Ammar Khairi
@ammar__khairi
New account. Research Scholar @Cohere_Labs
I’m very excited to be co-organizing this @NeurIPSConf workshop on LLM evaluations! Evaluating LLMs is a complex and evolving challenge. With this workshop, we hope to bring together diverse perspectives to make real progress. See the details below:
We are happy to announce our @NeurIPSConf workshop on LLM evaluations! Mastering LLM evaluation is no longer optional -- it's fundamental to building reliable models. We'll tackle the field's most pressing evaluation challenges. For details: sites.google.com/corp/view/llm-…. 1/3
We have an incredible roster of accepted papers at @aclmeeting 2025. I will be there, as will many of our senior and engineering staff @mziizm @beyzaermis @mrdanieldsouza @singhshiviii 🔥 Looking forward to catching up with everyone.
There’s less than one week to go until @aclmeeting in Vienna, Austria! 🇦🇹 The Cohere Labs and @Cohere research teams are looking forward to showcasing some of our latest research and connecting with the community. Be sure to stop by our booth and say hello!
i had the chance to talk with @geoffreyhinton about existential risk, AI sentience, and art the other day. I admit its challenging to disagree with a Nobel laureate and the guy who taught me everything i know about AI, but i did my best. youtube.com/watch?v=S4Tz7d…
🖼️ What does it take to build a multilingual image generation model that is both efficient and competitive? 🌍 In collaboration with @UvA_Amsterdam, we introduce NeoBabel, a 2B multilingual text-to-image model trained natively in 6 languages.
When Life Gives You Samples The Benefits of Scaling up Inference Compute for Multilingual LLMs
Wow wasn't expecting this! Thanks so much for the kind message @Cohere_Labs! Big shoutout to @mrdanieldsouza and @sarahookr for all the help & support they've given me as coauthors and now coworkers :)
@weiyinko_ml was one of the earliest members of our Open Science Community and an early collaborator on our open science research. We’re proud to have been part of Wei-Yin’s journey from community collaborator to colleague, and grateful he took an early bet on working with us 🚀
Can we improve the performance of LLMs during inference without the need for extensive sampling OR special reward models? 🤔 Our latest work introduces a new inference time scaling recipe that is sample-efficient, multilingual, and suitable for multi-task requirements. 🍋
🚨New Recipe just dropped! 🚨 "LLMonade 🍋" ➡️ squeeze max performance from your multilingual LLMs at inference time !👀🔥 🧑🍳@ammar__khairi shows you how to 1⃣ Harvest your Lemons 🍋🍋🍋🍋🍋 2⃣ Pick the Best One 🍋
🚀 Want better LLM performance without extra training or special reward models? Happy to share my work with @Cohere_labs : "When Life Gives You Samples: Benefits of Scaling Inference Compute for Multilingual LLMs" 👀How we squeeze more from less at inference 🍋, details in 🧵
We’re excited to be a founding participant in the @StanfordDDL Industry-Wide Forum on AI agents alongside @Meta, @Oracle, and @PayPal. We look forward to working with other industry leaders to shape the future of AI agents with responsible development and cross-industry…