5 papers
QUASAR: Lowering the Loss Floor of Quantization-Aware Training with Loss-Aware Reconstruction
Vincent Counathe, Ben Athiwaratkun, Christopher De Sa +1
As large language model inference shifts toward lower precision, post-training quantization (PTQ) becomes increasingly brittle, making quantization-aware training (QAT) essential f…
BOCCHI: A More Realistic and Challenging Benchmark for Local Motion Blur Detection with MSDCT-UNet
Kuan-Lin Chen, Yuan-Kang Lee, Cheng-Yuan Chiang +1
Local motion blur detection requires pixel-level localization of blurred regions. Existing benchmarks let models rely on gradient shortcuts that fail to transfer. We introduce BOCC…
RL-AWB: Deep Reinforcement Learning for Auto White Balance Correction in Low-Light Night-time Scenes
Yuan-Kang Lee, Kuan-Lin Chen, Chia-Che Chang +1
Nighttime color constancy still remains a challenging problem in computational photography due to low-light noise and complex illumination conditions. We present RL-AWB, a novel fr…
AnchorSteer: Self-Discovered Concept Injection for Structure-Preserving Music Editing
Chih-Heng Chang, Keng-Seng Ho, Chih-Yu Tsai +3
Controllable music editing is to modify high-level attributes while strictly preserving rhythmic and melodic structures. However, this task is challenged by a semantic-structural e…
Guitar Tone Morphing by Diffusion-based Model
Kuan-Yu Chen, Kuan-Lin Chen, Yu-Chieh Yu +1
In Music Information Retrieval (MIR), modeling and transforming the tone of musical instruments, particularly electric guitars, has gained increasing attention due to the richness…