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Collections including paper arxiv:2202.08906

Papers reimplemented

List of research papers, architectures, and techniques reimplemented in LLM-quest or Hugging Face's TRL. Missing: Qwen3.5, Qwen3-Next, GPT-2

VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training

Paper • 2602.10693 • Published Feb 11 • 220
Reinforced Attention Learning

Paper • 2602.04884 • Published Feb 4 • 29
Learning to Reason in 13 Parameters

Paper • 2602.04118 • Published Feb 4 • 6
LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters

Paper • 2405.17604 • Published May 27, 2024 • 3

Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts

Paper • 2009.10622 • Published Sep 22, 2020 • 1
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29, 2024 • 53
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8, 2024 • 74
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving

Paper • 2401.14361 • Published Jan 25, 2024 • 2

mixture-of-experts

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

Paper • 1701.06538 • Published Jan 23, 2017 • 7
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 • 11
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

Papers - MoE - Scaling

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

Paper • 1701.06538 • Published Jan 23, 2017 • 7
ST-MoE: Designing Stable and Transferable Sparse Expert Models

Paper • 2202.08906 • Published Feb 17, 2022 • 3
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

Paper • 2403.07816 • Published Mar 12, 2024 • 45

Mixtral of Experts

Paper • 2401.04088 • Published Jan 8, 2024 • 160
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29, 2024 • 53
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8, 2024 • 74
EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models

Paper • 2308.14352 • Published Aug 28, 2023

MoEs papers reading list

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

Paper • 1701.06538 • Published Jan 23, 2017 • 7
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 • 11
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

Papers reimplemented

List of research papers, architectures, and techniques reimplemented in LLM-quest or Hugging Face's TRL. Missing: Qwen3.5, Qwen3-Next, GPT-2

VESPO: Variational Sequence-Level Soft Policy Optimization for Stable Off-Policy LLM Training

Paper • 2602.10693 • Published Feb 11 • 220
Reinforced Attention Learning

Paper • 2602.04884 • Published Feb 4 • 29
Learning to Reason in 13 Parameters

Paper • 2602.04118 • Published Feb 4 • 6
LoRA-XS: Low-Rank Adaptation with Extremely Small Number of Parameters

Paper • 2405.17604 • Published May 27, 2024 • 3

Papers - MoE - Scaling

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

Paper • 1701.06538 • Published Jan 23, 2017 • 7
ST-MoE: Designing Stable and Transferable Sparse Expert Models

Paper • 2202.08906 • Published Feb 17, 2022 • 3
Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

Paper • 2403.07816 • Published Mar 12, 2024 • 45

Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts

Paper • 2009.10622 • Published Sep 22, 2020 • 1
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29, 2024 • 53
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8, 2024 • 74
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving

Paper • 2401.14361 • Published Jan 25, 2024 • 2

Mixtral of Experts

Paper • 2401.04088 • Published Jan 8, 2024 • 160
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models

Paper • 2401.15947 • Published Jan 29, 2024 • 53
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts

Paper • 2401.04081 • Published Jan 8, 2024 • 74
EdgeMoE: Fast On-Device Inference of MoE-based Large Language Models

Paper • 2308.14352 • Published Aug 28, 2023

mixture-of-experts

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

Paper • 1701.06538 • Published Jan 23, 2017 • 7
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 • 11
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

MoEs papers reading list

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

Paper • 1701.06538 • Published Jan 23, 2017 • 7
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 • 11
A Mixture of h-1 Heads is Better than h Heads

Paper • 2005.06537 • Published May 13, 2020 • 2

QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models

Paper • 2310.16795 • Published Oct 25, 2023 • 27
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference

Paper • 2308.12066 • Published Aug 23, 2023 • 4
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference

Paper • 2303.06182 • Published Mar 10, 2023 • 1
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate

Paper • 2112.14397 • Published Dec 29, 2021 • 1

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