Huan Wang is a Research Director at Salesforce Research. He works on various topics including deep learning theory, reinforcement learning, time series analytics, operational and data intelligence.
As codebases grow to millions of lines of code, can AI agents still understand, reason, and code effectively? LoCoBench-Agent delivers the answer: a comprehensive benchmark for evaluating AI coding assistants across contexts ranging…
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…
Our team at Salesforce Research introduces Text2Data, an innovative framework specifically designed to generate high-quality, controllable data from limited textual input.
We've introduced xLAM, our family of in-house Large Action Models, designed for function calling, reasoning, and planning. These models are designed to streamline and simplify the integration of AI into your workflows, reducing the complexity often associated with LLMs.
Huan Wang, Shelby Heinecke, Juan Carlos Niebles, Caiming Xiong TL;DR: We release xLAM, a series of LLMs optimized for function calling and AI Agents. It offers several variants designed to serve different application…
