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layout: page | ||
title: home | ||
permalink: / | ||
title: <h3>Workshop on Instruction Tuning and Instruction Following</h3> | ||
title: <h3 align="center">Workshop on Instruction Tuning and Instruction Following</h3> | ||
nav_order: 1 | ||
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__@ NeurIPS 2023, Dec 15 or 16__ | ||
__New Orleans, Louisiana, United States__ | ||
<h2 align="center">Workshop on Instruction Tuning and Instruction Following</h2><br> | ||
<p align="center"> | ||
@ NeurIPS 2023, Dec 15 or 16<br> | ||
New Orleans, Louisiana, United States<br><br> | ||
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Quick Links: | ||
<a href="/">Twitter</a> | <a href="/call">Call for Papers</a> | <a href="https://openreview.net/group?id=NeurIPS.cc/2023/Workshop/Instruction">OpenReview Portal</a> <br> | ||
Program: | ||
<a href="#speakers">Speakers</a> | <a href="#panelists">Panelists</a> | <a href="/organization">Organization</a> | <a href="/schedule">Schedule</a><br><br> | ||
Contact Us: <a href="mailto:[email protected]">[email protected]</a> | ||
</p> | ||
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<br> | ||
Recent advancements in training large language models (LLMs) to follow "instructions" have significantly increased their ability to comprehend open-ended language commands, encompassing a wide range of needs, preferences, and values. | ||
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This remarkable transformation has led to the creation of phenomenal industrial models such as [GPT-4](https://arxiv.org/abs/2303.08774) and [Bard](https://blog.google/technology/ai/bard-google-ai-search-updates/), as well as an increased focus within the open-source and research communities: creating new benchmark and resources [[1](https://aclanthology.org/2022.emnlp-main.340/),[2](https://arxiv.org/abs/2301.13688)], developing new training methods [[3](https://arxiv.org/abs/2203.02155),[4](https://arxiv.org/abs/2212.10560)], and understanding the limitations of these methods [[5](https://arxiv.org/abs/2109.01247)]. Furthermore, instruction following powered by LLMs has proven to be effective in multi-modal settings, with applications in image editing [[6](https://arxiv.org/abs/2211.09800)] and robotic command execution [[7](https://arxiv.org/abs/2204.01691)]. | ||
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* [Nazneen Rajani](https://www.nazneenrajani.com/), Hugging Face | ||
* [Omer Levy](https://www.cs.tau.ac.il/~levyomer/), Tel Aviv University, Meta AI | ||
* [Sara Hooker](https://www.sarahooker.me/), Cohere for AI | ||
* [Fei Xia](https://fxia22.github.io/), Google Deepmind | ||
* [Fei Xia](https://fxia22.github.io/), Google DeepMind | ||
* [Tatsunori Hashimoto](https://thashim.github.io/), Stanford University | ||
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<br> | ||
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## Panelists | ||
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Stay tuned! We plan to have two panels to encourage discussion! | ||
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<br> | ||
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## Organizers | ||
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* [Qinyuan Ye](http://yeqy.xyz/), University of Southern California | ||
* [Yizhong Wang](https://homes.cs.washington.edu/~yizhongw/), University of Washington | ||
* [Shayne Longpre](https://www.shaynelongpre.com/), Massachusetts Institute of Technology | ||
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<br> | ||
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## Contact Us | ||
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Email: [[email protected]](mailto:[email protected]) | ||
## Steering Committee | ||
* [Hannaneh Hajishirzi](https://homes.cs.washington.edu/~hannaneh/), University of Washington, Allen Institute for AI | ||
* [Xiang Ren](https://shanzhenren.github.io/), University of Southern California, Allen Institute for AI | ||
* [Robin Jia](https://robinjia.github.io/), University of Southern California |
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