PhD students in NLP/ML/AI: apply for an in-person summer 2023 internship at Microsoft Semantic Machines! Intelligent agents helping humans, via grounded natural language dialogue and more. Read more at aka.ms/smjobs . #NLProc #ML #AI

New Columbia NLP #EMNLP2022 paper where we leverage the strong few-shot capabilities of LLMs 🤖 & evaluative strength of expert humans 🧑‍💻 to create a benchmark for Figurative Language Understanding with a focus on Explanations (1/n) Paper: arxiv.org/pdf/2205.12404… #NLProc #xAI

Excited to announce a new dataset–– the result of a fun summer with Harsh Jhamtani at Semantic Machines. We present KNUDGE, a dataset of _real_ dialogue trees from The Outer Worlds (The Outer Worlds) with associated biography and quest specifications. nweir127.github.io/assets/papers/…

Natural Language Decomposition and Interpretation of Complex Utterances abs: arxiv.org/abs/2305.08677 paper page: huggingface.co/papers/2305.08…

Chandrayaan-3 Mission: 'India🇮🇳, I reached my destination and you too!' : Chandrayaan-3 Chandrayaan-3 has successfully soft-landed on the moon 🌖!. Congratulations, India🇮🇳! #Chandrayaan_3 #Ch3

"Interpreting User Requests in the Context of Natural Language Standing Instructions" to appear in #NAACL2024 Findings Paper: shorturl.at/hsFVZ Data: huggingface.co/datasets/nikit… Code: github.com/nikitacs16/nlsi Patrick Xia Jacob Andreas Jason Eisner Benjamin Van Durme Harsh Jhamtani

Glad to share my intern work in Microsoft Research. Great gratitude to my mentors Chi Wang , Harsh Jhamtani, Srinagesh Sharma and my PhD advisor Chuchu Fan. 'Steering Large Language Models between Code Execution and Textual Reasoning' 👉 Full paper: arxiv.org/abs/2410.03524

PhD Summer Research Internships on topics in conversational AI at Microsoft jobs.careers.microsoft.com/global/en/shar…

“Ontologically Faithful Generation of Non-Player Character Dialogues” Nathaniel Weir, Ryan Thomas, Randolph d'Amore, Kellie Hill, Benjamin Van Durme, Harsh Jhamtani arxiv.org/abs/2212.10618

“Learning to Retrieve Iteratively for In-Context Learning” Yunmo Chen, Tongfei Chen, Harsh Jhamtani,Patrick Xia, Richard Shin, Jason Eisner, Benjamin Van Durme arxiv.org/abs/2406.14739

How to effectively customise LLMs - x.com/nikita_moghe/s…

I'm at EMNLP! Come by Poster Session B (2pm-3:30pm) if you want to say hi and/or hear about this cool trick for bootstrapping paired language+code data from raw code! Paper 🔗: aclanthology.org/2024.emnlp-mai…

Our paper on 'Learning to Retrieve Iteratively for In-Context Learning' was named as one of the Outstanding Papers at EMNLP 2024!! aclanthology.org/2024.emnlp-mai…

Excited to share our latest work, Learning to Retrieve Iteratively for In-Context Learning, at #EMNLP2024! Here’s how we’re pushing the boundaries of retrieval techniques in large language models (LLMs). 🧵👇

🚀 Excited to share our latest work! 1. Steering Large Language Models between Code Execution and Textual Reasoning (ICLR’25) (arxiv.org/pdf/2410.03524) 2. CodeSteer: Symbolic-Augmented LLMs via Code/Text Guidance (arxiv.org/pdf/2502.04350) 📂 Code: github.com/yongchao98/Cod…

Our work will be presented today at ACL 2025 on Monday, July 28, 18:00-19:30 in Session 5. In this work, we created an environment to benchmark LLM agents on productivity tasks that doesn't just require tools, but also getting information from various people in the organization.

I am growing an R&D team around Copilot Tuning, a newly announced effort that supports adaptation at a customer-specific level. Join us! jobs.careers.microsoft.com/global/en/job/… We collaborate with a crack team of eng and scientists that support the product, also growing! jobs.careers.microsoft.com/global/en/job/…