🚀 Our team at ServiceNow ServiceNow Research is gonna present our paper at #ICLR2025: BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks 📍 Thursday, April 24 | 10 a.m.–12:30 p.m. 📍 Hall 3 + Hall 2B, Poster #280 🔗 bigdocs.github.io

I am excited to open-source PipelineRL - a scalable async RL implementation with in-flight weight updates. Why wait until your bored GPUs finish all sequences? Just update the weights and continue inference! Code: github.com/ServiceNow/Pip… Blog: huggingface.co/blog/ServiceNo…

⚠️We’re looking for emergency reviewers for the REALM workshop @ ACL 2025 (realm-workshop.github.io) If you work on LLM agents & can review 1–3 papers, we’d love your help! Sign up here: forms.gle/Mah45swKGNrUY5…

Incredibly proud of my students Ada Tur and Gaurav Kamath for winning a SAC award at #NAACL2025 for their work on assessing how LLMs model constituent shifts. Humans have a tendency to move heavier constituents towards the end of the sentence. While LLMs unsurprisingly show

Congratulations to Mila members Ada Tur, Gaurav Kamath and Siva Reddy for their SAC award at #NAACL2025! Check out Ada's talk in Session I: Oral/Poster 6. Paper: arxiv.org/abs/2502.05670

🚨🤯 Today Jensen Huang announced SLAM Lab's newest model on the ServiceNow Events stage: Apriel‑Nemotron‑15B‑Thinker 🚨 A lean, mean reasoning machine punching way above its weight class 👊 Built by SLAM × NVIDIA. Smaller models, bigger impact. 🧵👇

🚀 Important Update! We're reaching out to collect email IDs of the CulturalVQA and GlobalRG challenge participants for time-sensitive communications, including informing the winning teams. ALL participating teams please fill out the forms below ASAP (ideally within 24 hours). 👇

🚀 Excited to share that UI-Vision has been accepted at ICML 2025! 🎉 We have also released the UI-Vision grounding datasets. Test your agents on it now! 🚀 🤗 Dataset: huggingface.co/datasets/Servi… #ICML2025 #AI #DatasetRelease #Agents

Our team has released the UI-Vision benchmark (accepted at #ICML2025) for testing GUI agent visual grounding and action prediction! 🚀🚀🚀 🤗 Dataset: huggingface.co/datasets/Servi… Special thanks to the students to lead this effort, P Shravan Nayak and Xiangru (Edward) Jian ServiceNow Research

Congrats Tianbao Xie and team on this exciting work and release! 🎉 We’re happy to share that Jedi-7B performs on par with UI-Tars-72B agent on our challenging UI-Vision benchmark, with 10x fewer parameters! 👏 Incredible 🤗Dataset: huggingface.co/datasets/Servi… 🌐uivision.github.io

Very excited to release StarFlow: a large diverse workflow dataset and open models that can transform sketches into executable workflows using VLMs. Stay tuned for more updates on this space!

Rendering-Aware Reinforcement Learning for Vector Graphics Generation RLRF significantly outperforms supervised fine-tuning, addressing common failure modes and enabling precise, high-quality SVG generation with strong structural understanding and generalization

Thanks AK for sharing our work! Excited to present our next generation of SVG models, now using Reinforcement Learning from Rendering Feedback (RLRF). 🧠 We think we cracked SVG generalization with this one. Go read the paper! arxiv.org/abs/2505.20793 More details on

Are you new to ML, or first-time author attending ICML 📢 Submit to New in ML @ ICML 2025! ✅ Feedback from top researchers ✅ Oral presentations + awards ✅ Limited ICML 2025 tickets! newinml.github.io

If you are at #CVPR25 come join us at our workshop in room 104E for exciting line up of talks, posters, and a panel! And some cool merch!!

A Hindu wedding without a sacred fire? A Chinese banquet with forks? Do text-to-image models meet cultural expectations, both explicitly stated and implicitly assumed? Excited to share our latest paper on evaluating cultural alignment in T2I models 🌐 culturalframes.github.io

The IVADO #Bootcamp marked the launch of the Thematic Semester on Autonomous #LLM Agents last week at Université de Montréal. Over 4 days, researchers, experts, and #AI enthusiasts gathered for conferences, tutorials, and rich discussions, laying the groundwork for our next two workshops.

🔥 We stress-tested today’s best AI code generators in 𝑑𝑒𝑝𝑒𝑛𝑑𝑒𝑛𝑐𝑦 ℎ𝑒𝑙𝑙. Introducing 𝐆𝐢𝐭𝐂𝐡𝐚𝐦𝐞𝐥𝐞𝐨𝐧 𝟐.𝟎: 328 challenges for version-controlled code generation. The verdict? Even top models only hit ~50% success.

🚨 Is #WorkArena on the verge of being solved? Or did GPT-5 just get trained on it? 🔥While some benchmarks show modest gains, GPT-5 is crushing WorkArena L2🔥 ➡️ 69.4% avg success vs. ~40% for next best🤯 ➡️ Complex tasks, up to 100 steps, 5–20 min for humans

UI-Vision vs GPT-5: Still holding the crown 👑 and far from saturation. GPT-5 has strengths in coding and reasoning, but when it comes to computer-use tasks, it’s still awkward to rely on it alone. And our team's UI-Vision (ICML 2025) remains a key and still unbeaten multimodal