'There's a new generation of empirical deep learning researchers, hacking away at whatever seems trendy, blowing with the wind' [D]

This is a discussion thread on r/MachineLearning critiquing a perceived cultural shift in AI research, where a newer wave of empirical deep learning researchers is characterized as prioritizing trendy topics over principled, theory-driven inquiry. The post likely sparks debate about research quality, rigor, and whether chasing popular trends (e.g., the latest architectures or benchmark tasks) undermines deeper scientific understanding in the field. Community responses likely include both defenses of empirical, results-driven approaches and concerns about the lack of foundational theoretical grounding in modern ML research.

Just did an analysis on ICLR 2025 vs 2026 scores and WOW [D]
[[d-how-are-reviewers-able-to-get-away-without-providing-ackno|[D] How are reviewers able to get away without providing acknowledgement in ICML 2026?]]
Getting sabotaged by a reviewer at IJCAI [D]
[[d-dealing-with-an-unprofessional-reviewer-using-fake-referen|[D] Dealing with an unprofessional reviewer using fake references and personal attacks in ICML26]]
Post Rebuttal ICML Average Scores? [D]

Source: r/MachineLearning | 2026-04-12

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