..  _publications:

Publications Using Scenic
=========================

Main Papers
-----------

The main paper on Scenic, describing the language (as of version 2) and its applications is:

	| :t:`Scenic: A Language for Scenario Specification and Data Generation`.
	| Fremont, Kim, Dreossi, Ghosh, Yue, Sangiovanni-Vincentelli, and Seshia.
	| *Machine Learning*, 2022. [`available here <https://doi.org/10.1007/s10994-021-06120-5>`_]
	| (see also the `full version with appendices <https://arxiv.org/abs/2010.06580>`_)

For the new features in Scenic 3, see the paper:

	| :t:`3D Environment Modeling for Falsification and Beyond with Scenic 3.0`.
	| Vin, Kashiwa, Rhea, Fremont, Kim, Dreossi, Ghosh, Yue, Sangiovanni-Vincentelli, and Seshia.
	| CAV 2023. [`arXiv version <https://arxiv.org/abs/2307.03325>`_]

Our main 2022 journal paper extends the earlier conference paper on Scenic 1.0:

	| :t:`Scenic: A Language for Scenario Specification and Scene Generation`.
	| Fremont, Dreossi, Ghosh, Yue, Sangiovanni-Vincentelli, and Seshia.
	| PLDI 2019. [`full version <https://arxiv.org/abs/1809.09310>`_]

An expanded version of that paper appeared as Chapters 5 and 8 of this thesis:

	| :t:`Algorithmic Improvisation`. [`thesis <https://people.ucsc.edu/~dfremont/papers/thesis.pdf>`__]
	| Daniel J. Fremont.
	| Ph.D. dissertation, 2019 (University of California, Berkeley; Group in Logic and the Methodology of Science).

Scenic is also integrated into the `VerifAI toolkit <https://github.com/BerkeleyLearnVerify/VerifAI>`_, which is described in another paper:

	| :t:`VerifAI: A Toolkit for the Formal Design and Analysis of Artificial Intelligence-Based Systems`.
	| Dreossi*, Fremont*, Ghosh*, Kim, Ravanbakhsh, Vazquez-Chanlatte, and Seshia.
	| `CAV 2019 <https://doi.org/10.1007/978-3-030-25540-4_25>`_.

\* Equal contribution.


Case Studies
------------

We have also used Scenic in several industrial case studies:

	| :t:`Addressing the IEEE AV Test Challenge with Scenic and VerifAI`.
	| Viswanadha, Indaheng, Wong, Kim, Kalvan, Pant, Fremont, and Seshia.
	| `AITest 2021 <https://doi.org/10.1109/AITEST52744.2021.00034>`_.

	| :t:`Formal Analysis and Redesign of a Neural Network-Based Aircraft Taxiing System with VerifAI`.
	| Fremont, Chiu, Margineantu, Osipychev, and Seshia.
	| `CAV 2020 <https://people.eecs.berkeley.edu/~sseshia/pubs/b2hd-fremont-cav20.html>`_.

	.. _ITSC2020:

	| :t:`Formal Scenario-Based Testing of Autonomous Vehicles: From Simulation to the Real World`.
	| Fremont, Kim, Pant, Seshia, Acharya, Bruso, Wells, Lemke, Lu, and Mehta.
	| `ITSC 2020 <https://people.eecs.berkeley.edu/~sseshia/pubs/b2hd-fremont-itsc20.html>`_.
	| [See also `this white paper <https://gomentumstation.net/wp-content/uploads/2020/03/AAA-UCB-LG-AV-Testing-Project-Whitepaper-Final-2020-7-15.pdf>`_ and `associated blog post <https://gomentumstation.net/blog-2020-03-26/>`_]


Other Papers Building on Scenic
-------------------------------

	| :t:`Querying Labelled Data with Scenario Programs for Sim-to-Real Validation`.
	| Kim, Shenoy, Junges, Fremont, Sangiovanni-Vincentelli, and Seshia.
	| `ICCPS 2022 <https://doi.org/10.1109/ICCPS54341.2022.00010>`_.

	| :t:`Parallel and Multi-objective Falsification with Scenic and VerifAI`.
	| Viswanadha, Kim, Indaheng, Fremont, and Seshia.
	| `RV 2021 <https://doi.org/10.1007/978-3-030-88494-9_15>`_.

	| :t:`A Programmatic and Semantic Approach to Explaining and Debugging Neural Network Based Object Detectors`.
	| Kim, Gopinath, Pasareanu, and Seshia.
	| `CVPR 2020 <https://people.eecs.berkeley.edu/~sseshia/pubs/b2hd-kim-cvpr20.html>`_.