A Reddit discussion examines the perceived prestige of journal publications compared to conference submissions in the machine learning community.
Category: Education
A post on r/MachineLearning that gathered over 70 upvotes is stirring conversations about the implications of submitting research exclusively to journals versus conferences in the field of machine learning.
In academia, the debate on whether to prioritize journal publications or conference submissions has long been a contentious topic. Traditionally, journals have been viewed as the gold standard for publishing research, often associated with more rigorous peer review processes. Yet, within the machine learning community, conferences like NeurIPS and ICML are increasingly seen as equally, if not more, prestigious.
One Redditor, u/atomatoma, emphasized that conferences are important for networking and receiving feedback from peers. They noted that journal publications can carry more weight in terms of impact points, depending on the journal's quality. "Conferences are very valuable for progressing your career since you get to interact with your community," they said.
Another user, u/kostaspap90, mentioned considering a shift from conference submissions to journals. They pointed out that top journals such as the Journal of Machine Learning Research (JMLR) are typically viewed as more prestigious than top conferences like ICML, but they come with challenges, including a slower review process. "Top journals... are harder to get into and much much slower in terms of the review process, so not sure if worth it," they added.
Some users questioned the negative perceptions surrounding journal submissions. One commenter, u/Ok-Painter573, expressed confusion about why journals would be viewed negatively, stating, "Isn't journals considered more prestigious? Why would it affect negatively?" This sentiment reflects a broader uncertainty among newcomers to academia about the hierarchy of publication venues.
Discussion continued with u/hyperactve weighing in on the varying reputations of different journals. They noted that journals like Nature and JMLR maintain high standards, whereas newer journals like TMLR are still establishing their reputations. "The reviews are good... but we have to see what happens in the long run," they cautioned.
On the other hand, u/GermanBusinessInside shared an industry perspective, stating that publication venues hold less significance in practical applications. "In academia, it's a different story though — conferences like NeurIPS/ICML carry way more weight than journals in ML... which is kind of the opposite of most other fields," they explained. This highlights the unique dynamics of machine learning as a discipline, where conference presentations can significantly influence career trajectories.
Redditor u/pastor_pilao challenged the focus on prestige, arguing that the true purpose of conferences is often overlooked. They asserted that there isn't a substantial difference in CV impact between having papers published in respected journals like JAIR or JMLR versus presenting at top conferences. "Except for the smaller companies that don't really do research and put 'NeurIPS' on their CVs," they noted, emphasizing the importance of research quality over venue.
One user, u/Lonely-Dragonfly-413, encouraged fellow researchers to remain optimistic about the conference review process. They pointed out that major conferences like NeurIPS, ICML, and ICLR collectively accept around 15,000 papers annually. "As long as your paper is solid and you keep improving your paper based on the feedback, it will be accepted in the end," they advised.
The conversation also touched on historical perspectives. User u/impatiens-capensis shared an anecdote about a relative who had a NeurIPS paper from over a decade ago, noting that the perception of prestige has shifted over time. "Who knows what will be prestigious in 10 years! But the conference model is broken and something needs to change," they remarked.
Many Reddit users contributed their thoughts on the topic, illustrating a range of opinions:
One user argued that journal articles are more thorough and provide a comprehensive overview of research, making them valuable for in-depth studies.
Another commenter insisted that conferences offer immediate feedback and networking opportunities that are invaluable for early-career researchers.
A different viewpoint highlighted the speed of publication at conferences versus the lengthy review process of journals, which can hinder timely dissemination of research findings.
Some users expressed skepticism about the future of academic publishing, questioning whether the traditional models will continue to hold relevance in a rapidly changing field.
This discussion reflects broader trends in academia, particularly in fast-evolving fields like machine learning. The rise of online platforms and open-access journals is reshaping how research is disseminated and valued. As new models emerge, the established norms of journal versus conference prestige may continue to evolve.
Experts suggest that the emphasis on publication venues may shift as the community adapts to new technologies and methodologies. The increasing importance of collaboration and interdisciplinary research could also influence how researchers choose to publish their work.
The debate over the value of journal versus conference publications in machine learning is indicative of larger trends in academia. How researchers navigate these choices can impact their careers and the future of the discipline. As the community continues to engage in discussions like this one, the outcomes could shape the next generation of academic publishing.