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Collections including paper arxiv:2403.09347

Long context LLM

Sequence Parallelism: Long Sequence Training from System Perspective

Paper • 2105.13120 • Published May 26, 2021 • 5
Ring Attention with Blockwise Transformers for Near-Infinite Context

Paper • 2310.01889 • Published Oct 3, 2023 • 11
Striped Attention: Faster Ring Attention for Causal Transformers

Paper • 2311.09431 • Published Nov 15, 2023 • 4
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Paper • 2309.14509 • Published Sep 25, 2023 • 18

Training-Free Long-Context Scaling of Large Language Models

Paper • 2402.17463 • Published Feb 27, 2024 • 23
Evaluating Very Long-Term Conversational Memory of LLM Agents

Paper • 2402.17753 • Published Feb 27, 2024 • 20
Resonance RoPE: Improving Context Length Generalization of Large Language Models

Paper • 2403.00071 • Published Feb 29, 2024 • 24
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences

Paper • 2403.09347 • Published Mar 14, 2024 • 22

Attention in LLM

Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28, 2024 • 20
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences

Paper • 2403.09347 • Published Mar 14, 2024 • 22

daily_paper_coll

Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 55
Beyond Language Models: Byte Models are Digital World Simulators

Paper • 2402.19155 • Published Feb 29, 2024 • 51
StarCoder 2 and The Stack v2: The Next Generation

Paper • 2402.19173 • Published Feb 29, 2024 • 138
Simple linear attention language models balance the recall-throughput tradeoff

Paper • 2402.18668 • Published Feb 28, 2024 • 20

InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory

Paper • 2402.04617 • Published Feb 7, 2024 • 4
BurstAttention: An Efficient Distributed Attention Framework for Extremely Long Sequences

Paper • 2403.09347 • Published Mar 14, 2024 • 22
Resonance RoPE: Improving Context Length Generalization of Large Language Models

Paper • 2403.00071 • Published Feb 29, 2024 • 24
Training-Free Long-Context Scaling of Large Language Models

Paper • 2402.17463 • Published Feb 27, 2024 • 23

Papers - Context

In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss

Paper • 2402.10790 • Published Feb 16, 2024 • 42
LongAgent: Scaling Language Models to 128k Context through Multi-Agent Collaboration

Paper • 2402.11550 • Published Feb 18, 2024 • 18
A Neural Conversational Model

Paper • 1506.05869 • Published Jun 19, 2015 • 2
Data Engineering for Scaling Language Models to 128K Context

Paper • 2402.10171 • Published Feb 15, 2024 • 25

Papers - Attention

Linear Transformers with Learnable Kernel Functions are Better In-Context Models

Paper • 2402.10644 • Published Feb 16, 2024 • 81
GQA: Training Generalized Multi-Query Transformer Models from Multi-Head Checkpoints

Paper • 2305.13245 • Published May 22, 2023 • 5
ChunkAttention: Efficient Self-Attention with Prefix-Aware KV Cache and Two-Phase Partition

Paper • 2402.15220 • Published Feb 23, 2024 • 21
Sequence Parallelism: Long Sequence Training from System Perspective

Paper • 2105.13120 • Published May 26, 2021 • 5

PIA: Your Personalized Image Animator via Plug-and-Play Modules in Text-to-Image Models

Paper • 2312.13964 • Published Dec 21, 2023 • 20
LLM in a flash: Efficient Large Language Model Inference with Limited Memory

Paper • 2312.11514 • Published Dec 12, 2023 • 259
StreamDiffusion: A Pipeline-level Solution for Real-time Interactive Generation

Paper • 2312.12491 • Published Dec 19, 2023 • 70
LLaVA-φ: Efficient Multi-Modal Assistant with Small Language Model

Paper • 2401.02330 • Published Jan 4, 2024 • 17

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