From the 1 of 30 linked papers with an AI index.
54 citations · 56 across the 3 of their papers we have counts for
30 papers
Commit Locally, Exit Globally: Coordinating Adaptive Sampling and Early Exit in Diffusion Language Models
Chia-Ming Lee, Ming-Ching Chang, Shao-Kai Liu +3
The paper introduces LATCH, a training‑free, candidate‑aware early‑exit framework for diffusion language models that decides when to stop generation and where to accelerate decodin…
NTIRE 2025 Challenge on Image Super-Resolution (x4): Methods and Results
Zheng Chen, Kai Liu, Jue Gong +108
This paper presents the NTIRE 2025 image super-resolution (4) challenge, one of the associated competitions of the 10th NTIRE Workshop at CVPR 2025. The challenge aims to r…
NTIRE 2024 Challenge on Image Super-Resolution (x4): Methods and Results
Zheng Chen, Zongwei Wu, Eduard Zamfir +85
This paper reviews the NTIRE 2024 challenge on image super-resolution (4), highlighting the solutions proposed and the outcomes obtained. The challenge involves generating…
VISTA: Validation-Guided Integration of Spatial and Temporal Foundation Models with Anatomical Decoding for Rare-Pathology VCE Event Detection -- after competition results
Bo-Cheng Qiu, Fang-Ying Lin, Ming-Han Sun +3
Capsule endoscopy event detection is challenging because clinically relevant findings are sparse, visually heterogeneous, and evaluated at the event level rather than by frame accu…
Cross-modal Affinity-aligned Multimodal Learning Analytics for Predicting Student Collaboration Satisfaction in Game-Based Learning
Wen-Hsin Tsai, Chia-Ming Lee, Yuk-Ying Tung
Collaborative game-based learning environments offer rich opportunities for small-group knowledge construction, yet automatically predicting student collaboration satisfaction rema…
Robust Deepfake Detection, NTIRE 2026 Challenge: Report
Benedikt Hopf, Radu Timofte, Chenfan Qu +54
Robustness is a long-overlooked problem in deepfake detection. However, detection performance is nearly worthless in the real world if it suffers under exposure to even slight imag…