antonisa

The Impossible Task of Conference SACs/PCs or How I lost 3 Nights of Sleep

I am writing this post in order to share my thoughts on the processes behind acceptance/rejection decisions in top-tier (NLP) conferences. I'll first discuss the process and then share some thoughts on its shortcomings.

Before we start, a bit about me. I am an assistant professor (aka, rather junior: I have been in this position for less than 4 years, following my PhD studies and a short postdoc) working on NLP, with a focus on multilingualism and low-resource settings. While I have submitted, published at, and reviewed for *ACL conferences and workshops for many years, it was at EMNLP'23 that I was a Senior Area Chair (SAC) for the first time.

The Conference Paper Pipeline

Let's first briefly outline the process that a paper undergoes, from submission to decision:

bluelovers

Stable Diffusion is an AI art generation model similar to DALLE-2.
Here are some prompts for generating art with Stable Diffusion. 

Example:

- A ghostly apparition drifting through a haunted mansion's grand ballroom, illuminated by flickering candlelight. Eerie, ethereal, moody lighting. 
- portait of a homer simpson archer shooting arrow at forest monster, front game card, drark, marvel comics, dark, smooth
- pirate, deep focus, fantasy, matte, sharp focus
- red dead redemption 2, cinematic view, epic sky, detailed, low angle, high detail, warm lighting, volumetric, godrays, vivid, beautiful
- a fantasy style portrait painting of rachel lane / alison brie hybrid in the style of francois boucher oil painting, rpg portrait

trygvebw

import torch
import numpy as np
import k_diffusion as K

from PIL import Image
from torch import autocast
from einops import rearrange, repeat

def pil_img_to_torch(pil_img, half=False):
    image = np.array(pil_img).astype(np.float32) / 255.0