Excited to share what we’ve been building at Meta Superintelligence Labs!
Today we’re launching Muse Spark 1.1, our strongest model yet for complex agentic workflows — delivering massive gains in agents, computer use, coding, multimodal reasoning, and multi-agent orchestration.
This is also our first API release! We’d love to hear your feedback.
And we’re just getting started, super proud of the team behind it, and the larger models are training right now. 🚀
https://t.co/GBoZgv2aA2
Very honored to receive the best short paper award at #SIGIR2023! Will present the work at 12 in room 201E today.
"SparseEmbed: Learning Sparse Lexical Representations with Contextual Embeddings for Retrieval" w/ Jeffrey M. Dudek, Cheng Li, @_Mingyang_Zhang@bemikelive
3.1 "Job Type Extraction for Service Businesses" https://t.co/ZiVvWue96W by @Li_Cheng_, Y. Qi, H. Zakarian, @bemikelive, Y. Wu and @marc_najork describes a large-scale pipeline for high-precision automatic extraction of job types from websites of business owners.
Our paper "Out-of-Domain Semantics to the Rescue! Zero-Shot Hybrid Retrieval Models" (by @tao_chen@_Mingyang_Zhang Jing Lu @bemikelive@marc_najork; To appear in ECIR, 2022) is now on arXiv: https://t.co/fV3g7cByiW
I'll be presenting our paper "Dynamic Language Models for Continuously Evolving Content" at #KDD2021 in the ADS Track (Session-10: Web Mining) on August 16th 10.30 AM PT/August 17th 1.30 AM SGT. This is a joint work with @tao_chen, @_Mingyang_Zhang, @bemikelive, and @marc_najork.
The paper will be presented during @sigir2019 by @bemikelive. Innovative technology with practical applications. Please come and enjoy the talk with us.