TMLR
Transactions on Machine Learning Research (TMLR) is a peer-reviewed academic journal in the field of machine learning. It is characterized by open-access publication and an expedited review process, and it accepts research papers covering a broad range of machine learning topics.
Core Facts
Timeline (last 90 days)
In a paper published in TMLR (Transactions on Machine Learning Research), Sakana AI proposed a mechanism called Multi-Layered Review (MLR).
The TMLR editorial board proactively contacted the authors of 10 submissions on the desk-rejection watchlist and asked them to personally explain their submitted papers.
In TMLR's experiment, not a single one of the 10 papers held up under personal defense by the authors.
Among the 10 papers, 1 author directly withdrew the submission, 1 author declined citing other commitments, and 1 author scheduled a meeting but did not show up.
Among the 10 papers, 3 authors were unable to answer basic questions about their papers, and 3 authors could discuss high-level ideas but were unable to answer technical details.
Among the 10 papers, 1 author answered all questions, but the action editor discovered a significant flaw in the paper during the interview process.
TMLR officially published an explanatory article about this experiment on Medium.
TMLR uses a rolling submission system, without the natural traffic modulation that comes from deadlines.
Having authors verbally explain their own papers is difficult to scale, as it requires a substantial time investment and raises fairness concerns regarding oral defense.
TMLR's process is highly dependent on the proactive management of Action Editors (AEs), and when AEs are overburdened, the entire process can come to a standstill.
9 more timeline events
All Facts (17)
TMLR (Transactions on Machine Learning Research) was officially launched in 2022.
75%UnverifiedHaving authors verbally explain their own papers is difficult to scale, as it requires a substantial time investment and raises fairness concerns regarding oral defense.
50%UnverifiedIn TMLR's experiment, not a single one of the 10 papers held up under personal defense by the authors.
50%UnverifiedAmong the 10 papers, 1 author directly withdrew the submission, 1 author declined citing other commitments, and 1 author scheduled a meeting but did not show up.
50%UnverifiedAmong the 10 papers, 3 authors were unable to answer basic questions about their papers, and 3 authors could discuss high-level ideas but were unable to answer technical details.
50%UnverifiedAmong the 10 papers, 1 author answered all questions, but the action editor discovered a significant flaw in the paper during the interview process.
50%UnverifiedTMLR officially published an explanatory article about this experiment on Medium.
50%UnverifiedTMLR uses a rolling submission system, without the natural traffic modulation that comes from deadlines.
50%UnverifiedTMLR was co-founded by prominent scholars in the field of deep learning including Yoshua Bengio, with support from the Machine Learning Foundation (MLF).
50%UnverifiedTMLR is an open access journal in the field of machine learning that adopts a rolling submission review model with no fixed deadlines, accepting submissions year-round.
50%UnverifiedTMLR takes "technical correctness" and "supported claims" as its core acceptance criteria, rather than pursuing "novelty" or "impact".
50%UnverifiedTMLR's review philosophy was inspired by the concept of "continuous integration" from the field of software engineering.
50%UnverifiedTMLR uses the OpenReview platform for open peer review, making the review process transparent and traceable.
50%UnverifiedTMLR's review speed is noticeably slowing down because submission volume is rising while reviewer resources have not grown in tandem.
50%UnverifiedTMLR's process is highly dependent on the proactive management of Action Editors (AEs), and when AEs are overburdened, the entire process can come to a standstill.
50%UnverifiedIn a paper published in TMLR (Transactions on Machine Learning Research), Sakana AI proposed a mechanism called Multi-Layered Review (MLR).
50%UnverifiedThe TMLR editorial board proactively contacted the authors of 10 submissions on the desk-rejection watchlist and asked them to personally explain their submitted papers.
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