Cover Image

Zhyper: Factorized Hypernetworks for Conditioned LLM Fine-Tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Abdalla, M. H. I., Wang, Zhipin, Frey, Christian, Eger, Steffen, Grabocka, Josif
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ValueGround: Evaluating Culture-Conditioned Visual Value Grounding in MLLMs
by: Wang, Zhipin, et al.
Published: (2026)

LLLMs: A Data-Driven Survey of Evolving Research on Limitations of Large Language Models
by: Kostikova, Aida, et al.
Published: (2025)

Ensembling Finetuned Language Models for Text Classification
by: Arango, Sebastian Pineda, et al.
Published: (2024)

Tabular Data: Is Deep Learning all you need?
by: Zabërgja, Guri, et al.
Published: (2024)

Learning to Order: Task Sequencing as In-Context Optimization
by: Kobiolka, Jan, et al.
Published: (2026)

End-to-End Compression for Tabular Foundation Models
by: Zabërgja, Guri, et al.
Published: (2026)

Learn-to-learn on Arbitrary Textual Conditioning: A Hypernetwork-Driven Meta-Gated LLM
by: Ji, Luo, et al.
Published: (2026)

LLM Analysis of 150+ years of German Parliamentary Debates on Migration Reveals Shift from Post-War Solidarity to Anti-Solidarity in the Last Decade
by: Kostikova, Aida, et al.
Published: (2025)

POP: Prior-Fitted First-Order Optimization Policies
by: Kobiolka, Jan, et al.
Published: (2026)

Hierarchical Transformers are Efficient Meta-Reinforcement Learners
by: Shala, Gresa, et al.
Published: (2024)

Interpretable Mesomorphic Networks for Tabular Data
by: Kadra, Arlind, et al.
Published: (2023)

Fine-Grained Detection of Solidarity for Women and Migrants in 155 Years of German Parliamentary Debates
by: Kostikova, Aida, et al.
Published: (2022)

PocketLLM: Enabling On-Device Fine-Tuning for Personalized LLMs
by: Peng, Dan, et al.
Published: (2024)

Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
by: Arango, Sebastian Pineda, et al.
Published: (2023)

Memory-Efficient Structured Backpropagation for On-Device LLM Fine-Tuning
by: Park, Juneyoung, et al.
Published: (2026)

Hypernetworks for Personalizing ASR to Atypical Speech
by: Müller-Eberstein, Max, et al.
Published: (2024)

Towards Explainable Evaluation Metrics for Machine Translation
by: Leiter, Christoph, et al.
Published: (2023)

Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmark
by: Zhang, Yihua, et al.
Published: (2024)

Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional Control
by: Wang, Xinyu, et al.
Published: (2026)

Understanding the Performance and Estimating the Cost of LLM Fine-Tuning
by: Xia, Yuchen, et al.
Published: (2024)

LUNE: Efficient LLM Unlearning via LoRA Fine-Tuning with Negative Examples
by: Liu, Yezi, et al.
Published: (2025)

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning
by: Zhu, Yuchang, et al.
Published: (2025)

LCSB: Layer-Cyclic Selective Backpropagation for Memory-Efficient On-Device LLM Fine-Tuning
by: Park, Juneyoung, et al.
Published: (2026)

Pre-training LLM without Learning Rate Decay Enhances Supervised Fine-Tuning
by: Yano, Kazuki, et al.
Published: (2026)

Fine Tuning Methods for Low-resource Languages
by: Bakkenes, Tim, et al.
Published: (2025)

From Parameters to Data: A Task-Parameter-Guided Fine-Tuning Pipeline for Efficient LLM Alignment
by: Chen, Hao, et al.
Published: (2026)

Reviving Your MNEME: Predicting The Side Effects of LLM Unlearning and Fine-Tuning via Sparse Model Diffing
by: Kassem, Aly M., et al.
Published: (2025)

Filter-then-Weight: Online Data Selection and Reweighting for LLM Fine-Tuning
by: Wang, Fangxin, et al.
Published: (2026)

Anchored Supervised Fine-Tuning
by: Zhu, He, et al.
Published: (2025)

Energy and Carbon Considerations of Fine-Tuning BERT
by: Wang, Xiaorong, et al.
Published: (2023)

TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Models
by: Liu, Zefang, et al.
Published: (2024)

Selection of LLM Fine-Tuning Data based on Orthogonal Rules
by: Li, Xiaomin, et al.
Published: (2024)

Accidental Vulnerability: Factors in Fine-Tuning that Shift Model Safeguards
by: Pandey, Punya Syon, et al.
Published: (2025)

Leaner Training, Lower Leakage: Revisiting Memorization in LLM Fine-Tuning with LoRA
by: Wang, Fei, et al.
Published: (2025)

DeepSeek-R1 vs. o3-mini: How Well can Reasoning LLMs Evaluate MT and Summarization?
by: Larionov, Daniil, et al.
Published: (2025)

Prior-Informed Zeroth-Order Optimization with Adaptive Direction Alignment for Memory-Efficient LLM Fine-Tuning
by: Jin, Feihu, et al.
Published: (2026)

Dissecting Fine-Tuning Unlearning in Large Language Models
by: Hong, Yihuai, et al.
Published: (2024)

COS-DPO: Conditioned One-Shot Multi-Objective Fine-Tuning Framework
by: Ren, Yinuo, et al.
Published: (2024)

Proximal Supervised Fine-Tuning
by: Zhu, Wenhong, et al.
Published: (2025)

Prompt Tuning for Natural Language to SQL with Embedding Fine-Tuning and RAG
by: Jang, Jisoo, et al.
Published: (2025)