Our team at Google DeepMind is hiring a Research Scientist in Mountain View!
Focus is on bridging foundational research & practical GenAI deployments.
✅ PhD in CS/ML
✅ LLMs & diffusion expertise
✅ Top-tier ML pubs
✅ Python/JAX/PyTorch
Apply : https://t.co/paNhfixL8l
Our team at GDM is hiring a Student Researcher (SR) next year 🧠
If you’re a PhD student working on LLMs please apply. I’d love to hear from you.
Please fill out this form: https://t.co/BVBVb5kXhA
Want to know how to optimally scale test-time compute with generative verifiers?
Come to our poster at #COLM2025 🇨🇦.
hmu if you want to chat about LLM reasoning and agents! :)
Poster session 1 (Tuesday Morning 11 AM - 1 PM), Poster number: 24.
Introducing linear scaling of reasoning:
𝐓𝐡𝐞 𝐌𝐚𝐫𝐤𝐨𝐯𝐢𝐚𝐧 𝐓𝐡𝐢𝐧𝐤𝐞𝐫
Reformulate RL so thinking scales 𝐎(𝐧) 𝐜𝐨𝐦𝐩𝐮𝐭𝐞, not O(n^2), with O(1) 𝐦𝐞𝐦𝐨𝐫𝐲, architecture-agnostic.
Train R1-1.5B into a markovian thinker with 96K thought budget, ~2X accuracy 🧵
Want to know how to optimally scale test-time compute with generative verifiers?
Come to our poster at #COLM2025 🇨🇦.
hmu if you want to chat about LLM reasoning and agents! :)
Poster session 1 (Tuesday Morning 11 AM - 1 PM), Poster number: 24.
MTP provides a robust platform to diagnose weaknesses and improve multi-turn capabilities.
Enjoyed working with @BadolaKartikeya@kazemi_sm@BahareFatemi Jon Simon and the rest of the team @GoogleDeepMind .
Details: https://t.co/iSG4HtyBSY
Data & more: https://t.co/2pHMwjyQki
LLMs are great at single-shot problems, but in the era of experience, interactive environments are key 🔑
Introducing * Multi-Turn Puzzles (MTP) * , a new benchmark to test multi-turn reasoning and strategizing
🔗 Paper: https://t.co/iSG4HtyBSY
🫙Data: https://t.co/0bRlKfqp5W
Our analysis shows stronger models don't just guess better. they build coherent plans, ask complex questions, and re-evaluate their own conclusions based on new info.
Weaker models jump to conclusions and ask less or questions. It's simple Q&A vs strategic dialogue.
7/n