As organizations increasingly rely on diverse data sources like invoices and surveys,
efficient Information Extraction (IE) is crucial. Natural Language Processing (NLP) enhances …

In the fast-paced realm of digital transformation, businesses are increasingly pressured to
innovate and boost efficiency to remain competitive and foster growth. Large Language …

We provide a sober look at the application of Multimodal Large Language Models (MLLMs)
in autonomous driving, challenging common assumptions about their ability to interpret …

Large-scale data is crucial for learning realistic and capable driving policies. However, it can
be impractical to rely on scaling datasets with real data alone. The majority of driving data is …

The generation of corner cases has become increasingly crucial for efficiently testing
autonomous vehicles prior to road deployment. However, existing methods struggle to …

Simulation is an indispensable tool in the development and testing of autonomous vehicles
(AVs), offering an efficient and safe alternative to road testing. An outstanding challenge with …

Text-to-scene generation, transforming textual descriptions into detailed scenes, typically
relies on generating key scenarios along predetermined paths, constraining environmental …

In this paper, we introduce SynthAI, a new method for the automated creation of High-Level
Synthesis (HLS) designs. SynthAI integrates ReAct agents, Chain-of-Thought (CoT) …

Generating realistic and interactive dynamics of traffic participants according to specific
instruction is critical for street scene simulation. However, there is currently a lack of a …

Autonomous driving evaluation requires simulation environments that closely replicate
actual road conditions, including real-world sensory data and responsive feedback loops …