Efficient LLM - a VoladorLuYu Collection

VoladorLuYu 's Collections

Research on LLM

Generative Multiple Modality

Super Alignment

Foundation Machine Learning

Graph Foundation Multimodal Models

Symbolic LLM Reasoning

Data-efficient LLMs

Understanding LLM

synthetic code generation

Diffusion Models

LLM+Architecture

LLM+Self-Play RL

Efficient LLM

updated Jun 27

Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads

Paper • 2401.10774 • Published Jan 19 • 53
APAR: LLMs Can Do Auto-Parallel Auto-Regressive Decoding

Paper • 2401.06761 • Published Jan 12 • 1
Infinite-LLM: Efficient LLM Service for Long Context with DistAttention and Distributed KVCache

Paper • 2401.02669 • Published Jan 5 • 14
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 50
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty

Paper • 2401.15077 • Published Jan 26 • 18
Small LLMs Are Weak Tool Learners: A Multi-LLM Agent

Paper • 2401.07324 • Published Jan 14 • 3
Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling

Paper • 2402.10211 • Published Feb 15 • 10
LongRoPE: Extending LLM Context Window Beyond 2 Million Tokens

Paper • 2402.13753 • Published Feb 21 • 111
Ouroboros: Speculative Decoding with Large Model Enhanced Drafting

Paper • 2402.13720 • Published Feb 21 • 5
Neural Network Diffusion

Paper • 2402.13144 • Published Feb 20 • 94
LongAlign: A Recipe for Long Context Alignment of Large Language Models

Paper • 2401.18058 • Published Jan 31 • 21
LongHeads: Multi-Head Attention is Secretly a Long Context Processor

Paper • 2402.10685 • Published Feb 16 • 1
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning

Paper • 2401.01325 • Published Jan 2 • 26
E^2-LLM: Efficient and Extreme Length Extension of Large Language Models

Paper • 2401.06951 • Published Jan 13 • 24
InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory

Paper • 2402.04617 • Published Feb 7 • 4
Speculative Streaming: Fast LLM Inference without Auxiliary Models

Paper • 2402.11131 • Published Feb 16 • 41
Towards Optimal Learning of Language Models

Paper • 2402.17759 • Published Feb 27 • 16
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method

Paper • 2402.17193 • Published Feb 27 • 23
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6 • 182
DenseMamba: State Space Models with Dense Hidden Connection for Efficient Large Language Models

Paper • 2403.00818 • Published Feb 26 • 15
LongNet: Scaling Transformers to 1,000,000,000 Tokens

Paper • 2307.02486 • Published Jul 5, 2023 • 80
Recurrent Drafter for Fast Speculative Decoding in Large Language Models

Paper • 2403.09919 • Published Mar 14 • 20
DiJiang: Efficient Large Language Models through Compact Kernelization

Paper • 2403.19928 • Published Mar 29 • 10
ReFT: Representation Finetuning for Language Models

Paper • 2404.03592 • Published Apr 4 • 89
Rethinking Optimization and Architecture for Tiny Language Models

Paper • 2402.02791 • Published Feb 5 • 12
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases

Paper • 2402.14905 • Published Feb 22 • 126
Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Paper • 2404.02258 • Published Apr 2 • 104
Pre-training Small Base LMs with Fewer Tokens

Paper • 2404.08634 • Published Apr 12 • 34
Scaling (Down) CLIP: A Comprehensive Analysis of Data, Architecture, and Training Strategies

Paper • 2404.08197 • Published Apr 12 • 27
Rho-1: Not All Tokens Are What You Need

Paper • 2404.07965 • Published Apr 11 • 84
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length

Paper • 2404.08801 • Published Apr 12 • 63
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models

Paper • 2307.14430 • Published Jul 26, 2023 • 3
Compression Represents Intelligence Linearly

Paper • 2404.09937 • Published Apr 15 • 27
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Paper • 2401.01335 • Published Jan 2 • 64
MoRA: High-Rank Updating for Parameter-Efficient Fine-Tuning

Paper • 2405.12130 • Published May 20 • 45
SLAB: Efficient Transformers with Simplified Linear Attention and Progressive Re-parameterized Batch Normalization

Paper • 2405.11582 • Published May 19 • 12
How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition

Paper • 2310.05492 • Published Oct 9, 2023 • 2
The Instruction Hierarchy: Training LLMs to Prioritize Privileged Instructions

Paper • 2404.13208 • Published Apr 19 • 38
Unlocking Continual Learning Abilities in Language Models

Paper • 2406.17245 • Published Jun 25 • 28