no code implementations • 10 Oct 2023 • Siddhant Agarwal, Ishan Durugkar, Peter Stone, Amy Zhang
We further introduce an entropy-regularized policy optimization objective, that we call $state$-MaxEnt RL (or $s$-MaxEnt RL) as a special case of our objective.
1 code implementation • 1 Dec 2022 • Shivam Sharma, Siddhant Agarwal, Tharun Suresh, Preslav Nakov, Md. Shad Akhtar, Tanmoy Chakraborty
Here, we introduce a novel task - EXCLAIM, generating explanations for visual semantic role labeling in memes.
no code implementations • 26 Nov 2021 • Siddhant Agarwal, Owais Iqbal, Sree Aditya Buridi, Madda Manjusha, Abir Das
Black-box methods to generate saliency maps are particularly interesting due to the fact that they do not utilize the internals of the model to explain the decision.
no code implementations • 23 Aug 2021 • Siddhant Agarwal, Nicola Tosi, Pan Kessel, Doris Breuer, Grégoire Montavon
Using a dataset of 10, 525 two-dimensional simulations of the thermal evolution of the mantle of a Mars-like planet, we show that deep learning techniques can produce reliable parameterized surrogates (i. e. surrogates that predict state variables such as temperature based only on parameters) of the underlying partial differential equations.
1 code implementation • ICLR 2021 • Mrigank Raman, Aaron Chan, Siddhant Agarwal, Peifeng Wang, Hansen Wang, Sungchul Kim, Ryan Rossi, Handong Zhao, Nedim Lipka, Xiang Ren
Knowledge graphs (KGs) have helped neural models improve performance on various knowledge-intensive tasks, like question answering and item recommendation.
1 code implementation • 18 Oct 2020 • MingJie Sun, Siddhant Agarwal, J. Zico Kolter
Under this threat model, we propose a test-time, human-in-the-loop attack method to generate multiple effective alternative triggers without access to the initial backdoor and the training data.