TASK DEFINITION: In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.
PROBLEM: Methods ::: Length Encoding Method
Inspired by BIBREF11, we use length encoding to provide the network with information about the remaining sentence length during decoding. We propose two types of length encoding: absolute and relative. Let pos and len be, respectively, a token position and the end of the sequence, both expressed in terms of number characters. Then, the absolute approach encodes the remaining length:

where $i=1,\ldots ,d/2$.

Similarly, the relative difference encodes the relative position to the end. This representation is made consistent with the absolute encoding by quantizing the space of the relative positions into a finite set of $N$ integers:

where $q_N: [0, 1] \rightarrow \lbrace 0, 1, .., N\rbrace $ is simply defined as $q_N(x) = \lfloor {x \times N}\rfloor $. As we are interested in the character length of the target sequence, len and pos are given in terms of characters, but we represent the sequence as a sequence of BPE-segmented subwords BIBREF17. To solve the ambiguity, len is the character length of the sequence, while pos is the character count of all the preceding tokens. 
 Question: How do they enrich the positional embedding with length information

SOLUTION: They introduce new trigonometric encoding which besides information about position uses additional length information (abs or relative).

PROBLEM: We use Gaussian Processes as this probabilistic kernelised framework avoids the need for expensive cross-validation for hyperparameter selection 
 Question: Why is a Gaussian process an especially appropriate method for this classification problem?

SOLUTION: avoids the need for expensive cross-validation for hyperparameter selection

PROBLEM: The final result submitted in public leaderboard is 0.73019 and in private leaderboard is 0.58455. It is quite different in bad way. That maybe is the result of the model too overfit on train set tuning on public test set. 
 Question: What is public dashboard?

SOLUTION:
Public dashboard where competitors can see their results during competition, on part of the test set (public test set).