Mengting Wan
@mengtingwan
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Scientist at @Microsoft #OAR #AppliedResearch | PhD from @ucsd_cse
Seattle, WA
Joined October 2012
We (Microsoft's Office of Applied Research) have a few openings for exceptional Research Engineers / MLEs to train, test, and scale the next-gen enterprise agentic systems to millions of copilot users. Apply today if you are up for the task! https://t.co/bwMXpYzNn0
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Landed in Vienna for #ACL2025! We are hiring FTEs/Postdocs/Interns at Office of Applied Research to push the frontier of continuous model improvement for productivity, through RL*, inference time scaling, self reflection, memory etc. Available to chat this week w/ @mengtingwan.
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🤔 We know what people are using LLMs for, but do we know how they collaborate with an LLM? 🔍 In a recent paper we answered this by analyzing multi-turn sessions in 21 million Microsoft Copilot for consumers and WildChat interaction logs: https://t.co/W1bmrE3Ddt
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🚀 News! Our 2nd Workshop on Long-Context Foundation Models (LCFM), to be held at ICML 2025 in Vancouver 🇨🇦! If you're working on long-context models, consider submitting your work! 🗓️ DDL: May 22, 2025 (AOE) 🌐 Web: https://t.co/5Dt6uBATcN 🔗 OpenReview: https://t.co/FaxTWdeGnr
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@Microsoft @NeurIPSConf @ylongqi @BahaarehS @peizNLP @sharma_ashish_2 @soshsihao @bhecht Also @BahaarehS and I will be around at the Women in ML workshop #WiML this Tuesday afternoon - don't hesitate to reach out if you want to learn more about opportunities to shape the future of GenAI models and experiences for #productivity!
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Many @Microsoft Office of Applied Research #OAR members will attend @NeurIPSConf this week: @ylongqi @BahaarehS @peizNLP @sharma_ashish_2 @soshsihao @bhecht & myself. We are hiring (both spring & summer) research interns, FTEs and postdocs. Please reach out if you're interested!
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Friends and colleagues! I'm on the academic job market in Fall 24/Spring 25. My research intersects NLP, IR, and HCI and I develop interactive and personalized models to aid workflows where knowledge workers find, consume, and produce information. Please help spread the word! 🧵
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See you at @COLM_conf !
Meet @Microsoft Office of Applied Research at @COLM_conf: @peizNLP @mengtingwan @sharma_ashish_2 @soshsihao @MSheshera and myself. We are hiring interns, postdocs, FTEs to shape and redefine the future of GenAI, M365 Copilot and productivity. Please reach out!
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Existing synthetic data like ULTRAFEEDBACK and SELF-INSTRUCT are biased and overlook real user preferences. 🤔 Introducing WILDFEEDBACK: leveraging real-time user feedback to create authentic, scalable, and unbiased preference data that truly aligns with human values! 🚀
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Hola! Glad to share that our TnT-LLM paper (the method for organizing Copilot logs into meaningful user tasks) was accepted to #KDD2024 - I'm in BCN now and will be presenting this work on 8/29 at the GenAI Application session. Feel free to stop by and join us for discussion!
Microsoft researchers are taking a comprehensive and dynamic approach to help Copilot (web) continuously learn from interaction and feedback, improving the AI system and making it increasingly useful. Learn more.
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Besides, working alongside with @tararootcake @ylongqi @ProfJenNeville @scottjcounts @ssuri @bhecht @jteevan and many others has been an extraordinary experience - truly grateful to be part of this journey.
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Addressing biases, privacy, costs, etc, remains crucial, but what I'm most excited about TnT-LLM is the potential to democratize knowledge extraction from unstructured text, and empower non-experts to intuitively interact with large text corpora via natural language. (3/4)
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Our goal is to convert unstructured texts into meaningful labels with minimal human effort. TnT-LLM showcases LLM can be both label taxonomy generator and annotator (facilitate building lightweight classifiers), paving the road for scalable and interpretable text analysis. (2/4)
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Add on this - thrilled to share TnT-LLM, a framework leverages LLMs to automate taxonomy generation and text classification! A gamechanger for us to process massive text datasets like Copilot logs and uncover critical insights at scale. Paper link: https://t.co/m0OODalyLI (1/4)
arxiv.org
Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and application. However,...
Learning from interaction is different from learning from annotations. Today we are excited to share how we are starting to learn from people's interactions to understand and improve Copilot (web) for our consumer customers: https://t.co/XgKQw0V5XO
#Microsoft #Copilot #Bing
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Job Alert! We are hiring full-time senior applied scientist to join Microsoft's Office of Applied Research. Your work will fundamentally impact Microsoft Copilots and contribute to the future of GenAI, LLMs, prompting, and much more. https://t.co/7Wncr4Gdo8
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Excited to be presenting at KDD this week! The paper: https://t.co/2nHf9HMdAk, with @ProfJenNeville , @ylongqi, @mengtingwan, and Cao Lu. tl;dr: we can improve cross-team information flow in a company's communication network by recommending posts in Microsoft Teams
dl.acm.org
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🚨 Internship Alert 🚨 There are some interesting internship opportunities on LLMs sponsored by our group, please apply! https://t.co/QmLicVWKke
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Jing is absolutely a rising star in the causal ML and graph mining field. Check out her profile if your department is hiring!
I'm now on the job market for faculty/postdoc positions starting from Fall 2023! I am broadly interested in machine learning (ML) and data mining, especially in causal inference & ML, graph ML, fairness, trustworthiness, and social good. My work has won KDD'22 Best Paper Award.
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We are hiring **in-person** research interns for summer 2023! If you are PhD students working on Foundation Models, Graphs, ML, Causal Inference, CSS, or HAI, we��d love to hear from you! Apply here:
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