Do Retrieval-Augmented Language Models Adapt to Varying User Needs?
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Peilin, Zhang, Xinlu, Yu, Wenhao, Liu, Xingyu, Du, Xinya, Chen, Zhiyu Zoey |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Search Wisely: Mitigating Sub-optimal Agentic Searches By Reducing Uncertainty
by: Wu, Peilin, et al.
Published: (2025)
by: Wu, Peilin, et al.
Published: (2025)
AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning
by: Wu, Peilin, et al.
Published: (2026)
by: Wu, Peilin, et al.
Published: (2026)
HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation
by: Wu, Peilin, et al.
Published: (2025)
by: Wu, Peilin, et al.
Published: (2025)
IDEA: Enhancing the Rule Learning Ability of Large Language Model Agent through Induction, Deduction, and Abduction
by: He, Kaiyu, et al.
Published: (2024)
by: He, Kaiyu, et al.
Published: (2024)
GEAR: A General Evaluation Framework for Abductive Reasoning
by: He, Kaiyu, et al.
Published: (2025)
by: He, Kaiyu, et al.
Published: (2025)
Is Grokking Worthwhile? Functional Analysis and Transferability of Generalization Circuits in Transformers
by: He, Kaiyu, et al.
Published: (2026)
by: He, Kaiyu, et al.
Published: (2026)
Unveiling the Impact of Coding Data Instruction Fine-Tuning on Large Language Models Reasoning
by: Zhang, Xinlu, et al.
Published: (2024)
by: Zhang, Xinlu, et al.
Published: (2024)
Logits are All We Need to Adapt Closed Models
by: Hiranandani, Gaurush, et al.
Published: (2025)
by: Hiranandani, Gaurush, et al.
Published: (2025)
SimRAG: Self-Improving Retrieval-Augmented Generation for Adapting Large Language Models to Specialized Domains
by: Xu, Ran, et al.
Published: (2024)
by: Xu, Ran, et al.
Published: (2024)
MLR-Copilot: Autonomous Machine Learning Research based on Large Language Models Agents
by: Li, Ruochen, et al.
Published: (2024)
by: Li, Ruochen, et al.
Published: (2024)
Chain-of-Note: Enhancing Robustness in Retrieval-Augmented Language Models
by: Yu, Wenhao, et al.
Published: (2023)
by: Yu, Wenhao, et al.
Published: (2023)
RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language Models
by: Huang, Jie, et al.
Published: (2023)
by: Huang, Jie, et al.
Published: (2023)
Similarity is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts
by: Gan, Chunjing, et al.
Published: (2024)
by: Gan, Chunjing, et al.
Published: (2024)
CBT-Bench: Evaluating Large Language Models on Assisting Cognitive Behavior Therapy
by: Zhang, Mian, et al.
Published: (2024)
by: Zhang, Mian, et al.
Published: (2024)
ReEval: Automatic Hallucination Evaluation for Retrieval-Augmented Large Language Models via Transferable Adversarial Attacks
by: Yu, Xiaodong, et al.
Published: (2023)
by: Yu, Xiaodong, et al.
Published: (2023)
Understand What LLM Needs: Dual Preference Alignment for Retrieval-Augmented Generation
by: Dong, Guanting, et al.
Published: (2024)
by: Dong, Guanting, et al.
Published: (2024)
Quantifying and Improving the Robustness of Retrieval-Augmented Language Models Against Spurious Features in Grounding Data
by: Yang, Shiping, et al.
Published: (2025)
by: Yang, Shiping, et al.
Published: (2025)
Do Retrieval Augmented Language Models Know When They Don't Know?
by: Zhou, Youchao, et al.
Published: (2025)
by: Zhou, Youchao, et al.
Published: (2025)
Astute RAG: Overcoming Imperfect Retrieval Augmentation and Knowledge Conflicts for Large Language Models
by: Wang, Fei, et al.
Published: (2024)
by: Wang, Fei, et al.
Published: (2024)
PRD: Peer Rank and Discussion Improve Large Language Model based Evaluations
by: Li, Ruosen, et al.
Published: (2023)
by: Li, Ruosen, et al.
Published: (2023)
Soft Prompt Tuning for Augmenting Dense Retrieval with Large Language Models
by: Peng, Zhiyuan, et al.
Published: (2023)
by: Peng, Zhiyuan, et al.
Published: (2023)
Lightweight Retrieval-Augmented Generation and Large Language Model-Based Modeling for Scalable Patient-Trial Matching
by: Li, Xiaodi, et al.
Published: (2026)
by: Li, Xiaodi, et al.
Published: (2026)
Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity
by: Jeong, Soyeong, et al.
Published: (2024)
by: Jeong, Soyeong, et al.
Published: (2024)
Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
by: Prahlad, Deeksha, et al.
Published: (2025)
by: Prahlad, Deeksha, et al.
Published: (2025)
Adapting Language Models via Token Translation
by: Feng, Zhili, et al.
Published: (2024)
by: Feng, Zhili, et al.
Published: (2024)
Learning Retrieval Augmentation for Personalized Dialogue Generation
by: Huang, Qiushi, et al.
Published: (2024)
by: Huang, Qiushi, et al.
Published: (2024)
Lugha-Llama: Adapting Large Language Models for African Languages
by: Buzaaba, Happy, et al.
Published: (2025)
by: Buzaaba, Happy, et al.
Published: (2025)
Synthesizing and Adapting Error Correction Data for Mobile Large Language Model Applications
by: Zhang, Yanxiang, et al.
Published: (2025)
by: Zhang, Yanxiang, et al.
Published: (2025)
LLM-Match: An Open-Sourced Patient Matching Model Based on Large Language Models and Retrieval-Augmented Generation
by: Li, Xiaodi, et al.
Published: (2025)
by: Li, Xiaodi, et al.
Published: (2025)
Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Models
by: Islam, Shayekh Bin, et al.
Published: (2024)
by: Islam, Shayekh Bin, et al.
Published: (2024)
Do Large Language Models Need a Content Delivery Network?
by: Cheng, Yihua, et al.
Published: (2024)
by: Cheng, Yihua, et al.
Published: (2024)
RAG-Instruct: Boosting LLMs with Diverse Retrieval-Augmented Instructions
by: Liu, Wanlong, et al.
Published: (2024)
by: Liu, Wanlong, et al.
Published: (2024)
Do We Need Frontier Models to Verify Mathematical Proofs?
by: Naik, Aaditya, et al.
Published: (2026)
by: Naik, Aaditya, et al.
Published: (2026)
Large Language Model Augmented Exercise Retrieval for Personalized Language Learning
by: Xu, Austin, et al.
Published: (2024)
by: Xu, Austin, et al.
Published: (2024)
Listen to the Context: Towards Faithful Large Language Models for Retrieval Augmented Generation on Climate Questions
by: Thulke, David, et al.
Published: (2025)
by: Thulke, David, et al.
Published: (2025)
Enhancing E-commerce Product Title Translation with Retrieval-Augmented Generation and Large Language Models
by: Zhang, Bryan, et al.
Published: (2024)
by: Zhang, Bryan, et al.
Published: (2024)
Adapting to Non-Stationary Environments: Multi-Armed Bandit Enhanced Retrieval-Augmented Generation on Knowledge Graphs
by: Tang, Xiaqiang, et al.
Published: (2024)
by: Tang, Xiaqiang, et al.
Published: (2024)
Adaptive Guidance for Retrieval-Augmented Masked Diffusion Models
by: Kim, Jaemin, et al.
Published: (2026)
by: Kim, Jaemin, et al.
Published: (2026)
RE-Adapt: Reverse Engineered Adaptation of Large Language Models
by: Fleshman, William, et al.
Published: (2024)
by: Fleshman, William, et al.
Published: (2024)
Domain-Adapted Small Language Models for Reliable Clinical Triage
by: Aljohani, Manar, et al.
Published: (2026)
by: Aljohani, Manar, et al.
Published: (2026)
Similar Items
-
Search Wisely: Mitigating Sub-optimal Agentic Searches By Reducing Uncertainty
by: Wu, Peilin, et al.
Published: (2025) -
AMARIS: A Memory-Augmented Rubric Improvement System for Rubric-Based Reinforcement Learning
by: Wu, Peilin, et al.
Published: (2026) -
HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation
by: Wu, Peilin, et al.
Published: (2025) -
IDEA: Enhancing the Rule Learning Ability of Large Language Model Agent through Induction, Deduction, and Abduction
by: He, Kaiyu, et al.
Published: (2024) -
GEAR: A General Evaluation Framework for Abductive Reasoning
by: He, Kaiyu, et al.
Published: (2025)