Iman Mirzadeh @i_mirzadeh

Machine Learning Research Engineer @Apple | opinions are my own. imirzadeh.me Seattle Joined October 2024

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Fartash Faghri @FartashFg

a month ago

📢Submissions are now open for #NeurIPS2025 CCFM workshop. Submission deadline: August 22, 2025, AoE. Website: sites.google.com/view/ccfm-neur… Call for papers: sites.google.com/view/ccfm-neur… Submission Link: openreview.net/group?id=NeurI…

Is your AI keeping Up with the world? Announcing #NeurIPS2025 CCFM Workshop: Continual and Compatible Foundation Model Updates When/Where: Dec. 6-7 San Diego Submission deadline: Aug. 22, 2025. (opening soon!) sites.google.com/view/ccfm-neur… #FoundationModels #ContinualLearning

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Oncel Tuzel @OncelTuzel

2 months ago

Come work with us! The Machine Learning Research (MLR) team at Apple is seeking a passionate AI researcher to work on Efficient ML algorithms: jobs.apple.com/en-us/details/…

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Epoch AI @EpochAIResearch

3 months ago

The biggest weakness was a lack of creativity and deep understanding. This is perhaps most aptly captured by a quote from one of the mathematicians:

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Gary Marcus @GaryMarcus

3 months ago

Healthy and unhealthy strategies for coping with the Apple paper: - attack Apple for publishing it (which does nothing to address the underlying problems they pointed out) or - figure out its implications and develop a robust alternative (the healthier option)

Andrew White 🐦‍⬛ @andrewwhite01

3 months ago

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Mehrdad Farajtabar @MFarajtabar

3 months ago

🧵 1/8 The Illusion of Thinking: Are reasoning models like o1/o3, DeepSeek-R1, and Claude 3.7 Sonnet really "thinking"? 🤔 Or are they just throwing more compute towards pattern matching? The new Large Reasoning Models (LRMs) show promising gains on math and coding benchmarks,…

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Iman Mirzadeh @i_mirzadeh

5 months ago

I will be attending #ICLR this week to present our GSM-Symbolic paper, and we also have a full-time opening on our team! Let me know if you're interested in discussing reasoning and/or joining us!

Mehrdad Farajtabar @MFarajtabar

5 months ago

I will be attending #ICLR this week to present our GSM-Symbolic paper, and we also have a full-time opening on our team! Let me know if you're interested in discussing reasoning and/or joining us!

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Iman Mirzadeh @i_mirzadeh

6 months ago

It was a pleasure joining @MLStreetTalk during the NeurIPS conference in December. While it might seem that a lot has changed over the past 3 months (e.g., with new models like o3/R1), I still believe the current models are not capable of reasoning :) youtube.com/watch?v=yQPdue…

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Iman Mirzadeh @i_mirzadeh

6 months ago

Exactly! I wish that at least academic people understood this. "All" models we have today are trained using cross-entropy to fit a distribution => By design, It is "impossible" for them to generate anything outside of that distribution.

BURKOV @burkov

6 months ago

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Iman Mirzadeh @i_mirzadeh

7 months ago

Amazing analysis! This has been THE question I was thinking about every single day in the past month. Although, I think if the model knows the algorithm (multiplication), we can only measure the accuracy of execution by the model and not necessarily their search/reasoning power.

Nouha Dziri @nouhadziri

7 months ago

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Pierre Ablin @PierreAblin

9 months ago

🍏🍏🍏 Come work with us at Apple Machine Learning Research! 🍏🍏🍏 Our team focuses on curiosity-based, open research. We work on several topics, including LLMs, optimization, optimal transport, uncertainty quantification, and generative modeling. Infos 👇

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Iman Mirzadeh @i_mirzadeh

9 months ago

We have open-sourced GSM-Symbolic templates and generated data! 🎉 - Github: github.com/apple/ml-gsm-s… - Hugging Face: huggingface.co/datasets/apple… I will be also attending #NeurIPS2024. If you are also attending and would like to discuss research ideas on reasoning, let's connect :)

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Atoosa Chegini @AtoosaChegini

10 months ago

1/🔔Excited to share my internship work, SALSA: Soup-based Alignment Learning for Stronger Adaptation, (NeurIPS workshop paper)! 🎉 Proximal Policy Optimization (PPO) often limits exploration by keeping models tethered to a single reference model. SALSA, however, breaks free…

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Mehrdad Farajtabar @MFarajtabar

11 months ago

1/ LLM inference is very expensive; and LLMs don't necessarily use their full capacity to respond to a specific prompt. That's why many researchers have been investigating adaptive computation methods such as early exiting, layer/expert pruning, speculative decoding, mixture of…

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Mehrdad Farajtabar @MFarajtabar

11 months ago

** Intern position on LLM reasoning ** @mchorton1991, @i_mirzadeh, @KeivanAlizadeh2 and I are co-hosting an intern position at #Apple to work on understanding and improving reasoning capabilities of LLMs. The ideal candidate: - Has prior publications on LLM reasoning - Is…

Mehrdad Farajtabar @MFarajtabar

11 months ago

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Sinead Williamson @sineadwilliamso

11 months ago

📢Internships at Apple ML Research🍏 We’re looking for a PhD research intern with interests in uncertainty quantification, LLMs, probabilistic ML and/or decision making under uncertainty! See thread for more details 👇 [1/3]

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Mehrdad Farajtabar @MFarajtabar

11 months ago

1/ Can Large Language Models (LLMs) truly reason? Or are they just sophisticated pattern matchers? In our latest preprint, we explore this key question through a large-scale study of both open-source like Llama, Phi, Gemma, and Mistral and leading closed models, including the…

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Iman Mirzadeh @i_mirzadeh

11 months ago

I was waiting and hoping the ML community on Twitter would move over to Mastodon so I wouldn't have to create an account here. But, well… here we are! :)