← Learning Types
Machine Learning › Learning Types ›

Fine-Tuning

487 directly classified papers

Papers per year

Papers

Re-Tuning: Overcoming the Compositionality Limits of Large Language Models with Recursive Tuning ACL 2024
Ask Again, Then Fail: Large Language Models’ Vacillations in Judgment ACL 2024
Uncertainty Aware Learning for Language Model Alignment ACL 2024
Split and Rephrase with Large Language Models ACL 2024
Learning to Generate Answers with Citations via Factual Consistency Models ACL 2024
XFT: Unlocking the Power of Code Instruction Tuning by Simply Merging Upcycled Mixture-of-Experts ACL 2024
“My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models ACL 2024
Challenging Large Language Models with New Tasks: A Study on their Adaptability and Robustness ACL 2024
Rationales for Answers to Simple Math Word Problems Confuse Large Language Models ACL 2024
On the Vulnerability of Safety Alignment in Open-Access LLMs ACL 2024
Model Fusion through Bayesian Optimization in Language Model Fine-Tuning NIPS 2024
Gradient Rewiring for Editable Graph Neural Network Training NIPS 2024
Safe LoRA: The Silver Lining of Reducing Safety Risks when Finetuning Large Language Models NIPS 2024
Multi-language Diversity Benefits Autoformalization NIPS 2024
Navigating the Safety Landscape: Measuring Risks in Finetuning Large Language Models NIPS 2024
LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models EMNLP 2024
Edinburgh Clinical NLP at SemEval-2024 Task 2: Fine-tune your model unless you have access to GPT-4 SEMEVAL 2024
SU-FMI at SemEval-2024 Task 5: From BERT Fine-Tuning to LLM Prompt Engineering - Approaches in Legal Argument Reasoning SEMEVAL 2024
VIGC: Visual Instruction Generation and Correction AAAI 2024
Fine-Tuning Large Language Models for Stock Return Prediction Using Newsflow EMNLP 2024
AmazonQAC: A Large-Scale, Naturalistic Query Autocomplete Dataset EMNLP 2024
HW-TSC at SemEval-2024 Task 9: Exploring Prompt Engineering Strategies for Brain Teaser Puzzles Through LLMs SEMEVAL 2024
QuanTA: Efficient High-Rank Fine-Tuning of LLMs with Quantum-Informed Tensor Adaptation NIPS 2024
Personalized Federated Learning with Mixture of Models for Adaptive Prediction and Model Fine-Tuning NIPS 2024
On the Effects of Data Scale on UI Control Agents NIPS 2024