Rogerio Feris

CDS Silver Professor Julia Kempe (@KempeLab) is co-organizing this year's ICLR 2026 Workshop on New Frontiers in Associative Memory. The workshop is accepting submissions related to associative memory until Feb 14. nfam2026.amemory.net

🚀 Our Memory and Vision (MemVis) Workshop is happening this Sunday 8:30am-1pm, Oct 19 at #ICCV2025 in Honolulu, Hawaii! 📍 Room #304B 🕘 Full schedule is live Join us and our amazing speakers to explore how memory connects with vision models through inspiring talks, panels, and posters! 💫 Finally, huge thanks to our generous sponsor @abaka_ai, and join us in Happy Hour here: luma.com/m7xwirk0

MemVis @ #ICCV2025 -- 1st Workshop on Memory & Vision! 🧠👁️ Call for papers now open: Hopfield & energy nets, state-space + diffusion models, retrieval & lifelong learning, long-context FMs, multimodal memory, & more. 🗓️ Submit by 1 Aug 2025 → sites.google.com/view/memvis-ic… 🌺 #MemVis

🎉 Our paper “M+: Extending MemoryLLM with Scalable Long-Term Memory” is accepted to ICML 2025! 🔹 Co-trained retriever + latent memory 🔹 Retains info across 160k+ tokens 🔹 Much Lower GPU cost compared to backbone LLM arxiv.org/abs/2502.00592

🎯 Introducing Sparse Attention Vectors (SAVs): A breakthrough method for extracting powerful multimodal features from Large Multimodal Models (LMMs). SAVs enable SOTA performance on discriminative vision-language tasks (classification, safety alignment, etc.)! Links in replies! 🔎Using just ~20 attention heads & only few-shot examples, SAVs: - Outperform both LoRA and few-shot baselines - Work with image, text, & interleaved inputs - Extract features without finetuning - ready to go at test time! This project was a cross-collaborative effort between researchers from UC Berkeley, Carnegie Mellon University, and MIT-IBM Research (@berkeley_ai, @CMU_Robotics, @MITIBMLab). Many thanks to all of the collaborators and co-authors on this work: Brandon Huang, Tianning (Ray) Chai, @ZhiqiuLin, @ArbelleAssaf, @RogerioFeris, @leokarlin, @trevordarrell, @RamananDeva, @roeiherzig

Granite 3.0 is our latest update for the IBM foundation models. The 8B and 2B models outperform strong competitors with similar sizes. The 1B and 3B MoE use only 400M and 800M active parameters to target the on-device use cases. Our technical report provides all the details you need to train a state-of-the-art 8B model from scratch! github.com/ibm-granite/gr…

Welcome to join our workshop to figure out what is next in Multimodal foundation models! Tuesday 08:30 Pacific Time, Summit 437-439 at Seattle Convention Center Summit🤖

Thanks for the highlight @_akhaliq! We offer a simple and nearly-data-free way to move (large quantities) of custom PEFT models within or across LLM families or even across PEFT configurations. Useful for LLM cloud hosting when old base models need to be deprecated & upgraded

We have a cool challenge on understanding document images in our 2nd #CVPR2024 workshop on “What is Next in Multimodal Foundation Models?”, (sites.google.com/view/2nd-mmfm-…). This is a great opportunity to showcase your work in front of a large audience (pic below from our 1st workshop)

IBM & Meta are launching the AI Alliance to advance *open* & reliable AI. The list of over 50 founding members from industry, government, and academia include AMD, Anyscale, CERN, Hugging Face, the Linux Foundation, NASA.... ai.meta.com/blog/ai-allian…

@EhsaanA99918076 @MITIBMLab We are requiring interns to be physically present in our Cambridge office

@RogerioFeris @MITIBMLab remote internship is possible?

Our team is hiring 2024 summer interns. We are doing research towards augmenting large language models with memory, multiple modalities (vision, speech, sound, …), and specializing LLMs for enterprise domains. @MITIBMLab

Apply here: careers.ibm.com/job/19215487/i…[…]jcz*_ga_FYECCCS21D*MTY5NzQ5MjI3My4xLjAuMTY5NzQ5MjI4MS4wLjAuMA/

🚨Can we self-align LLMs with an expert domain like biomedicine with limited supervision? Introducing Self-Specialization, uncovering expertise latent within LLMs to boost their utility in specialized domains. arxiv.org/abs/2310.00160 @ICatGT @mlatgt @MIT_CSAIL @MITIBMLab 1/8

What could be the computational function of astrocytes in the brain? We hypothesize that they may be the biological cells that could implement the Transformer's attention operation commonly used in AI. Much improved compared to an earlier preprint: pnas.org/doi/10.1073/pn…

(1/3)🤔Wondering what's transferred between the pre-training and fine-tuning? Our ACL finding looks into this question with synthetic pre-training tasks for MT. Surprisingly, most pre-training benefits are realized even with 75% nonsense parallel corpus or purely synthetic data!

Recent advances in Hopfield networks of associative memory may be the guiding theoretical principle for designing novel large scale neural architectures. I explain my enthusiasm about these ideas in the article ⬇️⬇️⬇️. Please let me know what you think. nature.com/articles/s4225…

We can all agree we’re at a unique and evolutionary moment in AI, with enterprises increasingly turning to this technology’s transformative power to unlock new levels of innovation and productivity. At #Think2023, @IBM unveiled watsonx. Learn more: newsroom.ibm.com/2023-05-09-IBM…

New technique from the @MITIBMLab and its collaborators learns to "grow" a larger machine-learning model from a smaller, pre-trained model, reducing the monetary and environmental cost of developing AI applications and with similar or improved performance. news.mit.edu/2023/new-techn…

We are looking for a summer intern (MSc/PhD) to work on large language models for sports & entertainment, with the goal of improving the experience of millions of fans as part of major tournaments (US Open/Wimbledon) @IBMSports @MITIBMLab Apply at: #jobDetails=662537_5016" target="_blank" rel="nofollow noopener">krb-sjobs.brassring.com/TGnewUI/Search…