This horrible paper proposes a job posting generation task which generates job requirement conditioned on the basic information and the job description.
- The title is confusing, it should be job requirement generation instead.
- The paper is confusing, what exactly are the local and global P?
- “we view this a MultiLabel Classification as a sequence generation problem”, what’s the benefit? Can you justify your view? Are you serious?
- The proposed task has little real point, who will post generated requirements to the public? The authors think they know better about what kind of employees these companies need, which is arrogant and ignorant.
- Such a shitshow.
- 5: Transformative: This paper is likely to change our field. It should be considered for a best paper award.
- 4.5: Exciting: It changed my thinking on this topic. I would fight for it to be accepted.
- 4: Strong: I learned a lot from it. I would like to see it accepted.
- 3.5: Leaning positive: It can be accepted more or less in its current form. However, the work it describes is not particularly exciting and/or inspiring, so it will not be a big loss if people don’t see it in this conference.
- 3: Ambivalent: It has merits (e.g., it reports state-of-the-art results, the idea is nice), but there are key weaknesses (e.g., I didn’t learn much from it, evaluation is not convincing, it describes incremental work). I believe it can significantly benefit from another round of revision, but I won’t object to accepting it if my co-reviewers are willing to champion it.
- 2.5: Leaning negative: I am leaning towards rejection, but I can be persuaded if my co-reviewers think otherwise.
- 2: Mediocre: I would rather not see it in the conference.
- 1.5: Weak: I am pretty confident that it should be rejected.
- 1: Poor: I would fight to have it rejected.