DeepSeek's commentary of top AI/ML conferences (just4fun)
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Recently, I was revising my paper and, out of curiosity, asked DeepSeek AI to give some sharp reviews of major AI conferences. The results were entertaining enough to share!
CVPR
The "crown jewel" of computer vision, with submission volume rivaling holiday train tickets and painfully low acceptance rates.
CVPR is an event that raises the blood pressure of AI researchers globally. If your paper gets rejected, don't worry—90% of people share your fate.
CVPR is like a battlefield for papers, with reviewers acting as ruthless supervisors holding magnifying glasses to pick faults. You're the student endlessly tormented.
Hot topics? They change annually. This year it’s diffusion models; next year, it'll probably be something even more mystical. CVPR teaches us: forget eternity; pursue temporary insanity instead.
NeurIPS
The "Oscars" of machine learning, with acceptance rates heartbreakingly low.
NeurIPS resembles an academic stand-up comedy show, where everyone gathers to share their "innovative ideas." But don’t celebrate prematurely; your paper might still be rejected for "inelegant experimental design."
Reviewers here are like scholarly monks living deep in the mountains, meditating on how to perfect each paper. Their feedback sounds like verdicts from the void: "Sorry, your model isn't mystical enough."
NeurIPS teaches one valuable lesson — before conquering the world, first conquer your reviewers.
ACL
The "ancestor" of NLP, acceptance rates low enough to shatter hearts.
ACL is like a dating event for language models, where researchers showcase their masterpieces only to realize "other people's children" always seem better.
Reviewers here act like literary inquisitors, scrutinizing your paper under a microscope for every potential logical flaw: "Why didn’t you use a larger dataset?" "Why didn't you try that model instead?"
ACL reveals an essential truth: forget fairness; believe only in your capabilities.
ICML
The "Spring Festival Gala" of machine learning, enormous and influential.
ICML is like an academic amusement park, where everyone chases the latest research trends. But remember, the entry ticket is your paper.
Reviewers here act like academic police, checking if your paper meets their aesthetic standards: "Your experimental design isn't innovative enough," or "Your results aren't impressive enough."
ICML reminds us there are no shortcuts, only relentless effort.
ICLR
The "rising star" of deep learning, with acceptance rates crushingly low.
ICLR is an academic influencer’s hotspot, with everyone eager to showcase their research. However, the entry threshold is deceptively high.
Reviewers here behave like fashion bloggers, critically evaluating if your paper aligns with their aesthetic tastes: "Your model isn’t flashy enough," "Your results aren't stunning enough."
ICLR imparts the truth—work hard, but never forget to be trendy.
The "mysticism" and "reality" of those conferences
Submissions are lotteries: Acceptance often relies heavily on your luck.- 🧩 Reviewers are puzzles: Their feedback can feel enigmatic, originating from mysterious realms.
Academic rat race: Top conferences resemble massive "paper factories," with everyone desperately chasing trends and novelty, sometimes realizing too late that their efforts were in vain.
Final thoughts
If your goal is to publish in top conferences, brace yourself for a prolonged psychological battle.
Yet remember, academic research aims to explore truths, not chase prestigious conference halos.
View submissions as part of your scholarly journey and feedback from reviewers as opportunities for growth. True academic value isn't measured by how many top papers you publish, but by your contributions to advancing the field.
