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Collections including paper arxiv:2402.19427

Trellis Networks for Sequence Modeling

Paper • 1810.06682 • Published Oct 15, 2018 • 1
ProSG: Using Prompt Synthetic Gradients to Alleviate Prompt Forgetting of RNN-like Language Models

Paper • 2311.01981 • Published Nov 3, 2023 • 1
Gated recurrent neural networks discover attention

Paper • 2309.01775 • Published Sep 4, 2023 • 7
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks

Paper • 2305.19190 • Published May 30, 2023 • 1

LLM architecture

The Impact of Depth and Width on Transformer Language Model Generalization

Paper • 2310.19956 • Published Oct 30, 2023 • 9
Retentive Network: A Successor to Transformer for Large Language Models

Paper • 2307.08621 • Published Jul 17, 2023 • 170
RWKV: Reinventing RNNs for the Transformer Era

Paper • 2305.13048 • Published May 22, 2023 • 15
Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 49

Efficient Memory Management for Large Language Model Serving with PagedAttention

Paper • 2309.06180 • Published Sep 12, 2023 • 25
LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models

Paper • 2308.16137 • Published Aug 30, 2023 • 39
Scaling Transformer to 1M tokens and beyond with RMT

Paper • 2304.11062 • Published Apr 19, 2023 • 2
DeepSpeed Ulysses: System Optimizations for Enabling Training of Extreme Long Sequence Transformer Models

Paper • 2309.14509 • Published Sep 25, 2023 • 17

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

Paper • 2402.19427 • Published Feb 29, 2024 • 52

SciLitLLM: How to Adapt LLMs for Scientific Literature Understanding

Paper • 2408.15545 • Published Aug 28, 2024 • 34
Controllable Text Generation for Large Language Models: A Survey

Paper • 2408.12599 • Published Aug 22, 2024 • 63
To Code, or Not To Code? Exploring Impact of Code in Pre-training

Paper • 2408.10914 • Published Aug 20, 2024 • 41
Automated Design of Agentic Systems

Paper • 2408.08435 • Published Aug 15, 2024 • 38

fuck quadratic attention

Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence

Paper • 2404.05892 • Published Apr 8, 2024 • 32
Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Paper • 2312.00752 • Published Dec 1, 2023 • 138
RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Paper • 2404.07839 • Published Apr 11, 2024 • 43
Leave No Context Behind: Efficient Infinite Context Transformers with Infini-attention

Paper • 2404.07143 • Published Apr 10, 2024 • 104

RecurrentGemma: Moving Past Transformers for Efficient Open Language Models

Paper • 2404.07839 • Published Apr 11, 2024 • 43
Eagle and Finch: RWKV with Matrix-Valued States and Dynamic Recurrence

Paper • 2404.05892 • Published Apr 8, 2024 • 32
Jamba: A Hybrid Transformer-Mamba Language Model

Paper • 2403.19887 • Published Mar 28, 2024 • 104
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52

Multimodal Model (LLM)

Multimodal Foundation Models: From Specialists to General-Purpose Assistants

Paper • 2309.10020 • Published Sep 18, 2023 • 40
Language as the Medium: Multimodal Video Classification through text only

Paper • 2309.10783 • Published Sep 19, 2023 • 1
Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models

Paper • 2403.18814 • Published Mar 27, 2024 • 45
Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Paper • 2402.19427 • Published Feb 29, 2024 • 52

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

Paper • 2402.19427 • Published Feb 29, 2024 • 52
ai21labs/Jamba-v0.1

Text Generation • Updated Sep 11, 2024 • 7.91k • 1.17k
TechxGenus/Mini-Jamba

Text Generation • Updated Apr 2, 2024 • 39 • 29

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

Paper • 2402.19427 • Published Feb 29, 2024 • 52
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Paper • 2403.03507 • Published Mar 6, 2024 • 183
BiLLM: Pushing the Limit of Post-Training Quantization for LLMs

Paper • 2402.04291 • Published Feb 6, 2024 • 48
The Era of 1-bit LLMs: All Large Language Models are in 1.58 Bits

Paper • 2402.17764 • Published Feb 27, 2024 • 605

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