Imagen de Portada

CatRAG: Functor-Guided Structural Debiasing with Retrieval Augmentation for Fair LLMs

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Ranjan, Ravi, Grover, Utkarsh, Akewar, Mayur, Lin, Xiaomin, Polyzou, Agoritsa
Formato:	Preprint
Publicado:	2026
Materias:	Computation and Language Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Position: LLMs Must Use Functor-Based and RAG-Driven Bias Mitigation for Fairness
por: Ranjan, Ravi, et al.
Publicado: (2026)

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs
por: Ranjan, Ravi, et al.
Publicado: (2026)

RAZOR: Ratio-Aware Layer Editing for Targeted Unlearning in Vision Transformers and Diffusion Models
por: Ranjan, Ravi, et al.
Publicado: (2026)

G-Drift MIA: Membership Inference via Gradient-Induced Feature Drift in LLMs
por: Ranjan, Ravi, et al.
Publicado: (2026)

VLA-Forget: Vision-Language-Action Unlearning for Embodied Foundation Models
por: Ranjan, Ravi, et al.
Publicado: (2026)

REBot: From RAG to CatRAG with Semantic Enrichment and Graph Routing
por: Ma, Thanh, et al.
Publicado: (2025)

Social Debiasing for Fair Multi-modal LLMs
por: Cheng, Harry, et al.
Publicado: (2024)

Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation
por: Kim, To Eun, et al.
Publicado: (2024)

LongRAG: Enhancing Retrieval-Augmented Generation with Long-context LLMs
por: Jiang, Ziyan, et al.
Publicado: (2024)

AttentionRAG: Attention-Guided Context Pruning in Retrieval-Augmented Generation
por: Fang, Yixiong, et al.
Publicado: (2025)

Embodied Foundation Models at the Edge: A Survey of Deployment Constraints and Mitigation Strategies
por: Grover, Utkarsh, et al.
Publicado: (2026)

KORAL: Knowledge Graph Guided LLM Reasoning for SSD Operational Analysis
por: Akewar, Mayur, et al.
Publicado: (2026)

DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation
por: Chu, Rui, et al.
Publicado: (2026)

RAG in the Wild: On the (In)effectiveness of LLMs with Mixture-of-Knowledge Retrieval Augmentation
por: Xu, Ran, et al.
Publicado: (2025)

RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
por: Liu, Wanlong, et al.
Publicado: (2024)

A Comprehensive Survey of Retrieval-Augmented Generation (RAG): Evolution, Current Landscape and Future Directions
por: Gupta, Shailja, et al.
Publicado: (2024)

TaSR-RAG: Taxonomy-guided Structured Reasoning for Retrieval-Augmented Generation
por: Sun, Jiashuo, et al.
Publicado: (2026)

DuetRAG: Collaborative Retrieval-Augmented Generation
por: Jiao, Dian, et al.
Publicado: (2024)

CBR-RAG: Case-Based Reasoning for Retrieval Augmented Generation in LLMs for Legal Question Answering
por: Wiratunga, Nirmalie, et al.
Publicado: (2024)

RAG LLMs are Not Safer: A Safety Analysis of Retrieval-Augmented Generation for Large Language Models
por: An, Bang, et al.
Publicado: (2025)

CLI-RAG: A Retrieval-Augmented Framework for Clinically Structured and Context Aware Text Generation with LLMs
por: Keerthana, Garapati, et al.
Publicado: (2025)

Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs
por: Rezaei, Mohammad Reza, et al.
Publicado: (2025)

Class-RAG: Real-Time Content Moderation with Retrieval Augmented Generation
por: Chen, Jianfa, et al.
Publicado: (2024)

LaRA: Benchmarking Retrieval-Augmented Generation and Long-Context LLMs -- No Silver Bullet for LC or RAG Routing
por: Li, Kuan, et al.
Publicado: (2025)

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

GEM-RAG: Graphical Eigen Memories For Retrieval Augmented Generation
por: Rappazzo, Brendan Hogan, et al.
Publicado: (2024)

Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting
por: Wang, Zilong, et al.
Publicado: (2024)

RAG+: Enhancing Retrieval-Augmented Generation with Application-Aware Reasoning
por: Wang, Yu, et al.
Publicado: (2025)

A Survey on RAG Meeting LLMs: Towards Retrieval-Augmented Large Language Models
por: Fan, Wenqi, et al.
Publicado: (2024)

RuleRAG: Rule-Guided Retrieval-Augmented Generation with Language Models for Question Answering
por: Chen, Zhongwu, et al.
Publicado: (2024)

AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
por: Fu, Jia, et al.
Publicado: (2024)

RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs
por: Yu, Yue, et al.
Publicado: (2024)

RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generation
por: Fleischer, Daniel, et al.
Publicado: (2024)

BalanceRAG: Joint Risk Calibration for Cascaded Retrieval-Augmented Generation
por: Jia, Zijun, et al.
Publicado: (2026)

HM-RAG: Hierarchical Multi-Agent Multimodal Retrieval Augmented Generation
por: Liu, Pei, et al.
Publicado: (2025)

ConflictRAG: Detecting and Resolving Knowledge Conflicts in Retrieval Augmented Generation
por: Wang, Chenyu, et al.
Publicado: (2026)

RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement
por: Jiang, Jinhao, et al.
Publicado: (2024)

StackRAG Agent: Improving Developer Answers with Retrieval-Augmented Generation
por: Abrahamyan, Davit, et al.
Publicado: (2024)

Pitfalls of Conversational LLMs on News Debiasing
por: Schlicht, Ipek Baris, et al.
Publicado: (2024)

The Other Side of the Coin: Exploring Fairness in Retrieval-Augmented Generation
por: Zhang, Zheng, et al.
Publicado: (2025)