Ran Xu received his Ph.D. in computer science from University at Buffalo from 2015. Currently, he leads a group of exceptional computer vision and multimodal AI researchers at Salesforce to push the boundary of research and productive AI for CRM.
My expertise
Ran Xu's interest is in mutlimodal content understanding and generation, agentic systems.
Large language models (LLMs) have become foundational to AI code understanding and generation, powering a wide range of enterprise AI workflows — from software synthesis to automated reasoning over symbolic sequences. Despite this…
In the world of AI agents that click, scroll, execute and automate — we’re moving fast from “just understand text” to “actually use software for you.” The new benchmark SCUBA tackles exactly that:…
The Challenge with Flows Today Salesforce flows sit at the heart of modern CRM automation, yet authoring them still requires a unique mix of declarative drag‑and‑drop and Apex know‑how. To ease this process,…
Architecture, Training and Dataset Github Code: https://github.com/JiuhaiChen/BLIP3o Models: https://huggingface.co/BLIP3o/BLIP3o-Model Demo: https://huggingface.co/spaces/BLIP3o/blip-3o Motivation OpenAI’s GPT-4o has demonstrated state-of-the-art performance in image understanding, generation and editing tasks. Emerging hypotheses of its architecture suggest a hybrid…
Our team at Salesforce Research introduces Text2Data, an innovative framework specifically designed to generate high-quality, controllable data from limited textual input.
