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Mar 16
Mar 16
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Collections including paper arxiv:2310.16795
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Mar 26
Mar 26
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QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
Pareto-Optimal Quantized ResNet Is Mostly 4-bit
Paper • 2105.03536 • Published • 2 -
Decoding Compressed Trust: Scrutinizing the Trustworthiness of Efficient LLMs Under Compression
Paper • 2403.15447 • Published • 16
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Apr 3
Apr 3
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Adaptive sequential Monte Carlo by means of mixture of experts
Paper • 1108.2836 • Published • 2 -
Convergence Rates for Mixture-of-Experts
Paper • 1110.2058 • Published • 2 -
Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs
Paper • 2310.12008 • Published • 2 -
Enhancing NeRF akin to Enhancing LLMs: Generalizable NeRF Transformer with Mixture-of-View-Experts
Paper • 2308.11793 • Published • 2
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Aug 23
Aug 23
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Non-asymptotic oracle inequalities for the Lasso in high-dimensional mixture of experts
Paper • 2009.10622 • Published • 1 -
MoE-LLaVA: Mixture of Experts for Large Vision-Language Models
Paper • 2401.15947 • Published • 48 -
MoE-Mamba: Efficient Selective State Space Models with Mixture of Experts
Paper • 2401.04081 • Published • 70 -
MoE-Infinity: Activation-Aware Expert Offloading for Efficient MoE Serving
Paper • 2401.14361 • Published • 2
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Oct 9
Oct 9
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Measuring the Effects of Data Parallelism on Neural Network Training
Paper • 1811.03600 • Published • 2 -
Adafactor: Adaptive Learning Rates with Sublinear Memory Cost
Paper • 1804.04235 • Published • 2 -
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
Paper • 1905.11946 • Published • 3 -
Yi: Open Foundation Models by 01.AI
Paper • 2403.04652 • Published • 62
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Sep 11
Sep 11
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Self-Rewarding Language Models
Paper • 2401.10020 • Published • 143 -
ReFT: Reasoning with Reinforced Fine-Tuning
Paper • 2401.08967 • Published • 27 -
Tuning Language Models by Proxy
Paper • 2401.08565 • Published • 20 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 64
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Feb 27
Feb 27
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Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Paper • 1701.06538 • Published • 4 -
Sparse Networks from Scratch: Faster Training without Losing Performance
Paper • 1907.04840 • Published • 3 -
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Paper • 1910.02054 • Published • 4 -
A Mixture of h-1 Heads is Better than h Heads
Paper • 2005.06537 • Published • 2
Collection by
5 days ago
5 days ago
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Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer
Paper • 1701.06538 • Published • 4 -
Sparse Networks from Scratch: Faster Training without Losing Performance
Paper • 1907.04840 • Published • 3 -
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Paper • 1910.02054 • Published • 4 -
A Mixture of h-1 Heads is Better than h Heads
Paper • 2005.06537 • Published • 2
Collection by
Jun 21
Jun 21
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QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
Paper • 2308.12066 • Published • 4 -
Towards MoE Deployment: Mitigating Inefficiencies in Mixture-of-Expert (MoE) Inference
Paper • 2303.06182 • Published • 1 -
EvoMoE: An Evolutional Mixture-of-Experts Training Framework via Dense-To-Sparse Gate
Paper • 2112.14397 • Published • 1
Collection by
Apr 10
Apr 10
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QMoE: Practical Sub-1-Bit Compression of Trillion-Parameter Models
Paper • 2310.16795 • Published • 26 -
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMs
Paper • 2310.13961 • Published • 4 -
The Consensus Game: Language Model Generation via Equilibrium Search
Paper • 2310.09139 • Published • 12 -
Large Language Model Cascades with Mixture of Thoughts Representations for Cost-efficient Reasoning
Paper • 2310.03094 • Published • 12