Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models | Paper Citation Record

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models , " * write output.state after.block = add.period write newline

Reference 1

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models write newline

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This paper cites GPT-4 Technical Report.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models GPT-4 Technical Report

Reference 3

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Simple linear attention language models balance the recall-throughput tradeoff

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models R.; et al

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This paper cites R.; and Hinton, G.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models R.; and Hinton, G

Reference 6

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

Reference 8

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models by parts

Reference 9

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

Reference 10

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This paper cites SummScreen: A Dataset for Abstractive Screenplay Summarization.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models SummScreen: A Dataset for Abstractive Screenplay Summarization

Reference 11

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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This paper cites J.; and Rudnicky, A.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models J.; and Rudnicky, A

Reference 13

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

Reference 14

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This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 15

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This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

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This paper cites P.; Caron, M.; Geirhos, R.; Alabdul mohsin, I.; Jenatton, R.; Beyer, L.; Tschannen, M.; Arnab, A.; Wang, X.; Ruiz, C.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models P.; Caron, M.; Geirhos, R.; Alabdul mohsin, I.; Jenatton, R.; Beyer, L.; Tschannen, M.; Arnab, A.; Wang, X.; Ruiz, C

Reference 17

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This paper cites The Llama 3 Herd of Models.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models The Llama 3 Herd of Models

Reference 18

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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This paper cites On the Properties of the Softmax Function with Application in Game Theory and Reinforcement Learning.

Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models On the Properties of the Softmax Function with Application in Game Theory and Reinforcement Learning

Reference 21

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Gaussian Error Linear Units (GELUs)

Reference 27

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models R.; Pawar, S

Reference 28

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models G.; Zhu, M.; Chen, B.; Kalenichenko, D.; Wang, W.; Weyand, T.; Andreetto, M.; and Adam, H

Reference 29

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Categorical Reparameterization with Gumbel-Softmax

Reference 33

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models The Impact of Positional Encoding on Length Generalization in Transformers

Reference 36

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Attention is a smoothed cubic spline

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

Reference 40

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models DeepSeek-V3 Technical Report

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Mish: A Self Regularized Non-Monotonic Activation Function

Reference 46

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models The FineWeb Datasets: Decanting the Web for the Finest Text Data at Scale

Reference 48

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Theory, Analysis, and Best Practices for Sigmoid Self-Attention

Reference 52

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models E.; Hinton, G

Reference 53

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models FlashAttention-3: Fast and Accurate Attention with Asynchrony and Low-precision

Reference 54

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models A Study on ReLU and Softmax in Transformer

Reference 55

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

Reference 56

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models H.; Bai, S.; Yamada, M.; Morency, L.-P.; and Salakhutdinov, R

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Crowdsourcing Multiple Choice Science Questions

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Replacing softmax with ReLU in Vision Transformers

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Mirage: A Multi-Level Superoptimizer for Tensor Programs

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 66

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Softplus Attention with Re-weighting Boosts Length Extrapolation in Large Language Models Unresolved cited work

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