-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 630 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 27 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 24 -
The Power of Scale for Parameter-Efficient Prompt Tuning
Paper • 2104.08691 • Published • 10
Hao-Yuan Chen
MarkChenX
AI & ML interests
Deep Learning, Foundational Models, Domain Adaptation, Quantum AI, LLM Reasoning, Agentic Research
Recent Activity
updated a Space 23 days ago
MarkChenX/ChatSupernova published a model about 1 month ago
MarkChenX/lfm2-quantum-128m published a model about 1 month ago
MarkChenX/lfm2-quantum-128m-sft-v2Organizations
-
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits
Paper • 2402.17764 • Published • 630 -
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 27 -
Training-Free Long-Context Scaling of Large Language Models
Paper • 2402.17463 • Published • 24 -
The Power of Scale for Parameter-Efficient Prompt Tuning
Paper • 2104.08691 • Published • 10
