@jlambert_

Google DeepMind | Prev: @Waymo, @StanfordAILab, CS PhD @GeorgiaTech, Grad @Stanford

johnwlambert.github.io/
Joined April 2020
  • Tweets130
  • Following144
  • Followers1.8K
34Media
When LLMs are asked open-ended questions, which cultures do their responses best align with? And can we transparently change that default through inference-time prompt-free interventions? Excited to share our new COLM '26 work from Google DeepMind: arxiv.org/abs/2603.23301🧵(1/N)
1
13
2,150
more replies
4. Bias is mostly an elicitation problem, not missing knowledge. Steering with CuE beats explicit prompting on cultural faithfulness and surfaces rarer, long-tail cultural concepts that prompting alone tends to miss.
1
1
76
This work was led by our talented past student researcher @simi_97k , supervised by @lunwang1996 , with Hongbin Liu, Shujian Zhang, Mingqing Chen, and Rajiv Mathews. "Steering LLMs for Culturally Localized Generation" (arxiv.org/abs/2603.23301) COLM 2026

Steering LLMs for Culturally Localized Generation

LLMs are deployed globally, yet produce responses biased towards cultures with abundant training data. Existing cultural localization approaches such as prompting or post-training alignment are...

arxiv.org
3
122
I am hiring a Student researcher at Google DeepMind for Winter/Spring or Summer of 2026! 🛠️ Interested in tool-use and reasoning for LLMs? 🚀 Up-to-date with frontier research? 🔬 Love to understand code & algorithms from first principles? 📚 Currently studying for a BS/MS/PhD?
33
81
2
1,180
90,939
If so, we want to hear from you! To apply, please follow these two steps: 1️⃣ Fill out the form below to personally express your interest to me: docs.google.com/forms/d/e/1F… 2️⃣ Fill out the Google DeepMind "Student Researcher 2026" application form: google.com/about/careers/app…
10
2
90
9,885
John Lambert retweeted
Bingyi Kang
@bingyikang14 Nov 2025
After a year of team work, we're thrilled to introduce Depth Anything 3 (DA3)! 🚀 Aiming for human-like spatial perception, DA3 extends monocular depth estimation to any-view scenarios, including single images, multi-view images, and video. In pursuit of minimal modeling, DA3 reveals two key insights: 💎 A plain transformer (e.g., vanilla DINO) is enough. No specialized architecture. ✨ A single depth-ray representation is enough. No complex 3D tasks. Three series of models have been released: the main DA3 series, a monocular metric estimation series, and a monocular depth estimation series. The core team members, aside from me: @HaotongLin, Sili Chen, Jun Hao Liew, @donydchen. 👇(1/n) #DepthAnything3
78
485
81
3,545
516,415
Can a single autonomous driving simulation world model jointly insert, delete, and control the behavior of all agents and traffic lights in a bird's-eye-view scene? For the first time, we show this is possible in SceneDiffuser++, our CVPR '25 paper, w/ 60+ second simulations.🧵
1
2
4
1,263
more replies
We propose a new task, CitySim, where given a city map and an AV software stack, the simulator can simulate the trip from point A -> B by populating the city around the AV and controlling all aspects of the scene (e.g., vehicles, pedestrians, traffic light states).
1
1
558
Thanks to the team: @maxjiang93 , @stan188249301 , @tanmingxing, @AnguelovDrago, @hongjjeonS, Sakshum Kulshrestha, Yijing Bai, Jing Luo. - SceneDiffuser++ Paper: arxiv.org/abs/2506.21976 - Watch our video: youtube.com/watch?v=J70R3wxP… - SceneDiffuser Paper: arxiv.org/abs/2412.12129
402
Our Gemini 2.5 tech report ✨ is finally out on arXiv -- grateful for the collaboration with brilliant colleagues! arxiv.org/pdf/2507.06261
6
664
Load more