LLM-Aided Testbench Generation and Bug Detection for Finite-State Machines J Bhandari, J Knechtel, R Narayanaswamy, S Garg, R Karri arXiv preprint arXiv:2406.17132, 2024 | | 2024 |
C2HLSC: Can LLMs Bridge the Software-to-Hardware Design Gap? L Collini, S Garg, R Karri arXiv preprint arXiv:2406.09233, 2024 | | 2024 |
NYU CTF Dataset: A Scalable Open-Source Benchmark Dataset for Evaluating LLMs in Offensive Security M Shao, S Jancheska, M Udeshi, B Dolan-Gavitt, H Xi, K Milner, B Chen, ... arXiv preprint arXiv:2406.05590, 2024 | | 2024 |
Split Computing With Scalable Feature Compression for Visual Analytics on the Edge Z Yuan, S Rawlekar, S Garg, E Erkip, Y Wang IEEE Transactions on Multimedia, 2024 | | 2024 |
Model Cascading for Code: Reducing Inference Costs with Model Cascading for LLM Based Code Generation B Chen, M Zhu, B Dolan-Gavitt, M Shafique, S Garg arXiv preprint arXiv:2405.15842, 2024 | | 2024 |
Learning-Based Compress-and-Forward Schemes for the Relay Channel E Ozyilkan, F Carpi, S Garg, E Erkip arXiv preprint arXiv:2405.09534, 2024 | | 2024 |
Learned Pulse Shaping Design for PAPR Reduction in DFT-s-OFDM F Carpi, S Rostami, J Cho, S Garg, E Erkip, CJ Zhang arXiv preprint arXiv:2404.16137, 2024 | | 2024 |
Evaluating LLMs for Hardware Design and Test J Blocklove, S Garg, R Karri, H Pearce arXiv preprint arXiv:2405.02326, 2024 | | 2024 |
Neural Compress-and-Forward for the Relay Channel E Ozyilkan, F Carpi, S Garg, E Erkip arXiv preprint arXiv:2404.14594, 2024 | | 2024 |
On the (In) feasibility of ML Backdoor Detection as an Hypothesis Testing Problem G Pichler, M Romanelli, DP Manivannan, P Krishnamurthy, S Garg International Conference on Artificial Intelligence and Statistics, 4051-4059, 2024 | | 2024 |
An empirical evaluation of llms for solving offensive security challenges M Shao, B Chen, S Jancheska, B Dolan-Gavitt, S Garg, R Karri, ... arXiv preprint arXiv:2402.11814, 2024 | 5 | 2024 |
Exploiting connections between Lipschitz structures for certifiably robust deep equilibrium models A Havens, A Araujo, S Garg, F Khorrami, B Hu Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
Make every move count: Llm-based high-quality rtl code generation using mcts M DeLorenzo, AB Chowdhury, V Gohil, S Thakur, R Karri, S Garg, ... arXiv preprint arXiv:2402.03289, 2024 | 8 | 2024 |
Novel quadratic constraints for extending lipsdp beyond slope-restricted activations P Pauli, A Havens, A Araujo, S Garg, F Khorrami, F Allgöwer, B Hu arXiv preprint arXiv:2401.14033, 2024 | 4 | 2024 |
Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization AB Chowdhury, M Romanelli, B Tan, R Karri, S Garg arXiv preprint arXiv:2401.12205, 2024 | | 2024 |
Retrieval-Guided Reinforcement Learning for Boolean Circuit Minimization A Basak Chowdhury, M Romanelli, B Tan, R Karri, S Garg arXiv e-prints, arXiv: 2401.12205, 2024 | | 2024 |
Manipulation attacks on learned image compression K Liu, D Wu, Y Wu, Y Wang, D Feng, B Tan, S Garg IEEE Transactions on Artificial Intelligence, 2023 | 3 | 2023 |
Autochip: Automating hdl generation using llm feedback S Thakur, J Blocklove, H Pearce, B Tan, S Garg, R Karri arXiv preprint arXiv:2311.04887, 2023 | 18 | 2023 |
Towards the Imagenets of ML4EDA AB Chowdhury, S Thakur, H Pearce, R Karri, S Garg 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 1-7, 2023 | | 2023 |
LipSim: A Provably Robust Perceptual Similarity Metric S Ghazanfari, A Araujo, P Krishnamurthy, F Khorrami, S Garg arXiv preprint arXiv:2310.18274, 2023 | 1 | 2023 |