8 citations · 13 across the 13 of their papers we have counts for
5 papers · 1 filter
STISA: A 0.16 GOPS/W/PE Single-Shot Inference FPGA-based SNN Accelerator with Algorithm and Hardware Co-Design
Kainan Wang, Chengyi Yang, Lei Liu +4
Spiking neural networks (SNNs) offer great potential for low-power intelligent computing owing to their event-driven nature, yet their deployment is limited by high inference laten…
Benchmarking 3D Reconstruction for Under-Ice Robotic Perception in Arctic Environments
Klára Orbán, Ashwin Nedungadi, Ana-Ştefania Kogălniceanu +5
As the Arctic transitions toward a seasonally ice-free state, capturing the complex morphology of submerged sea ice is crucial for advancing models of ocean-ice-atmosphere heat exc…
Autoregressive Mosaics: Probing 2D Spatial Reasoning in Text-Only Language Models
Ashwin Nedungadi, Stefan Oehmcke, Stefan Lüdtke
Large language models (LLMs) trained only on text and code can sometimes generate programs that draw recognizable images. However, it is unclear whether this reflects an internal r…
Lost in Aggregation: How Benchmarks Overlook Irreplaceable Model Strengths
Andrej Tschalzev, Stefan Lüdtke, Heiner Stuckenschmidt +1
Tabular machine learning benchmarks typically summarize performance by averaging scores, ranks, or pairwise wins across datasets. Such aggregates are useful for selecting robust de…
TabPrep: Closing the Feature Engineering Gap in Tabular Benchmarks
Andrej Tschalzev, Nick Erickson, Yuyang Wang +4
Progress in tabular machine learning has largely focused on increasingly sophisticated model architectures. At the same time, feature engineering remains a critical yet underexplor…