2 citations · 4 across the 8 of their papers we have counts for
8 papers
Test-Time Optimization of Physical Query Plans with LLMs
Mehmet Hamza Erol, Xiangpeng Hao, Federico Bianchi +3
Traditional query optimization relies on cost-based optimizers that estimate execution cost (e.g., runtime, memory, and I/O) using predefined heuristics and statistical models. Imp…
Exploring Human-AI Conceptual Alignment through the Prism of Chess
Semyon Lomasov, Judah Goldfeder, Mehmet Hamza Erol +5
Do AI systems truly understand human concepts or merely mimic surface patterns? We investigate this through chess, where human creativity meets precise strategic concepts. Analyzin…
Cost-of-Pass: An Economic Framework for Evaluating Language Models
Mehmet Hamza Erol, Batu El, Mirac Suzgun +2
Widespread adoption of AI systems hinges on their ability to generate economic value that outweighs their inference costs. Evaluating this tradeoff requires metrics accounting for…
ElasticAST: An Audio Spectrogram Transformer for All Length and Resolutions
Jiu Feng, Mehmet Hamza Erol, Joon Son Chung +1
Transformers have rapidly overtaken CNN-based architectures as the new standard in audio classification. Transformer-based models, such as the Audio Spectrogram Transformers (AST),…
Audio Mamba: Bidirectional State Space Model for Audio Representation Learning
Mehmet Hamza Erol, Arda Senocak, Jiu Feng +1
Transformers have rapidly become the preferred choice for audio classification, surpassing methods based on CNNs. However, Audio Spectrogram Transformers (ASTs) exhibit quadratic s…
From Coarse to Fine: Efficient Training for Audio Spectrogram Transformers
Jiu Feng, Mehmet Hamza Erol, Joon Son Chung +1
Transformers have become central to recent advances in audio classification. However, training an audio spectrogram transformer, e.g. AST, from scratch can be resource and time-int…
FlexiAST: Flexibility is What AST Needs
Jiu Feng, Mehmet Hamza Erol, Joon Son Chung +1
The objective of this work is to give patch-size flexibility to Audio Spectrogram Transformers (AST). Recent advancements in ASTs have shown superior performance in various audio-b…
RLens: A Computer-aided Visualization System for Supporting Reflection on Language Learning under Distributed Tutorship
Meng Xia, Yankun Zhao, Jihyeong Hong +3
With the rise of the gig economy, online language tutoring platforms are becoming increasingly popular. These platforms provide temporary and flexible jobs for native speakers as t…