Copertina

Understanding and Mitigating Tokenization Bias in Language Models

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Phan, Buu, Havasi, Marton, Muckley, Matthew, Ullrich, Karen
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language Artificial Intelligence Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Exact Byte-Level Probabilities from Tokenized Language Models for FIM-Tasks and Model Ensembles
di: Phan, Buu, et al.
Pubblicazione: (2024)

Cross-Tokenizer Likelihood Scoring Algorithms for Language Model Distillation
di: Phan, Buu, et al.
Pubblicazione: (2025)

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

TLPO: Token-Level Policy Optimization for Mitigating Language Confusion in Large Language Models
di: Choo, Jinho, et al.
Pubblicazione: (2026)

Revisiting Graph-Tokenizing Large Language Models: A Systematic Evaluation of Graph Token Understanding
di: Zhang, Zhongjian, et al.
Pubblicazione: (2026)

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

Mitigating Biases for Instruction-following Language Models via Bias Neurons Elimination
di: Yang, Nakyeong, et al.
Pubblicazione: (2023)

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

Understanding and Mitigating Bias Inheritance in LLM-based Data Augmentation on Downstream Tasks
di: Li, Miaomiao, et al.
Pubblicazione: (2025)

Mission Impossible: A Statistical Perspective on Jailbreaking LLMs
di: Su, Jingtong, et al.
Pubblicazione: (2024)

From Concepts to Components: Concept-Agnostic Attention Module Discovery in Transformers
di: Su, Jingtong, et al.
Pubblicazione: (2025)

Reasoning Towards Fairness: Mitigating Bias in Language Models through Reasoning-Guided Fine-Tuning
di: Kabra, Sanchit, et al.
Pubblicazione: (2025)

Mitigating Bias for Question Answering Models by Tracking Bias Influence
di: Ma, Mingyu Derek, et al.
Pubblicazione: (2023)

Token Homogenization under Positional Bias
di: Yusupov, Viacheslav, et al.
Pubblicazione: (2025)

Identifying Features Associated with Bias Against 93 Stigmatized Groups in Language Models and Guardrail Model Safety Mitigation
di: Gueorguieva, Anna-Maria, et al.
Pubblicazione: (2025)

Disentangling Exploration of Large Language Models by Optimal Exploitation
di: Grams, Tim, et al.
Pubblicazione: (2025)

TableRAG: Million-Token Table Understanding with Language Models
di: Chen, Si-An, et al.
Pubblicazione: (2024)

Length-MAX Tokenizer for Language Models
di: Dong, Dong, et al.
Pubblicazione: (2025)

Mitigating Memorization In Language Models
di: Sakarvadia, Mansi, et al.
Pubblicazione: (2024)

Mitigating Extrinsic Gender Bias for Bangla Classification Tasks
di: Joy, Sajib Kumar Saha, et al.
Pubblicazione: (2024)

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

Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
di: Szep, Marton, et al.
Pubblicazione: (2024)

Adapting Language Models via Token Translation
di: Feng, Zhili, et al.
Pubblicazione: (2024)

Counterfactual Token Generation in Large Language Models
di: Chatzi, Ivi, et al.
Pubblicazione: (2024)

Guiding Language Model Reasoning with Planning Tokens
di: Wang, Xinyi, et al.
Pubblicazione: (2023)

AGR: Age Group fairness Reward for Bias Mitigation in LLMs
di: Cao, Shuirong, et al.
Pubblicazione: (2024)

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

Understanding Token Probability Encoding in Output Embeddings
di: Cho, Hakaze, et al.
Pubblicazione: (2024)

Token-Efficient Leverage Learning in Large Language Models
di: Zeng, Yuanhao, et al.
Pubblicazione: (2024)

Language Model Cascades: Token-level uncertainty and beyond
di: Gupta, Neha, et al.
Pubblicazione: (2024)

MoESD: Mixture of Experts Stable Diffusion to Mitigate Gender Bias
di: Wang, Guorun, et al.
Pubblicazione: (2024)

Compositional Steering of Large Language Models with Steering Tokens
di: Radevski, Gorjan, et al.
Pubblicazione: (2026)

Probabilistic Token Alignment for Large Language Model Fusion
di: Zeng, Runjia, et al.
Pubblicazione: (2025)

Specialised or Generic? Tokenization Choices for Radiology Language Models
di: Warr, Hermione, et al.
Pubblicazione: (2025)

Balanced Aggregation: Understanding and Fixing Aggregation Bias in GRPO
di: Zeng, Zhiyuan, et al.
Pubblicazione: (2026)

Understanding and Mitigating the Uncertainty in Zero-Shot Translation
di: Wang, Wenxuan, et al.
Pubblicazione: (2022)

Understanding and Mitigating Dataset Corruption in LLM Steering
di: Anderson, Cullen, et al.
Pubblicazione: (2026)

Does Visual Rendering Bypass Tokenization? Investigating Script-Tokenizer Misalignment in Pixel-Based Language Models
di: Susanto, Lucky, et al.
Pubblicazione: (2026)

Mitigating Degree Bias Adaptively with Hard-to-Learn Nodes in Graph Contrastive Learning
di: Hu, Jingyu, et al.
Pubblicazione: (2025)

What is in a name? Mitigating Name Bias in Text Embeddings via Anonymization
di: Manchanda, Sahil, et al.
Pubblicazione: (2025)