Row 8476

Row ID: 8476 | Dataset Entry | Axioma AXP Content Repository

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This page contains data entry 8476 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

I work on statistical ML. I notice that many people (including myself and those that I review) often recycle their submissions for ML conferences.

E.g., if their papers got rejected by ICML, they submit to NeurIPS, and later to ICLR (or UAI/AISTATS which are also top in my field). If they did not get into ICML/NeurIPS/ICLR after 2\~3 times, they would submit them to AAAI/IJCAI/TMLR/ICDM, journals like T-NNLS/T-KDD/NN/Neurocomputing, or domain-specific venues like LoG/CoLLAs/AABI. After all these, if the paper still did not get accepted, they then simply put them or arXiv. I believe this might also be the case for CV/NLP.

As a reviewer, I often encounter conference submissions where the authors resubmit without really taking into account the previous reviews provided. Sometimes they do incorporate the reviews when resubmitting--but sometimes the work may just be not at the level of Tier 1 conferences but they just keep resubmitting and hoping that they can accepted by chance.

I think that this is consuming a lot of reviewers' time from the community to keep reviewing the same submissions (especially given that NeurIPS hits 20k submission id; I expect to see many resubmissions). This is perhaps also one of the reason TMLR was born (to emphasize correctness instead of novelty).

I do understand arguments like "the quality of research is more important than the publication venues" or "OpenAI often simply just put their papers like GPT-X on arXiv these days". However, students or junior researchers also need publications in their career, including myself.

What do folks think about it?

FieldValue
text I work on statistical ML. I notice that many people (including myself and those that I review) often recycle their submissions for ML conferences. E.g., if their papers got rejected by ICML, they submit to NeurIPS, and later to ICLR (or UAI/AISTATS which are also top in my field). If they did not get into ICML/NeurIPS/ICLR after 2\~3 times, they would submit them to AAAI/IJCAI/TMLR/ICDM, journals like T-NNLS/T-KDD/NN/Neurocomputing, or domain-specific venues like LoG/CoLLAs/AABI. After all thes…
label r/machinelearning
dataType post
communityName r/MachineLearning
datetime 2024-05-19
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Raw Record

{
  "text": "I work on statistical ML. I notice that many people (including myself and those that I review) often recycle their submissions for ML conferences.\n\nE.g., if their papers got rejected by ICML, they submit to NeurIPS, and later to ICLR (or UAI/AISTATS which are also top in my field). If they did not get into ICML/NeurIPS/ICLR after 2\\~3 times, they would submit them to AAAI/IJCAI/TMLR/ICDM, journals like T-NNLS/T-KDD/NN/Neurocomputing, or domain-specific venues like LoG/CoLLAs/AABI. After all these, if the paper still did not get accepted, they then simply put them or arXiv. I believe this might also be the case for CV/NLP.\n\nAs a reviewer, I often encounter conference submissions where the authors resubmit without really taking into account the previous reviews provided. Sometimes they do incorporate the reviews when resubmitting--but sometimes the work may just be not at the level of Tier 1 conferences but they just keep resubmitting and hoping that they can accepted by chance.\n\nI think that this is consuming a lot of reviewers' time from the community to keep reviewing the same submissions (especially given that NeurIPS hits 20k submission id; I expect to see many resubmissions). This is perhaps also one of the reason TMLR was born (to emphasize correctness instead of novelty).\n\nI do understand arguments like \"the quality of research is more important than the publication venues\" or \"OpenAI often simply just put their papers like GPT-X on arXiv these days\". However, students or junior researchers also need publications in their career, including myself. \n\nWhat do folks think about it?",
  "label": "r/machinelearning",
  "dataType": "post",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-19",
  "username_encoded": "Z0FBQUFBQm5Lakw0VFNqSEQ4emxldDVISEtOMFpyWHRMcmVaWXVoSzcxU3pBNk5hc0R4dUprVURUUWRPbk1UTVNaNWJ4ZThkc2ZhVGNqSGExd3R2Ymd5eE4yRHlQUGszRXc9PQ==",
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}
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