FIPO: Free-form Instruction-oriented Prompt Optimization with Preference Dataset and Modular Fine-tuning Schema
Fuente:
arXiv
Saved in:
| Main Authors: | Lu, Junru, An, Siyu, Zhang, Min, He, Yulan, Yin, Di, Sun, Xing |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence
by: Lu, Junru, et al.
Published: (2024)
by: Lu, Junru, et al.
Published: (2024)
RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-Following
by: Lu, Junru, et al.
Published: (2025)
by: Lu, Junru, et al.
Published: (2025)
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
by: Shen, Zhenyi, et al.
Published: (2025)
by: Shen, Zhenyi, et al.
Published: (2025)
Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas
by: Stähelin, Lukas, et al.
Published: (2026)
by: Stähelin, Lukas, et al.
Published: (2026)
PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching
by: Qi, Zhenting, et al.
Published: (2023)
by: Qi, Zhenting, et al.
Published: (2023)
Efficient Ensemble for Fine-tuning Language Models on Multiple Datasets
by: Li, Dongyue, et al.
Published: (2025)
by: Li, Dongyue, et al.
Published: (2025)
Learning or Self-aligning? Rethinking Instruction Fine-tuning
by: Ren, Mengjie, et al.
Published: (2024)
by: Ren, Mengjie, et al.
Published: (2024)
Fine-tuning vs Prompting, Can Language Models Understand Human Values?
by: Sun, Pingwei
Published: (2024)
by: Sun, Pingwei
Published: (2024)
AIR: A Systematic Analysis of Annotations, Instructions, and Response Pairs in Preference Dataset
by: He, Bingxiang, et al.
Published: (2025)
by: He, Bingxiang, et al.
Published: (2025)
Fine-tuning Large Language Models with Sequential Instructions
by: Hu, Hanxu, et al.
Published: (2024)
by: Hu, Hanxu, et al.
Published: (2024)
Preference-grounded Token-level Guidance for Language Model Fine-tuning
by: Yang, Shentao, et al.
Published: (2023)
by: Yang, Shentao, et al.
Published: (2023)
Calibrating LLMs with Preference Optimization on Thought Trees for Generating Rationale in Science Question Scoring
by: Li, Jiazheng, et al.
Published: (2024)
by: Li, Jiazheng, et al.
Published: (2024)
AlignSum: Data Pyramid Hierarchical Fine-tuning for Aligning with Human Summarization Preference
by: Han, Yang, et al.
Published: (2024)
by: Han, Yang, et al.
Published: (2024)
FinVerse: An Autonomous Agent System for Versatile Financial Analysis
by: An, Siyu, et al.
Published: (2024)
by: An, Siyu, et al.
Published: (2024)
Prompt-based Graph Model for Joint Liberal Event Extraction and Event Schema Induction
by: Li, Haochen, et al.
Published: (2024)
by: Li, Haochen, et al.
Published: (2024)
Causal Prompting: Debiasing Large Language Model Prompting based on Front-Door Adjustment
by: Zhang, Congzhi, et al.
Published: (2024)
by: Zhang, Congzhi, et al.
Published: (2024)
Enhancing Complex Instruction Following for Large Language Models with Mixture-of-Contexts Fine-tuning
by: Lu, Yuheng, et al.
Published: (2025)
by: Lu, Yuheng, et al.
Published: (2025)
The Importance of Online Data: Understanding Preference Fine-tuning via Coverage
by: Song, Yuda, et al.
Published: (2024)
by: Song, Yuda, et al.
Published: (2024)
On the Loss of Context-awareness in General Instruction Fine-tuning
by: Wang, Yihan, et al.
Published: (2024)
by: Wang, Yihan, et al.
Published: (2024)
COIG-CQIA: Quality is All You Need for Chinese Instruction Fine-tuning
by: Bai, Yuelin, et al.
Published: (2024)
by: Bai, Yuelin, et al.
Published: (2024)
Two Heads Are Better Than One: Dual-Model Verbal Reflection at Inference-Time
by: Li, Jiazheng, et al.
Published: (2025)
by: Li, Jiazheng, et al.
Published: (2025)
Exploring Memorization in Fine-tuned Language Models
by: Zeng, Shenglai, et al.
Published: (2023)
by: Zeng, Shenglai, et al.
Published: (2023)
SHED: Shapley-Based Automated Dataset Refinement for Instruction Fine-Tuning
by: He, Yexiao, et al.
Published: (2024)
by: He, Yexiao, et al.
Published: (2024)
Large Language Models for Ingredient Substitution in Food Recipes using Supervised Fine-tuning and Direct Preference Optimization
by: Senath, Thevin, et al.
Published: (2024)
by: Senath, Thevin, et al.
Published: (2024)
Towards Context-Robust LLMs: A Gated Representation Fine-tuning Approach
by: Zeng, Shenglai, et al.
Published: (2025)
by: Zeng, Shenglai, et al.
Published: (2025)
Simultaneous Masking, Not Prompting Optimization: A Paradigm Shift in Fine-tuning LLMs for Simultaneous Translation
by: Raffel, Matthew, et al.
Published: (2024)
by: Raffel, Matthew, et al.
Published: (2024)
Modular Prompt Optimization: Optimizing Structured Prompts with Section-Local Textual Gradients
by: Sharma, Prith, et al.
Published: (2026)
by: Sharma, Prith, et al.
Published: (2026)
Be Careful When Fine-tuning On Open-Source LLMs: Your Fine-tuning Data Could Be Secretly Stolen!
by: Zhang, Zhexin, et al.
Published: (2025)
by: Zhang, Zhexin, et al.
Published: (2025)
Do we Really Need Visual Instructions? Towards Visual Instruction-Free Fine-tuning for Large Vision-Language Models
by: Liu, Zikang, et al.
Published: (2025)
by: Liu, Zikang, et al.
Published: (2025)
Outlier-weighed Layerwise Sampling for LLM Fine-tuning
by: Li, Pengxiang, et al.
Published: (2024)
by: Li, Pengxiang, et al.
Published: (2024)
Video-Text Dataset Construction from Multi-AI Feedback: Promoting Weak-to-Strong Preference Learning for Video Large Language Models
by: Yi, Hao, et al.
Published: (2024)
by: Yi, Hao, et al.
Published: (2024)
Demystifying Instruction Mixing for Fine-tuning Large Language Models
by: Wang, Renxi, et al.
Published: (2023)
by: Wang, Renxi, et al.
Published: (2023)
KcMF: A Knowledge-compliant Framework for Schema and Entity Matching with Fine-tuning-free LLMs
by: Xu, Yongqin, et al.
Published: (2024)
by: Xu, Yongqin, et al.
Published: (2024)
PARA: Parameter-Efficient Fine-tuning with Prompt Aware Representation Adjustment
by: Liu, Zequan, et al.
Published: (2025)
by: Liu, Zequan, et al.
Published: (2025)
Compact Prompting in Instruction-tuned LLMs for Joint Argumentative Component Detection
by: Elguendouze, Sofiane, et al.
Published: (2026)
by: Elguendouze, Sofiane, et al.
Published: (2026)
LoFiT: Localized Fine-tuning on LLM Representations
by: Yin, Fangcong, et al.
Published: (2024)
by: Yin, Fangcong, et al.
Published: (2024)
Targeted Efficient Fine-tuning: Optimizing Parameter Updates with Data-Driven Sample Selection
by: Dong, Ming, et al.
Published: (2024)
by: Dong, Ming, et al.
Published: (2024)
Reverse Preference Optimization for Complex Instruction Following
by: Huang, Xiang, et al.
Published: (2025)
by: Huang, Xiang, et al.
Published: (2025)
MultiLingPoT: Enhancing Mathematical Reasoning with Multilingual Program Fine-tuning
by: Li, Nianqi, et al.
Published: (2024)
by: Li, Nianqi, et al.
Published: (2024)
Breaking the Transcription Bottleneck: Fine-tuning ASR Models for Extremely Low-Resource Fieldwork Languages
by: Liang, Siyu, et al.
Published: (2025)
by: Liang, Siyu, et al.
Published: (2025)
Similar Items
-
Eliminating Biased Length Reliance of Direct Preference Optimization via Down-Sampled KL Divergence
by: Lu, Junru, et al.
Published: (2024) -
RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-Following
by: Lu, Junru, et al.
Published: (2025) -
SSA: Sparse Sparse Attention by Aligning Full and Sparse Attention Outputs in Feature Space
by: Shen, Zhenyi, et al.
Published: (2025) -
Fine-tuning with Hierarchical Prompting for Robust Propaganda Classification Across Annotation Schemas
by: Stähelin, Lukas, et al.
Published: (2026) -
PILLOW: Enhancing Efficient Instruction Fine-tuning via Prompt Matching
by: Qi, Zhenting, et al.
Published: (2023)