Marek Rei

@marekrei.bsky.social

AI/ML/NLP researcher and Senior Lecturer at Imperial College London. Working on language models for planning, reasoning and interpretable decision making

🚀 Imperial NLP is heading to #ACL2026 & #ICML2026 with 23 papers! From reasoning and agents to interpretability, RL, safety, and healthcare models, our students & faculty have been busy. Come find us in San Diego 🌴 and Seoul 🇰🇷 to talk research, swap ideas, and say hi!

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📢⚠️ IMPORTANT DATE CORRECTION: the ARR deadline for EACL 2027 is Aug 3, 2026 (not Aug 6 as previously announced). EACL is earlier than usual in '27, so this is the only viable ARR cycle! 📚 All areas of CL/NLP + related fields welcome. Full CfP coming soon. #NLProc #EACL2027

EACL 2027@eaclmeeting.bsky.social · 3mo ago

Attention #NLProc researchers, the EACL 2027 website is officially LIVE: 2027.eacl.org! 🎉 🇬🇷 Join us in Athens, Greece (Mar 9-13, 2027) at #EACL2027 📅 ARR submission deadline: Aug 6, 2026. Open to all areas of CL/NLP + related fields. Stay tuned for the detailed CfP soon!

Picture of the Acropolis in Athens, Greece

We are excited to celebrate the launch of the #GenAIHubLaunch today. The Hub's mission is to unlock the next generation of Generative AI technologies. Congratulations to our Director, A. Aldo Faisal, for co-leading the Hub's Healthcare Working Group. Find out more➡️ www.genai.ac.uk

gen ai

We will help to transform science, industry, the economy and society through developing the next generation of generative AI models.

genai.ac.uk

Congratulations to our colleagues at @ai4healthcentre.bsky.social, including Aldo and Marek, for the launch of Nightingale AI. We are delighted you chose our event to announce this exciting initiative.

Marek Rei@marekrei.bsky.social · last yr.

Today was the launch event of the @genaihub.bsky.social. We announced the development of Nightingale AI, a foundation world model for health. It was great to be on the panel for GenAI in Healthcare, among such amazing experts. www.genai.ac.uk

Do LLMs need rationales for learning from mistakes? 🤔 When LLMs learn from previous incorrect answers, they typically observe corrective feedback in the form of rationales explaining each mistake. In our new preprint, we find these rationales do not help, in fact they hurt performance! 🧵

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We are hiring 6 lecturers at @imperialcollegeldn.bsky.social to work on AI, ML, graphics, vision, quantum and software engineering. This includes researchers working on LLMs, NLP, generative models and text applications. Deadline 6 Jan. @imperial-nlp.bsky.social www.imperial.ac.uk/jobs/search-...

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Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities ment...

imperial.ac.uk

Hi Bluesky, would like to introduce myself 🙂 I am PhD-ing at Imperial College under @marekrei.bsky.social’s supervision. I am broadly interested in LLM/LVLM reasoning & planning 🤖 (here’s our latest work arxiv.org/abs/2411.04535) Do reach out if you are interested in these (or related) topics!

Meta-Reasoning Improves Tool Use in Large Language Models

External tools help large language models (LLMs) succeed at tasks where they would otherwise typically fail. In existing frameworks, LLMs learn tool use either by in-context demonstrations or via full...

arxiv.org