Sepideh Mamooler
@smamooler
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PhD Candidate at @ICepfl 👩🏻💻 Working on multi-modal AI reasoning models in scientific domains | ex DeepMind Intern https://t.co/trZEyfX4Js
Switzerland
Joined February 2021
RT @abeirami: The leaderboards lack the needed granularity! . When we say model A is better than model B at text, that is too coarse. Even….
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RT @sarameghanbeery: The submission portal is now OPEN to take part in this interesting @NeurIPSConf 2025 data curation competition!! This….
dcvlr-neurips.github.io
Join the DCVLR NeurIPS 2025 Competition. Advance visual reasoning in VLMs through data curation.
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RT @ABosselut: The EPFL NLP lab is looking to hire a postdoctoral researcher on the topic of designing, training, and evaluating multilingu….
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RT @nikitasaxena02: Heading to @COLM_conf in Montreal?.So is @WiMLworkshop! 🎉. We are organizing our first ever event at #CoLM2025 and we w….
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RT @negarforoutan: 🚀 Excited to be at #ACL2025NLP in Vienna! @aclmeeting #ACL2025 .Let’s connect and chat about multilingual LLMs & long-….
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Also: not the usual #ACL topic, but if you're working on genetic AI models, I’d love to connect! I'm exploring the intersection of behavioral genomics and multi-modal AI for behavior understanding.
Excited to attend #ACL2025 in Vienna next week! .I’ll be presenting our #NAACL2025 paper, PICLe, at the first workshop on Large Language Models and Structure Modeling (XLLM) on Friday. Come by our poster if you’re into NER and ICL with pseudo-annotation.
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Excited to attend #ACL2025 in Vienna next week! .I’ll be presenting our #NAACL2025 paper, PICLe, at the first workshop on Large Language Models and Structure Modeling (XLLM) on Friday. Come by our poster if you’re into NER and ICL with pseudo-annotation.
arxiv.org
In-context learning (ICL) enables Large Language Models (LLMs) to perform tasks using few demonstrations, facilitating task adaptation when labeled examples are hard to obtain. However, ICL is...
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RT @negarforoutan: 📣The deadline is extended (June 30th)!.Consider submitting your multilingual work to #MELTWorkshop2025 #COLM2025.
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RT @silin_gao: NEW PAPER ALERT: Recent studies have shown that LLMs often lack robustness to distribution shifts in their reasoning. Our pa….
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RT @DamienTeney: Both are equally important, and the execution takes much more time and skills. Good-looking ideas and theories come at a d….
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RT @bkhmsi: 🚨New Preprint!!. Thrilled to share with you our latest work: “Mixture of Cognitive Reasoners”, a modular transformer architectu….
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RT @danvahdat: هر کسی که مهارتی دارد، چه داخل ایران چه خارج، و فکر میکند میتواند کمکی بکند، لطفاً ثبتنام کند. با شما در تماس خواهیم بود.….
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RT @danvahdat: با بعضی از ایرانیهایی که میشناسم صحبت کردهام. اما هنوز نمیفهمم چرا خیلیها فکر میکنن ما نمیتونیم چیزی رو عوض کنیم. چی….
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RT @danvahdat: To all my fellow countrymen living abroad,. Please don’t lose faith. Stay strong. We are a people of peace… descendants of a….
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RT @negarforoutan: Got ideas for making LLMs more inclusive and culturally aware? 🌍✨.Submit to #MELT Workshop 2025!.We’re all about multili….
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RT @aroraakhilcs: Thrilled to announce that our work “Fleet of Agents” has been accepted @icmlconf. On average, FoA boosts quality by ~5% w….
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Couldn't attend @naaclmeeting as I didn't get a visa on time 🤷♀️ My colleague @mismayilsoy will present PICLe on my behalf. Feel free to reach out if you want to chat more!.paper: code: data:
huggingface.co
Excited to share that we will present PICLe at @naacl main conference.
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Check out VinaBench, our new #CVPR2025 paper. We introduce a benchmark for faithful and consistent visual narratives. Paper: Project Page:
NEW PAPER ALERT: Generating visual narratives to illustrate textual stories remains an open challenge, due to the lack of knowledge to constrain faithful and self-consistent generations. Our #CVPR2025 paper proposes a new benchmark, VinaBench, to address this challenge.
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Excited to share that we will present PICLe at @naacl main conference.
🚀 Introducing PICLe: a framework for in-context named-entity detection (NED) using pseudo-annotated demonstrations. 🎯 No human labeling needed—yet it outperforms few-shot learning with human annotations!.#AI #NLProc #LLMs #ICL #NER
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