human
Rephrase the sections given below and use bullet points for all the given sections. 
Instruction to be followed - 
- Generate 2 -4 bullet points for each section and use # before the each section headings
- Use the same citation or references mentioned in the context of the sections. 
- Do not use empty lines between the points.
-  Generate each point on a new line
The sections are - 
1 Introduction : Recurrent neural networks, long short-term memory [12] and gated recurrent [7] neural networks in particular, have been firmly established as state of the art approaches in sequence modeling and transduction problems such as language modeling and machine translation [29, 2, 5] . Recurrent models typically factor computation along the symbol positions of the input and output sequences. Aligning the positions to steps in computation time, they generate a sequence of hidden states h t , as a function of the previous hidden state h t−1 and the input for position t. This inherently sequential nature precludes parallelization within training examples, which becomes critical at longer sequence lengths, as memory constraints limit batching across examples. Attention mechanisms have become an integral part of compelling sequence modeling and transduction models in various tasks, allowing modeling of dependencies without regard to their distance in the input or output sequences [2, 16] . The Transformer allows for significantly more parallelization and can reach a new state of the art in translation quality after being trai
gpt
--- Reasoning ---
1. Is the question multiple-choice question?
No
2. Is it implied multiple-choice question?
No
3. If two experts were independently asked the question, will the final answer be exactly the same?
No

--- Answer ---
open