From 6ba3251cfb8c1e87d91ab6ba9c0ae365f4afbdfb Mon Sep 17 00:00:00 2001 From: Yani Ioannou Date: Tue, 27 Jan 2026 00:09:51 +0000 Subject: [PATCH 1/4] Misc updates including ICLR paper --- _bibliography/papers.bib | 18 ++++++++++++------ _news/announcement_27_mike_borealis.md | 6 ++++++ ...nt_27_tejas.md => announcement_28_tejas.md} | 0 _news/announcement_29_reap_ICLR.md | 8 ++++++++ _people/manuel_zamudiolopez.md | 4 ++-- 5 files changed, 28 insertions(+), 8 deletions(-) create mode 100644 _news/announcement_27_mike_borealis.md rename _news/{announcement_27_tejas.md => announcement_28_tejas.md} (100%) create mode 100644 _news/announcement_29_reap_ICLR.md diff --git a/_bibliography/papers.bib b/_bibliography/papers.bib index 73032c537356e..f022ecb67b899 100644 --- a/_bibliography/papers.bib +++ b/_bibliography/papers.bib @@ -1,18 +1,24 @@ --- 2025 -@article{lasby2025reapexpertspruningprevails_preprint, +@inproceedings{lasby2025reapexpertspruningprevails, title={REAP the Experts: Why Pruning Prevails for One-Shot MoE compression}, author={Mike Lasby and Ivan Lazarevich and Nish Sinnadurai and Sean Lie and Yani Ioannou and Vithursan Thangarasa}, - year={2025}, + year={2026}, EPRINTTYPE={arXiv}, eprint={2510.13999}, archivePrefix={arXiv}, ARXIVID={2510.13999}, primaryClass={cs.LG}, - month={10}, - year={2025}, - ABBR={arXiv preprint}, - journal = {arXiv preprint arXiv:2510.13999}, + month={4}, + year={2026}, + BOOKTITLE = {{International Conference on Learning Representations (ICLR)}}, + ABBR={ICLR}, + VENUE = {{Rio de Janeiro, Brazil}}, + EVENTDATE = {2026-04-23/2026-04-27}, + openreview = {https://openreview.net/forum?id=ukGxWd2aDG}, + pdf = {https://openreview.net/pdf?id=ukGxWd2aDG}, + code = {https://github.com/CerebrasResearch/reap}, + blog = {https://www.cerebras.ai/blog/reap}, bibtex_show={true} } diff --git a/_news/announcement_27_mike_borealis.md b/_news/announcement_27_mike_borealis.md new file mode 100644 index 0000000000000..ed4d84ad8d8d7 --- /dev/null +++ b/_news/announcement_27_mike_borealis.md @@ -0,0 +1,6 @@ +--- +layout: post +date: 2025-11-19 00:00:00-0700 +inline: true +--- +Mike Lasby was announced as one of only 10 [RBC Borealis 2025 AI Fellows](https://rbcborealis.com/news/the-2024-2025-rbc-borealis-fellows-driving-the-future-of-ai/). diff --git a/_news/announcement_27_tejas.md b/_news/announcement_28_tejas.md similarity index 100% rename from _news/announcement_27_tejas.md rename to _news/announcement_28_tejas.md diff --git a/_news/announcement_29_reap_ICLR.md b/_news/announcement_29_reap_ICLR.md new file mode 100644 index 0000000000000..601577b854dc2 --- /dev/null +++ b/_news/announcement_29_reap_ICLR.md @@ -0,0 +1,8 @@ +--- +layout: post +date: 2026-01-26 00:00:00-0700 +inline: true +--- + +[Mike Lasby's](/labmembers/) collaborative work with Cerebras, "REAP the experts: Why pruning prevails for one-shot moe compression" {% cite lasby2025reapexpertspruningprevails %}, has been accepted at the [International Conference on Learning Representations (ICLR), 2026](https://iclr.cc/Conferences/2026). +This work explores the compression of Mixture of Experts (MoE) models through pruning techniques, demonstrating that REAP (Random Expert and Prune) outperforms existing expert-merging focused methods in terms of efficiency and performance retention. diff --git a/_people/manuel_zamudiolopez.md b/_people/manuel_zamudiolopez.md index 629a5eda58f80..8629481d37795 100644 --- a/_people/manuel_zamudiolopez.md +++ b/_people/manuel_zamudiolopez.md @@ -3,12 +3,12 @@ layout: page firstname: Manuel lastname: Zamudio Lopez pronouns: he/him -description: PhD Student co-supervised with Dr. Hamidreza Zareipour (Fall 2022 - Present) +description: PhD Student co-supervised with Dr. Hamidreza Zareipour (Fall 2022 - Winter 2026) img: assets/img/people/manuel_zamudiolopez.jpg redirect: https://www.linkedin.com/in/manuel-zamudio orcid_id: 0009-0009-7460-8178 linkedin_username: manuel-zamudio scholar_userid: 4eW8V0YAAAAJ -category: PhD Students +category: Alumni show: true --- From 766e6fe5d55c525cc89d75309000c354e6f84107 Mon Sep 17 00:00:00 2001 From: Yani Ioannou Date: Tue, 27 Jan 2026 00:20:27 +0000 Subject: [PATCH 2/4] Prettier fix --- _news/announcement_27_mike_borealis.md | 1 + 1 file changed, 1 insertion(+) diff --git a/_news/announcement_27_mike_borealis.md b/_news/announcement_27_mike_borealis.md index ed4d84ad8d8d7..38252bc903738 100644 --- a/_news/announcement_27_mike_borealis.md +++ b/_news/announcement_27_mike_borealis.md @@ -3,4 +3,5 @@ layout: post date: 2025-11-19 00:00:00-0700 inline: true --- + Mike Lasby was announced as one of only 10 [RBC Borealis 2025 AI Fellows](https://rbcborealis.com/news/the-2024-2025-rbc-borealis-fellows-driving-the-future-of-ai/). From 16baa2777423609b20b059b3bda37a24b989d8dd Mon Sep 17 00:00:00 2001 From: Yani Ioannou <1568965+yanii@users.noreply.github.com> Date: Tue, 27 Jan 2026 13:23:46 -0700 Subject: [PATCH 3/4] Update _bibliography/papers.bib Co-authored-by: Mike Lasby <64917385+mklasby@users.noreply.github.com> --- _bibliography/papers.bib | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_bibliography/papers.bib b/_bibliography/papers.bib index f022ecb67b899..5db74827cf2cc 100644 --- a/_bibliography/papers.bib +++ b/_bibliography/papers.bib @@ -9,7 +9,7 @@ @inproceedings{lasby2025reapexpertspruningprevails archivePrefix={arXiv}, ARXIVID={2510.13999}, primaryClass={cs.LG}, - month={4}, + month={1}, year={2026}, BOOKTITLE = {{International Conference on Learning Representations (ICLR)}}, ABBR={ICLR}, From 71d504c4612c05526591e1570e1deedbb8f07864 Mon Sep 17 00:00:00 2001 From: Yani Ioannou <1568965+yanii@users.noreply.github.com> Date: Tue, 27 Jan 2026 13:23:55 -0700 Subject: [PATCH 4/4] Update _news/announcement_29_reap_ICLR.md Co-authored-by: Mike Lasby <64917385+mklasby@users.noreply.github.com> --- _news/announcement_29_reap_ICLR.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/_news/announcement_29_reap_ICLR.md b/_news/announcement_29_reap_ICLR.md index 601577b854dc2..40d05c1ae890b 100644 --- a/_news/announcement_29_reap_ICLR.md +++ b/_news/announcement_29_reap_ICLR.md @@ -5,4 +5,4 @@ inline: true --- [Mike Lasby's](/labmembers/) collaborative work with Cerebras, "REAP the experts: Why pruning prevails for one-shot moe compression" {% cite lasby2025reapexpertspruningprevails %}, has been accepted at the [International Conference on Learning Representations (ICLR), 2026](https://iclr.cc/Conferences/2026). -This work explores the compression of Mixture of Experts (MoE) models through pruning techniques, demonstrating that REAP (Random Expert and Prune) outperforms existing expert-merging focused methods in terms of efficiency and performance retention. +This work explores the compression of Sparse Mixture of Experts (SMoE) models through expert compression techniques, demonstrating that REAP (Router-weighted Expert Activation Pruning) outperforms existing expert merging and pruning methods in terms of compressed model quality retention.