Saved in:
| Main Authors: | Agarwal, Ishika, Killamsetty, Krishnateja, Popa, Lucian, Danilevksy, Marina |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.04425 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Neural Networks for Learnable and Scalable Influence Estimation of Instruction Fine-Tuning Data
by: Agarwal, Ishika, et al.
Published: (2025)
by: Agarwal, Ishika, et al.
Published: (2025)
Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning
by: Nayak, Nikhil Shivakumar, et al.
Published: (2025)
by: Nayak, Nikhil Shivakumar, et al.
Published: (2025)
SCoRe: Submodular Combinatorial Representation Learning
by: Majee, Anay, et al.
Published: (2023)
by: Majee, Anay, et al.
Published: (2023)
Language Specific Knowledge: Do Models Know Better in X than in English?
by: Agarwal, Ishika, et al.
Published: (2025)
by: Agarwal, Ishika, et al.
Published: (2025)
MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversations
by: Rosenthal, Sara, et al.
Published: (2026)
by: Rosenthal, Sara, et al.
Published: (2026)
GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models
by: Ruan, Zhiwen, et al.
Published: (2026)
by: Ruan, Zhiwen, et al.
Published: (2026)
A Rising Tide Lifts All Boats: MTQE Rewards for Idioms Improve General Translation Quality
by: Agarwal, Ishika, et al.
Published: (2026)
by: Agarwal, Ishika, et al.
Published: (2026)
Parameter-Efficient Fine-Tuning with Differential Privacy for Robust Instruction Adaptation in Large Language Models
by: Huang, Yulin, et al.
Published: (2025)
by: Huang, Yulin, et al.
Published: (2025)
Tree-of-Debate: Multi-Persona Debate Trees Elicit Critical Thinking for Scientific Comparative Analysis
by: Kargupta, Priyanka, et al.
Published: (2025)
by: Kargupta, Priyanka, et al.
Published: (2025)
Dynamics of Instruction Fine-Tuning for Chinese Large Language Models
by: Song, Chiyu, et al.
Published: (2023)
by: Song, Chiyu, et al.
Published: (2023)
Phased Instruction Fine-Tuning for Large Language Models
by: Pang, Wei, et al.
Published: (2024)
by: Pang, Wei, et al.
Published: (2024)
On the Impact of Fine-Tuning on Chain-of-Thought Reasoning
by: Lobo, Elita, et al.
Published: (2024)
by: Lobo, Elita, et al.
Published: (2024)
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)
G-Loss: Graph-Guided Fine-Tuning of Language Models
by: Sharma, Aditya, et al.
Published: (2026)
by: Sharma, Aditya, et al.
Published: (2026)
Instruct, Not Assist: LLM-based Multi-Turn Planning and Hierarchical Questioning for Socratic Code Debugging
by: Kargupta, Priyanka, et al.
Published: (2024)
by: Kargupta, Priyanka, et al.
Published: (2024)
Federated Data-Efficient Instruction Tuning for Large Language Models
by: Qin, Zhen, et al.
Published: (2024)
by: Qin, Zhen, et al.
Published: (2024)
Seed-Guided Fine-Grained Entity Typing in Science and Engineering Domains
by: Zhang, Yu, et al.
Published: (2024)
by: Zhang, Yu, et al.
Published: (2024)
Internalizing Tool Knowledge in Small Language Models via QLoRA Fine-Tuning
by: Shemla, Yuval, et al.
Published: (2026)
by: Shemla, Yuval, et al.
Published: (2026)
Importance-Aware Data Selection for Efficient LLM Instruction Tuning
by: Jiang, Tingyu, et al.
Published: (2025)
by: Jiang, Tingyu, et al.
Published: (2025)
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)
Fine-Tuning on Noisy Instructions: Effects on Generalization and Performance
by: Alajrami, Ahmed, et al.
Published: (2025)
by: Alajrami, Ahmed, et al.
Published: (2025)
Beyond QA Pairs: Assessing Parameter-Efficient Fine-Tuning for Fact Embedding in LLMs
by: Ratnakar, Shivam, et al.
Published: (2025)
by: Ratnakar, Shivam, et al.
Published: (2025)
Toward Secure Tuning: Mitigating Security Risks from Instruction Fine-Tuning
by: Du, Yanrui, et al.
Published: (2024)
by: Du, Yanrui, et al.
Published: (2024)
Tracing the Genealogies of Ideas with Large Language Model Embeddings
by: Li, Lucian
Published: (2024)
by: Li, Lucian
Published: (2024)
TACOS: Open Tagging and Comparative Scoring for Instruction Fine-Tuning Data Selection
by: He, Xixiang, et al.
Published: (2025)
by: He, Xixiang, et al.
Published: (2025)
Towards Efficient Medical Reasoning with Minimal Fine-Tuning Data
by: Zhuang, Xinlin, et al.
Published: (2025)
by: Zhuang, Xinlin, et al.
Published: (2025)
Prompt, Translate, Fine-Tune, Re-Initialize, or Instruction-Tune? Adapting LLMs for In-Context Learning in Low-Resource Languages
by: Toukmaji, Christopher, et al.
Published: (2025)
by: Toukmaji, Christopher, et al.
Published: (2025)
Step-by-Step Unmasking for Parameter-Efficient Fine-tuning of Large Language Models
by: Agarwal, Aradhye, et al.
Published: (2024)
by: Agarwal, Aradhye, et al.
Published: (2024)
Parameter-Efficient Fine-Tuning of Large Language Models using Semantic Knowledge Tuning
by: Prottasha, Nusrat Jahan, et al.
Published: (2024)
by: Prottasha, Nusrat Jahan, et al.
Published: (2024)
Balancing Continuous Pre-Training and Instruction Fine-Tuning: Optimizing Instruction-Following in LLMs
by: Jindal, Ishan, et al.
Published: (2024)
by: Jindal, Ishan, et al.
Published: (2024)
Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning Distillation
by: Zhang, Lechen, et al.
Published: (2026)
by: Zhang, Lechen, et al.
Published: (2026)
ArgInstruct: Specialized Instruction Fine-Tuning for Computational Argumentation
by: Stahl, Maja, et al.
Published: (2025)
by: Stahl, Maja, et al.
Published: (2025)
Automated Data Curation for Robust Language Model Fine-Tuning
by: Chen, Jiuhai, et al.
Published: (2024)
by: Chen, Jiuhai, et al.
Published: (2024)
DataShield: Safety-degrading Data Filtering for LLM Benign Instruction Fine-Tuning
by: Zhang, Junbo, et al.
Published: (2026)
by: Zhang, Junbo, et al.
Published: (2026)
MeTA-LoRA: Data-Efficient Multi-Task Fine-Tuning for Large Language Models
by: Cheng, Bo, et al.
Published: (2025)
by: Cheng, Bo, et al.
Published: (2025)
BEFT: Bias-Efficient Fine-Tuning of Language Models in Low-Data Regimes
by: Huang, Baichuan, et al.
Published: (2025)
by: Huang, Baichuan, et al.
Published: (2025)
Instruction Mining: Instruction Data Selection for Tuning Large Language Models
by: Cao, Yihan, et al.
Published: (2023)
by: Cao, Yihan, et al.
Published: (2023)
UPDESH: Synthesizing Grounded Instruction Tuning Data for 13 Indic Languages
by: Chitale, Pranjal A., et al.
Published: (2025)
by: Chitale, Pranjal A., et al.
Published: (2025)
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)
Unlocking Parameter-Efficient Fine-Tuning for Low-Resource Language Translation
by: Su, Tong, et al.
Published: (2024)
by: Su, Tong, et al.
Published: (2024)
Similar Items
-
Neural Networks for Learnable and Scalable Influence Estimation of Instruction Fine-Tuning Data
by: Agarwal, Ishika, et al.
Published: (2025) -
Sculpting Subspaces: Constrained Full Fine-Tuning in LLMs for Continual Learning
by: Nayak, Nikhil Shivakumar, et al.
Published: (2025) -
SCoRe: Submodular Combinatorial Representation Learning
by: Majee, Anay, et al.
Published: (2023) -
Language Specific Knowledge: Do Models Know Better in X than in English?
by: Agarwal, Ishika, et al.
Published: (2025) -
MTRAG-UN: A Benchmark for Open Challenges in Multi-Turn RAG Conversations
by: Rosenthal, Sara, et al.
Published: (2026)