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Collections including paper arxiv:2406.06563

Self-Rewarding Language Models

Paper • 2401.10020 • Published Jan 18 • 143
Orion-14B: Open-source Multilingual Large Language Models

Paper • 2401.12246 • Published Jan 20 • 11
MambaByte: Token-free Selective State Space Model

Paper • 2401.13660 • Published Jan 24 • 50
MM-LLMs: Recent Advances in MultiModal Large Language Models

Paper • 2401.13601 • Published Jan 24 • 44

Papers I want to read

Papers in my to-read list

RLHF Workflow: From Reward Modeling to Online RLHF

Paper • 2405.07863 • Published May 13 • 67
Chameleon: Mixed-Modal Early-Fusion Foundation Models

Paper • 2405.09818 • Published May 16 • 126
Meteor: Mamba-based Traversal of Rationale for Large Language and Vision Models

Paper • 2405.15574 • Published May 24 • 53
An Introduction to Vision-Language Modeling

Paper • 2405.17247 • Published May 27 • 85

OLMo: Accelerating the Science of Language Models

Paper • 2402.00838 • Published Feb 1 • 80
Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models

Paper • 2406.06563 • Published Jun 3 • 17

LLM+Architecture

MoA: Mixture-of-Attention for Subject-Context Disentanglement in Personalized Image Generation

Paper • 2404.11565 • Published Apr 17 • 14
Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models

Paper • 2406.06563 • Published Jun 3 • 17
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Paper • 2406.11931 • Published Jun 17 • 57

Efficient Tool Use with Chain-of-Abstraction Reasoning

Paper • 2401.17464 • Published Jan 30 • 16
Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Paper • 2401.15688 • Published Jan 28 • 11
SliceGPT: Compress Large Language Models by Deleting Rows and Columns

Paper • 2401.15024 • Published Jan 26 • 68
From GPT-4 to Gemini and Beyond: Assessing the Landscape of MLLMs on Generalizability, Trustworthiness and Causality through Four Modalities

Paper • 2401.15071 • Published Jan 26 • 34

MoEs papers reading list

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Paper • 1701.06538 • Published Jan 23, 2017 • 4
Sparse Networks from Scratch: Faster Training without Losing Performance

Paper • 1907.04840 • Published Jul 10, 2019 • 3
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models

Paper • 1910.02054 • Published Oct 4, 2019 • 4
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

Attention Is All You Need

Paper • 1706.03762 • Published Jun 12, 2017 • 44
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Paper • 1810.04805 • Published Oct 11, 2018 • 14
RoBERTa: A Robustly Optimized BERT Pretraining Approach

Paper • 1907.11692 • Published Jul 26, 2019 • 7
DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Paper • 1910.01108 • Published Oct 2, 2019 • 14

Mixture of Experts

Memory Augmented Language Models through Mixture of Word Experts

Paper • 2311.10768 • Published Nov 15, 2023 • 16
Mixtral of Experts

Paper • 2401.04088 • Published Jan 8 • 157
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8 • 70
DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Paper • 2401.06066 • Published Jan 11 • 42

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