PEANuT: Parameter-Efficient Adaptation with Weight-aware Neural Tweakers
Fuente:
arXiv
Saved in:
| Main Authors: | Zhong, Yibo, Jiang, Haoxiang, Li, Lincan, Nakada, Ryumei, Liu, Tianci, Zhang, Linjun, Yao, Huaxiu, Wang, Haoyu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization
by: Liu, Tianci, et al.
Published: (2025)
by: Liu, Tianci, et al.
Published: (2025)
Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference
by: Zhang, Zhe, et al.
Published: (2024)
by: Zhang, Zhe, et al.
Published: (2024)
S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity
by: Yang, Xinyu, et al.
Published: (2024)
by: Yang, Xinyu, et al.
Published: (2024)
RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains
by: Jiang, Haoxiang, et al.
Published: (2026)
by: Jiang, Haoxiang, et al.
Published: (2026)
Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance
by: Nakada, Ryumei, et al.
Published: (2024)
by: Nakada, Ryumei, et al.
Published: (2024)
Residual Feature Integration is Sufficient to Prevent Negative Transfer
by: Xu, Yichen, et al.
Published: (2025)
by: Xu, Yichen, et al.
Published: (2025)
Safeguarding Data in Multimodal AI: A Differentially Private Approach to CLIP Training
by: Huang, Alyssa, et al.
Published: (2023)
by: Huang, Alyssa, et al.
Published: (2023)
A Theoretical Framework for Prompt Engineering: Approximating Smooth Functions with Transformer Prompts
by: Nakada, Ryumei, et al.
Published: (2025)
by: Nakada, Ryumei, et al.
Published: (2025)
Contrastive Learning on Multimodal Analysis of Electronic Health Records
by: Cai, Tianxi, et al.
Published: (2024)
by: Cai, Tianxi, et al.
Published: (2024)
Contrastive Network Representation Learning
by: Dong, Zihan, et al.
Published: (2025)
by: Dong, Zihan, et al.
Published: (2025)
FactTest: Factuality Testing in Large Language Models with Finite-Sample and Distribution-Free Guarantees
by: Nie, Fan, et al.
Published: (2024)
by: Nie, Fan, et al.
Published: (2024)
Mitigating Heterogeneous Token Overfitting in LLM Knowledge Editing
by: Liu, Tianci, et al.
Published: (2025)
by: Liu, Tianci, et al.
Published: (2025)
Alternating Reinforcement Learning for Rubric-Based Reward Modeling in Non-Verifiable LLM Post-Training
by: Xu, Ran, et al.
Published: (2026)
by: Xu, Ran, et al.
Published: (2026)
LIDAO: Towards Limited Interventions for Debiasing (Large) Language Models
by: Liu, Tianci, et al.
Published: (2024)
by: Liu, Tianci, et al.
Published: (2024)
Analyzing and Mitigating Object Hallucination in Large Vision-Language Models
by: Zhou, Yiyang, et al.
Published: (2023)
by: Zhou, Yiyang, et al.
Published: (2023)
Deconfounded Causality-aware Parameter-Efficient Fine-Tuning for Problem-Solving Improvement of LLMs
by: Wang, Ruoyu, et al.
Published: (2024)
by: Wang, Ruoyu, et al.
Published: (2024)
Efficient Stitchable Task Adaptation
by: He, Haoyu, et al.
Published: (2023)
by: He, Haoyu, et al.
Published: (2023)
Ever: Mitigating Hallucination in Large Language Models through Real-Time Verification and Rectification
by: Kang, Haoqiang, et al.
Published: (2023)
by: Kang, Haoqiang, et al.
Published: (2023)
DropLoRA: Sparse Low-Rank Adaptation for Parameter-Efficient Fine-Tuning
by: Zhang, Haojie
Published: (2025)
by: Zhang, Haojie
Published: (2025)
NeuroLoRA: Context-Aware Neuromodulation for Parameter-Efficient Multi-Task Adaptation
by: Yang, Yuxin, et al.
Published: (2026)
by: Yang, Yuxin, et al.
Published: (2026)
UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter-Efficient Fine-Tuning of Large Models
by: Zhang, Xueyan, et al.
Published: (2025)
by: Zhang, Xueyan, et al.
Published: (2025)
MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning
by: Xia, Peng, et al.
Published: (2025)
by: Xia, Peng, et al.
Published: (2025)
In-context Demonstration Matters: On Prompt Optimization for Pseudo-Supervision Refinement
by: Zhang, Zhen-Yu, et al.
Published: (2024)
by: Zhang, Zhen-Yu, et al.
Published: (2024)
$C^3$: Confidence Calibration Model Cascade for Inference-Efficient Cross-Lingual Natural Language Understanding
by: Lu, Taixi, et al.
Published: (2024)
by: Lu, Taixi, et al.
Published: (2024)
RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
AFLoRA: Adaptive Freezing of Low Rank Adaptation in Parameter Efficient Fine-Tuning of Large Models
by: Liu, Zeyu, et al.
Published: (2024)
by: Liu, Zeyu, et al.
Published: (2024)
SBoRA: Low-Rank Adaptation with Regional Weight Updates
by: Po, Lai-Man, et al.
Published: (2024)
by: Po, Lai-Man, et al.
Published: (2024)
Calibrated Self-Rewarding Vision Language Models
by: Zhou, Yiyang, et al.
Published: (2024)
by: Zhou, Yiyang, et al.
Published: (2024)
Unlocking Efficient, Scalable, and Continual Knowledge Editing with Basis-Level Representation Fine-Tuning
by: Liu, Tianci, et al.
Published: (2025)
by: Liu, Tianci, et al.
Published: (2025)
GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL
by: Yang, Rui, et al.
Published: (2026)
by: Yang, Rui, et al.
Published: (2026)
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment
by: Wang, Tianze, et al.
Published: (2025)
by: Wang, Tianze, et al.
Published: (2025)
Parameter Efficient Fine-tuning via Explained Variance Adaptation
by: Paischer, Fabian, et al.
Published: (2024)
by: Paischer, Fabian, et al.
Published: (2024)
DoTA: Weight-Decomposed Tensor Adaptation for Large Language Models
by: Hu, Xiaolin, et al.
Published: (2024)
by: Hu, Xiaolin, et al.
Published: (2024)
Parameter-Efficient Routed Fine-Tuning: Mixture-of-Experts Demands Mixture of Adaptation Modules
by: Liu, Yilun, et al.
Published: (2025)
by: Liu, Yilun, et al.
Published: (2025)
Distribution-Free Fair Federated Learning with Small Samples
by: Yin, Qichuan, et al.
Published: (2024)
by: Yin, Qichuan, et al.
Published: (2024)
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
by: Jiang, Enyi, et al.
Published: (2023)
by: Jiang, Enyi, et al.
Published: (2023)
Winner-Take-All Column Row Sampling for Memory Efficient Adaptation of Language Model
by: Liu, Zirui, et al.
Published: (2023)
by: Liu, Zirui, et al.
Published: (2023)
MoLAE: Mixture of Latent Experts for Parameter-Efficient Language Models
by: Liu, Zehua, et al.
Published: (2025)
by: Liu, Zehua, et al.
Published: (2025)
LSR-Adapt: Ultra-Efficient Parameter Tuning with Matrix Low Separation Rank Kernel Adaptation
by: Li, Xin, et al.
Published: (2025)
by: Li, Xin, et al.
Published: (2025)
Similar Items
-
RoseRAG: Robust Retrieval-augmented Generation with Small-scale LLMs via Margin-aware Preference Optimization
by: Liu, Tianci, et al.
Published: (2025) -
Differentially Private Federated Learning: Servers Trustworthiness, Estimation, and Statistical Inference
by: Zhang, Zhe, et al.
Published: (2024) -
S$^{2}$FT: Efficient, Scalable and Generalizable LLM Fine-tuning by Structured Sparsity
by: Yang, Xinyu, et al.
Published: (2024) -
RUBRIC-ARROW: Alternating Pointwise Rubric Reward Modeling for LLM Post-training in Non-verifiable Domains
by: Jiang, Haoxiang, et al.
Published: (2026) -
Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance
by: Nakada, Ryumei, et al.
Published: (2024)