Open davidberenstein1957 opened 1 year ago
Hello @davidberenstein1957,
To do overlap between sentences to have more attention between segments? if yes, recent works (I think the one using BERT for coreference) showed it is not necessary, also it comes with more computation time.
No overlap, as in that your entire text might not fit into (GPU) memory.
can you share more details? if you set max_tokens_in_batch
to your longest doc in the dataset is it still OOM?
Similarly, when you exceed the length of the 'max_tokens' for the transformer used, it might still be interesting to use the last 'x' sentences and use that prepended text for the next chunk, so that you can infer some knowledge from that batch and can later on merge the clusters if they contain the same spans.
If I understand correctly, you want want to overlap between batches? I can't understand the benefit of it.
let's say you have a text of length 3x, where the maximum number of tokens in a single pass is 2x, then it might make sense to allow for passing this text in segments 1:2 and segments 2:3. Afterwards, you could re-align/merge coref clusters based on the overlapping sentences in segment 2.
Hi,
I used to work a lot with coreference for longer texts and I think it would be a nice addition to overlap sentences to have a more robust model w.r.t. longer texts. I also want to work on this.
Regards, David