LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Paper
•
2309.12307
•
Published
•
87
LLM
-
-
LMDX: Language Model-based Document Information Extraction and Localization
Paper • 2309.10952 • Published • 65 -
Table-GPT: Table-tuned GPT for Diverse Table Tasks
Paper • 2310.09263 • Published • 39 -
BitNet: Scaling 1-bit Transformers for Large Language Models
Paper • 2310.11453 • Published • 96 -
TEQ: Trainable Equivalent Transformation for Quantization of LLMs
Paper • 2310.10944 • Published • 9 -
TableGPT: Towards Unifying Tables, Nature Language and Commands into One GPT
Paper • 2307.08674 • Published • 48 -
UniversalNER: Targeted Distillation from Large Language Models for Open Named Entity Recognition
Paper • 2308.03279 • Published • 21 -
MultiLoRA: Democratizing LoRA for Better Multi-Task Learning
Paper • 2311.11501 • Published • 33 -
YaRN: Efficient Context Window Extension of Large Language Models
Paper • 2309.00071 • Published • 65 -
DocLLM: A layout-aware generative language model for multimodal document understanding
Paper • 2401.00908 • Published • 181 -
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning
Paper • 2401.01325 • Published • 26 -
Improving Text Embeddings with Large Language Models
Paper • 2401.00368 • Published • 79 -
OLMo: Accelerating the Science of Language Models
Paper • 2402.00838 • Published • 80 -
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens
Paper • 2402.13753 • Published • 111 -
DoRA: Weight-Decomposed Low-Rank Adaptation
Paper • 2402.09353 • Published • 26 -
LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 6 -
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Paper • 2401.04398 • Published • 20 -
A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
Paper • 2402.07927 • Published • 1 -
Simple and Scalable Strategies to Continually Pre-train Large Language Models
Paper • 2403.08763 • Published • 48 -
LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders
Paper • 2404.05961 • Published • 64 -
Effective Long-Context Scaling of Foundation Models
Paper • 2309.16039 • Published • 30 -
LoRA Learns Less and Forgets Less
Paper • 2405.09673 • Published • 87 -
Data Engineering for Scaling Language Models to 128K Context
Paper • 2402.10171 • Published • 21 -
Arcee's MergeKit: A Toolkit for Merging Large Language Models
Paper • 2403.13257 • Published • 20 -
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Paper • 1910.02054 • Published • 4 -
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning
Paper • 2405.12130 • Published • 45 -
DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model
Paper • 2405.04434 • Published • 13 -
Generative Representational Instruction Tuning
Paper • 2402.09906 • Published • 51 -
LoRA-GA: Low-Rank Adaptation with Gradient Approximation
Paper • 2407.05000 • Published -
Trained Transformers Learn Linear Models In-Context
Paper • 2306.09927 • Published -
Attention Heads of Large Language Models: A Survey
Paper • 2409.03752 • Published • 87