Published: (2023)

Benefits and Pitfalls of Reinforcement Learning for Language Model Planning: A Theoretical Perspective
by: Wang, Siwei, et al.
Published: (2025)

More Thinking, More Bias: Length-Driven Position Bias in Reasoning Models
by: Wang, Xiao
Published: (2026)

Having Beer after Prayer? Measuring Cultural Bias in Large Language Models
by: Naous, Tarek, et al.
Published: (2023)

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks
by: Wu, Zhaofeng, et al.
Published: (2023)

CALM : A Multi-task Benchmark for Comprehensive Assessment of Language Model Bias
by: Gupta, Vipul, et al.
Published: (2023)

ToolACE-R: Model-aware Iterative Training and Adaptive Refinement for Tool Learning
by: Zeng, Xingshan, et al.
Published: (2025)

Convergent Evolution: How Different Language Models Learn Similar Number Representations
by: Fu, Deqing, et al.
Published: (2026)

BIPEFT: Budget-Guided Iterative Search for Parameter Efficient Fine-Tuning of Large Pretrained Language Models
by: Chang, Aofei, et al.
Published: (2024)

Soft-prompt Tuning for Large Language Models to Evaluate Bias
by: Tian, Jacob-Junqi, et al.
Published: (2023)

Attention Speaks Volumes: Localizing and Mitigating Bias in Language Models
by: Adiga, Rishabh, et al.
Published: (2024)

DEBATE, TRAIN, EVOLVE: Self Evolution of Language Model Reasoning
by: Srivastava, Gaurav, et al.
Published: (2025)

Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
by: Siddique, Zara, et al.
Published: (2025)

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement
by: Qiu, Linlu, et al.
Published: (2023)

Investigating Annotator Bias in Large Language Models for Hate Speech Detection
by: Das, Amit, et al.
Published: (2024)

CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment
by: Guo, Siyuan, et al.
Published: (2026)

Explicit Multi-head Attention for Inter-head Interaction in Large Language Models
by: Peng, Runyu, et al.
Published: (2026)

Unlocking Continual Learning Abilities in Language Models
by: Du, Wenyu, et al.
Published: (2024)

Iterative Mask Filling: An Effective Text Augmentation Method Using Masked Language Modeling
by: Kesgin, Himmet Toprak, et al.
Published: (2024)

Promote, Suppress, Iterate: How Language Models Answer One-to-Many Factual Queries
by: Yan, Tianyi Lorena, et al.
Published: (2025)

SELF: Self-Evolution with Language Feedback
by: Lu, Jianqiao, et al.
Published: (2023)

BiasFreeBench: a Benchmark for Mitigating Bias in Large Language Model Responses
by: Xu, Xin, et al.
Published: (2025)

Position Engineering: Boosting Large Language Models through Positional Information Manipulation
by: He, Zhiyuan, et al.
Published: (2024)

D$^2$Evo: Dual Difficulty-Aware Self-Evolution for Data-Efficient Reinforcement Learning
by: Zhang, Ru, et al.
Published: (2026)

Mitigating Selection Bias in Large Language Models via Permutation-Aware GRPO
by: Zheng, Jinquan, et al.
Published: (2026)

BEFT: Bias-Efficient Fine-Tuning of Language Models in Low-Data Regimes
by: Huang, Baichuan, et al.
Published: (2025)