Merging in a Bottle: Differentiable Adaptive Merging (DAM) and the Path from Averaging to Automation
Paper
•
2410.08371
•
Published
•
3
Maxime Labonne PRO
mlabonne
AI & ML interests
Post-training, model editing, quantization
Organizations
authored
a
paper
about 1 year ago
authored
6
papers
over 2 years ago
Short-Term Flow-Based Bandwidth Forecasting using Machine Learning
Paper
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2011.14421
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Published
•
1
Predicting Bandwidth Utilization on Network Links Using Machine Learning
Paper
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2112.02417
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Published
•
1
An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning
Paper
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2305.15016
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Published
•
5
Toward Formal Data Set Verification for Building Effective Machine Learning Models
Paper
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2108.11220
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Published
•
1
Priority Flow Admission and Routing in SDN: Exact and Heuristic Approaches
Paper
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2009.10822
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Published
•
1
Spam-T5: Benchmarking Large Language Models for Few-Shot Email Spam Detection
Paper
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2304.01238
•
Published
•
2