3 citations · 3 across the 5 of their papers we have counts for
6 papers
T-LLM Compiler: Trusted LLM-based Code Optimization and Verification Framework
Zahra Fazel, Sunanda Gamage, Shayan Shirahmad Gale Bagi +5
Recent advances in Large Language Models (LLMs) have opened opportunities to apply high-level code transformations to the field of code optimization, and it has since emerged as on…
Protean Compiler: An Agile Framework to Drive Fine-grain Phase Ordering
Amir H. Ashouri, Shayan Shirahmad Gale Bagi, Kavin Satheeskumar +6
The phase ordering problem has been a long-standing challenge since the late 1970s, yet it remains an open problem due to having a vast optimization space and an unbounded nature,…
PerfCoder: Large Language Models for Interpretable Code Performance Optimization
Jiuding Yang, Shengyao Lu, Hongxuan Liu +4
Large language models (LLMs) have achieved remarkable progress in automatic code generation, yet their ability to produce high-performance code remains limited--a critical requirem…
Implicit Causal Representation Learning via Switchable Mechanisms
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte +1
Learning causal representations from observational and interventional data in the absence of known ground-truth graph structures necessitates implicit latent causal representation…
Generative Causal Representation Learning for Out-of-Distribution Motion Forecasting
Shayan Shirahmad Gale Bagi, Zahra Gharaee, Oliver Schulte +1
Conventional supervised learning methods typically assume i.i.d samples and are found to be sensitive to out-of-distribution (OOD) data. We propose Generative Causal Representation…
Deep Representation of Imbalanced Spatio-temporal Traffic Flow Data for Traffic Accident Detection
Pouya Mehrannia, Shayan Shirahmad Gale Bagi, Behzad Moshiri +1
Automatic detection of traffic accidents has a crucial effect on improving transportation, public safety, and path planning. Many lives can be saved by the consequent decrease in t…