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Approximating Two-Layer Feedforward Networks for Efficient Transformers
Paper • 2310.10837 • Published • 10 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 94 -
QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
LLM-FP4: 4-Bit Floating-Point Quantized Transformers
Paper • 2310.16836 • Published • 10
Collections
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Collections including paper arxiv:2310.11453
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LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models
Paper • 2310.08659 • Published • 20 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 94 -
ZeroQuant(4+2): Redefining LLMs Quantization with a New FP6-Centric Strategy for Diverse Generative Tasks
Paper • 2312.08583 • Published • 9
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QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43 -
PaLI-3 Vision Language Models: Smaller, Faster, Stronger
Paper • 2310.09199 • Published • 22 -
Can GPT models be Financial Analysts? An Evaluation of ChatGPT and GPT-4 on mock CFA Exams
Paper • 2310.08678 • Published • 11 -
MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning
Paper • 2310.09478 • Published • 17
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LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper • 2309.12307 • Published • 84 -
LMDX: Language Model-based Document Information Extraction and Localization
Paper • 2309.10952 • Published • 61 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 37 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 94
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Chain-of-Verification Reduces Hallucination in Large Language Models
Paper • 2309.11495 • Published • 37 -
Adapting Large Language Models via Reading Comprehension
Paper • 2309.09530 • Published • 73 -
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Paper • 2309.09400 • Published • 77 -
Language Modeling Is Compression
Paper • 2309.10668 • Published • 81
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TinyStories: How Small Can Language Models Be and Still Speak Coherent English?
Paper • 2305.07759 • Published • 30 -
QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models
Paper • 2309.14717 • Published • 43 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 94 -
LLM-FP4: 4-Bit Floating-Point Quantized Transformers
Paper • 2310.16836 • Published • 10
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Agents: An Open-source Framework for Autonomous Language Agents
Paper • 2309.07870 • Published • 39 -
Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts
Paper • 2309.07430 • Published • 26 -
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Paper • 2309.08532 • Published • 50 -
Investigating Answerability of LLMs for Long-Form Question Answering
Paper • 2309.08210 • Published • 11
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MADLAD-400: A Multilingual And Document-Level Large Audited Dataset
Paper • 2309.04662 • Published • 21 -
Neurons in Large Language Models: Dead, N-gram, Positional
Paper • 2309.04827 • Published • 16 -
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
Paper • 2309.05516 • Published • 8 -
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs
Paper • 2309.03907 • Published • 6