Closed freshjarman closed 1 year ago
Hi, thanks for your interest in our work. We do not include the part you mention in this version since it will introduce additional package dependency. We instead take a more straightforward case for training, and it undermines the performance in an acceptable range.
Thanks for your reply. Could u share the part with me? I am glad to see relevant codes of your interesting work. Thanks 😊
---Original--- From: @.> Date: Tue, Dec 6, 2022 23:37 PM To: @.>; Cc: @.**@.>; Subject: Re: [RyanWangZf/Trial2Vec] Issues about Local contrastive loss.(Issue #2)
Hi, thanks for your interest in our work. We do not include the part you mention in this version since it will introduce additional package dependency. We instead take a more straightforward case for training, and it undermines the performance in an acceptable range.
— Reply to this email directly, view it on GitHub, or unsubscribe. You are receiving this because you authored the thread.Message ID: @.***>
Hi, thanks for your interest in our work. We do not include the part you mention in this version since it will introduce additional package dependency. We instead take a more straightforward case for training, and it undermines the performance in an acceptable range.
I look forward to seeing that version (relevant codes of Hierarchical contrastive learning
) if you are free. Thanks for ur reply and interesting work which is of great help~ Here's my e-mail: wangtao98@seu.edu.cn 😊
Sent to your email.
Hi Zifeng,
I was wondering about the same piece related to the local contrastive loss. really appreciate it if you could make that part of the code available. much appreciated! I have sent you a message to your university email in this regards
Thanks,
@asamadan
Has sent to your email.
Hi Zifeng,
Firstly, congrats for great project. I am also interested with same piece of code. Can you send me too please, Thanks in advance (altunumut13@gmail.com)
Hi, I didn't find the relevant codes of
Local contrastive loss.
in the paper3.3
. Specifically, I don't know how to implement eq(6-8) (like, how to use SciSpacy and map one entity to its canonical name? I didn't find relevant codes in the project). Could u point it out, thanks~