RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection
Fuente:
arXiv
Saved in:
| Main Authors: | Yang, Yixin, Dong, Qingxiu, Yao, Linli, Zhu, Fangwei, Sui, Zhifang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
CoLT: Reasoning with Chain of Latent Tool Calls
by: Zhu, Fangwei, et al.
Published: (2026)
by: Zhu, Fangwei, et al.
Published: (2026)
Can Large Multimodal Models Uncover Deep Semantics Behind Images?
by: Yang, Yixin, et al.
Published: (2024)
by: Yang, Yixin, et al.
Published: (2024)
Reducing Hallucinations in Entity Abstract Summarization with Facts-Template Decomposition
by: Zhu, Fangwei, et al.
Published: (2024)
by: Zhu, Fangwei, et al.
Published: (2024)
Language Models Encode the Value of Numbers Linearly
by: Zhu, Fangwei, et al.
Published: (2024)
by: Zhu, Fangwei, et al.
Published: (2024)
Chain-of-Thought Tokens are Computer Program Variables
by: Zhu, Fangwei, et al.
Published: (2025)
by: Zhu, Fangwei, et al.
Published: (2025)
Self-Boosting Large Language Models with Synthetic Preference Data
by: Dong, Qingxiu, et al.
Published: (2024)
by: Dong, Qingxiu, et al.
Published: (2024)
Chip-Tuning: Classify Before Language Models Say
by: Zhu, Fangwei, et al.
Published: (2024)
by: Zhu, Fangwei, et al.
Published: (2024)
Reinforcement Pre-Training
by: Dong, Qingxiu, et al.
Published: (2025)
by: Dong, Qingxiu, et al.
Published: (2025)
Decoding in Geometry: Alleviating Embedding-Space Crowding for Complex Reasoning
by: Yang, Yixin, et al.
Published: (2026)
by: Yang, Yixin, et al.
Published: (2026)
Synthetic Data (Almost) from Scratch: Generalized Instruction Tuning for Language Models
by: Li, Haoran, et al.
Published: (2024)
by: Li, Haoran, et al.
Published: (2024)
SelfBudgeter: Adaptive Token Allocation for Efficient LLM Reasoning
by: Li, Zheng, et al.
Published: (2025)
by: Li, Zheng, et al.
Published: (2025)
How Far are LLMs from Being Our Digital Twins? A Benchmark for Persona-Based Behavior Chain Simulation
by: Li, Rui, et al.
Published: (2025)
by: Li, Rui, et al.
Published: (2025)
RICoTA: Red-teaming of In-the-wild Conversation with Test Attempts
by: Choi, Eujeong, et al.
Published: (2025)
by: Choi, Eujeong, et al.
Published: (2025)
CoachLM: Automatic Instruction Revisions Improve the Data Quality in LLM Instruction Tuning
by: Liu, Yilun, et al.
Published: (2023)
by: Liu, Yilun, et al.
Published: (2023)
Not All Demonstration Examples are Equally Beneficial: Reweighting Demonstration Examples for In-Context Learning
by: Yang, Zhe, et al.
Published: (2023)
by: Yang, Zhe, et al.
Published: (2023)
Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding
by: Xia, Heming, et al.
Published: (2024)
by: Xia, Heming, et al.
Published: (2024)
IterSelectTune: An Iterative Training Framework for Efficient Instruction-Tuning Data Selection
by: Song, Jielin, et al.
Published: (2024)
by: Song, Jielin, et al.
Published: (2024)
Beyond Single Frames: Can LMMs Comprehend Temporal and Contextual Narratives in Image Sequences?
by: Wang, Xiaochen, et al.
Published: (2025)
by: Wang, Xiaochen, et al.
Published: (2025)
Data Selection via Optimal Control for Language Models
by: Gu, Yuxian, et al.
Published: (2024)
by: Gu, Yuxian, et al.
Published: (2024)
MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space
by: Chen, Yicheng, et al.
Published: (2025)
by: Chen, Yicheng, et al.
Published: (2025)
PeriodicLoRA: Breaking the Low-Rank Bottleneck in LoRA Optimization
by: Meng, Xiangdi, et al.
Published: (2024)
by: Meng, Xiangdi, et al.
Published: (2024)
Towards Better RL Training Data Utilization via Second-Order Rollout
by: Yang, Zhe, et al.
Published: (2026)
by: Yang, Zhe, et al.
Published: (2026)
Large-Scale Data Selection for Instruction Tuning
by: Ivison, Hamish, et al.
Published: (2025)
by: Ivison, Hamish, et al.
Published: (2025)
Augmenting In-Context-Learning in LLMs via Automatic Data Labeling and Refinement
by: Shtok, Joseph, et al.
Published: (2024)
by: Shtok, Joseph, et al.
Published: (2024)
Importance-Aware Data Selection for Efficient LLM Instruction Tuning
by: Jiang, Tingyu, et al.
Published: (2025)
by: Jiang, Tingyu, et al.
Published: (2025)
Star-Agents: Automatic Data Optimization with LLM Agents for Instruction Tuning
by: Zhou, Hang, et al.
Published: (2024)
by: Zhou, Hang, et al.
Published: (2024)
Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
by: Chen, Xin, et al.
Published: (2026)
by: Chen, Xin, et al.
Published: (2026)
A Survey on Data Selection for LLM Instruction Tuning
by: Zhang, Bolin, et al.
Published: (2024)
by: Zhang, Bolin, et al.
Published: (2024)
What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning
by: Liu, Wei, et al.
Published: (2023)
by: Liu, Wei, et al.
Published: (2023)
Dynamic Data Mixing Maximizes Instruction Tuning for Mixture-of-Experts
by: Zhu, Tong, et al.
Published: (2024)
by: Zhu, Tong, et al.
Published: (2024)
What Makes Good Instruction-Tuning Data? An In-Context Learning Perspective
by: Han, Guangzeng, et al.
Published: (2026)
by: Han, Guangzeng, et al.
Published: (2026)
Simulated Adoption: Decoupling Magnitude and Direction in LLM In-Context Conflict Resolution
by: Zhang, Long, et al.
Published: (2026)
by: Zhang, Long, et al.
Published: (2026)
Low-Confidence Gold: Refining Low-Confidence Samples for Efficient Instruction Tuning
by: Cai, Hongyi, et al.
Published: (2025)
by: Cai, Hongyi, et al.
Published: (2025)
Data Selection for Multi-turn Dialogue Instruction Tuning
by: Li, Bo, et al.
Published: (2026)
by: Li, Bo, et al.
Published: (2026)
Self-Refine Instruction-Tuning for Aligning Reasoning in Language Models
by: Ranaldi, Leonardo, et al.
Published: (2024)
by: Ranaldi, Leonardo, et al.
Published: (2024)
Beyond Similarity: A Gradient-based Graph Method for Instruction Tuning Data Selection
by: Zhao, Yang, et al.
Published: (2025)
by: Zhao, Yang, et al.
Published: (2025)
Selective Reflection-Tuning: Student-Selected Data Recycling for LLM Instruction-Tuning
by: Li, Ming, et al.
Published: (2024)
by: Li, Ming, et al.
Published: (2024)
Select2Reason: Efficient Instruction-Tuning Data Selection for Long-CoT Reasoning
by: Yang, Cehao, et al.
Published: (2025)
by: Yang, Cehao, et al.
Published: (2025)
Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning
by: Zhu, Wenhao, et al.
Published: (2025)
by: Zhu, Wenhao, et al.
Published: (2025)
AIR: Complex Instruction Generation via Automatic Iterative Refinement
by: Liu, Wei, et al.
Published: (2025)
by: Liu, Wei, et al.
Published: (2025)
Similar Items
-
CoLT: Reasoning with Chain of Latent Tool Calls
by: Zhu, Fangwei, et al.
Published: (2026) -
Can Large Multimodal Models Uncover Deep Semantics Behind Images?
by: Yang, Yixin, et al.
Published: (2024) -
Reducing Hallucinations in Entity Abstract Summarization with Facts-Template Decomposition
by: Zhu, Fangwei, et al.
Published: (2024) -
Language Models Encode the Value of Numbers Linearly
by: Zhu, Fangwei, et al.
Published: (2024) -
Chain-of-Thought Tokens are Computer Program Variables
by: Zhu, Fangwei, et al.
Published: (2025)