![[D] ICML Reviewer Acknowledgement](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-circuit-gold-PMJWD5qsqGfXwX8w9a97Cb.webp)
[D] ICML Reviewer Acknowledgement
Hi, I'm a little confused about ICML discussion period Does the period for reviewer acknowledging responses have already ended? One of the four reviewers did not present any answer to a paper of mine. Do you know if the reviewer can still change their score before April 7th? There is a reviewer comment that I will answer on Monday. Will the reviewer be able to update the score after seeing my answer? Thanks! submitted by /u/Massive_Horror9038 [link] [comments]
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[R] Looking for arXiv cs.LG endorser, inference monitoring using information geometry
Hi r/MachineLearning , I’m looking for an arXiv endorser in cs.LG for a paper on inference-time distribution shift detection for deployed LLMs. The core idea: instead of monitoring input embeddings (which is what existing tools do), we monitor the statistical manifold of the model’s output distributions using Fisher-Rao geodesic distance. We then run adaptive CUSUM (Page-Hinkley) on the resulting z-score stream to catch slow drift that per-request spike detection misses entirely. The methodology is grounded in published work on information geometry (Figshare, DOIs available). We’ve validated the signal on real OpenAI API logprobs, CUSUM caught gradual domain drift in 7 steps with zero false alarms during warmup, while spike detection missed it entirely. If anyone with cs.LG endorsement is
![[D] KDD Review Discussion](https://d2xsxph8kpxj0f.cloudfront.net/310419663032563854/konzwo8nGf8Z4uZsMefwMr/default-img-wave-pattern-4YWNKzoeu65vYpqRKWMiWf.webp)
[D] KDD Review Discussion
KDD 2026 (Feb Cycle) reviews will release today (4-April AoE), This thread is open to discuss about reviews and importantly celebrate successful reviews. Let us all remember that review system is noisy and we all suffer from it and this doesn't define our research impact. Let's all prioritise reviews which enhance our papers. Feel free to discuss your experiences submitted by /u/BomsDrag [link] [comments]
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