Imagen de Portada

Do Retrieval-Augmented Language Models Adapt to Varying User Needs?

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Wu, Peilin, Zhang, Xinlu, Yu, Wenhao, Liu, Xingyu, Du, Xinya, Chen, Zhiyu Zoey
Formato:	Preprint
Publicado:	2025
Materias:	Computation and Language Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Search Wisely: Mitigating Sub-optimal Agentic Searches By Reducing Uncertainty
por: Wu, Peilin, et al.
Publicado: (2025)

AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning
por: Wu, Peilin, et al.
Publicado: (2026)

HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation
por: Wu, Peilin, et al.
Publicado: (2025)

IDEA: Enhancing the Rule Learning Ability of Large Language Model Agent through Induction, Deduction, and Abduction
por: He, Kaiyu, et al.
Publicado: (2024)

GEAR: A General Evaluation Framework for Abductive Reasoning
por: He, Kaiyu, et al.
Publicado: (2025)

Is Grokking Worthwhile? Functional Analysis and Transferability of Generalization Circuits in Transformers
por: He, Kaiyu, et al.
Publicado: (2026)

Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning
por: Zhang, Xinlu, et al.
Publicado: (2024)

Logits are All We Need to Adapt Closed Models
por: Hiranandani, Gaurush, et al.
Publicado: (2025)

SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
por: Xu, Ran, et al.
Publicado: (2024)

MLR-Copilot: Autonomous Machine Learning Research based on Large Language Models Agents
por: Li, Ruochen, et al.
Publicado: (2024)

Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
por: Yu, Wenhao, et al.
Publicado: (2023)

RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models
por: Huang, Jie, et al.
Publicado: (2023)

Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
por: Gan, Chunjing, et al.
Publicado: (2024)

CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy
por: Zhang, Mian, et al.
Publicado: (2024)

ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks
por: Yu, Xiaodong, et al.
Publicado: (2023)

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

Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
por: Yang, Shiping, et al.
Publicado: (2025)

Do Retrieval Augmented Language Models Know When They Don't Know?
por: Zhou, Youchao, et al.
Publicado: (2025)

Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models
por: Wang, Fei, et al.
Publicado: (2024)

PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
por: Li, Ruosen, et al.
Publicado: (2023)

Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models
por: Peng, Zhiyuan, et al.
Publicado: (2023)

Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching
por: Li, Xiaodi, et al.
Publicado: (2026)

Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
por: Jeong, Soyeong, et al.
Publicado: (2024)

Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
por: Prahlad, Deeksha, et al.
Publicado: (2025)

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

Learning Retrieval Augmentation for Personalized Dialogue Generation
por: Huang, Qiushi, et al.
Publicado: (2024)

Lugha-Llama: Adapting Large Language Models for African Languages
por: Buzaaba, Happy, et al.
Publicado: (2025)

Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications
por: Zhang, Yanxiang, et al.
Publicado: (2025)

LLM-Match: An Open-Sourced Patient Matching Model Based on Large Language Models and Retrieval-Augmented Generation
por: Li, Xiaodi, et al.
Publicado: (2025)

Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models
por: Islam, Shayekh Bin, et al.
Publicado: (2024)

Do Large Language Models Need a Content Delivery Network?
por: Cheng, Yihua, et al.
Publicado: (2024)

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

Do We Need Frontier Models to Verify Mathematical Proofs?
por: Naik, Aaditya, et al.
Publicado: (2026)

Large Language Model Augmented Exercise Retrieval for Personalized Language Learning
por: Xu, Austin, et al.
Publicado: (2024)

Listen to the Context: Towards Faithful Large Language Models for Retrieval Augmented Generation on Climate Questions
por: Thulke, David, et al.
Publicado: (2025)

Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Models
por: Zhang, Bryan, et al.
Publicado: (2024)

Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs
por: Tang, Xiaqiang, et al.
Publicado: (2024)

Adaptive Guidance for Retrieval-Augmented Masked Diffusion Models
por: Kim, Jaemin, et al.
Publicado: (2026)

RE-Adapt: Reverse Engineered Adaptation of Large Language Models
por: Fleshman, William, et al.
Publicado: (2024)

Domain-Adapted Small Language Models for Reliable Clinical Triage
por: Aljohani, Manar, et al.
Publicado: (2026)