Ph.D. student at @UMichCSE, adviced by @radamihalcea. Learning and working on AI. Wants to get lost in the mountains with a good book and a cup of coffee.
Ann Arbor, MI
Joined February 2014
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Samee Arif retweeted
🚨 Excited to share that our paper "One Example Is Enough to Pass Fairness Benchmarks: Rethinking Fairness Evaluation for Aligned LLMs" has been accepted to EMNLP 2026 (Main)! 🎉
Samee Arif retweeted
🌎 A dataset says it covers Spanish. But whose Spanish?
Spanish is spoken across Spain and much of Latin America, from Mexico to Argentina and beyond. Yet an NLP dataset labeled simply “Spanish” may contain data representing only a small subset of those countries.
Samee Arif retweeted
Happy to share that this work has been accepted to EMNLP 2026 Main! 🤗
Excited to share our new preprint:
Whose Norms? Disentangling Cultural and Personal Alignment in Large Language Models
We ask: when cultural norms and personal preferences conflict, whose norms do LLMs follow? 🌍⚖️
Check out our work here:
📄 Paper: arxiv.org/abs/2606.07877
🤗 Dataset: huggingface.co/datasets/Anga…
💻 Code: github.com/MichiganNLP/pact_…
🌐 Website: lit.eecs.umich.edu/pact_cult… (1/n)
Samee Arif retweeted
🌍⚡ New paper: The Language–Energy Divide
Does the language you ask in change how much energy an LLM burns to answer? 👉 Yes — and the gap is enormous.
We measured LLM inference energy across 122 languages and found a systemic divide:
⚡ Up to 8.3× more energy per token across languages — same model, same task
🔋 Up to 179× more total energy per request set: English (17.6 kJ) vs. Pashto (3,147 kJ)
📉 A double penalty — the languages that cost the most to serve are also the ones answered least accurately
