From the 1 of 5 linked papers with an AI index.
5 papers
A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports
Jia Yu, Yan Zhu, Yili He +12
The paper presents EndoCLIP, a vision‑language foundation model for colonoscopy that learns from lesion‑level image‑text pairs extracted from routine colonoscopy reports, achieving…
MALLOC: Benchmarking the Memory-aware Long Sequence Compression for Large Sequential Recommendation
Qihang Yu, Kairui Fu, Zhaocheng Du +10
The scaling law, which indicates that model performance improves with increasing dataset and model capacity, has fueled a growing trend in expanding recommendation models in both i…
Robust Polyp Detection and Diagnosis through Compositional Prompt-Guided Diffusion Models
Jia Yu, Yan Zhu, Peiyao Fu +8
Colorectal cancer (CRC) is a significant global health concern, and early detection through screening plays a critical role in reducing mortality. While deep learning models have s…
CHORD: Customizing Hybrid-precision On-device Model for Sequential Recommendation with Device-cloud Collaboration
Tianqi Liu, Kairui Fu, Shengyu Zhang +5
With the advancement of mobile device capabilities, deploying reranking models directly on devices has become feasible, enabling real-time contextual recommendations. When migratin…
More Than Catastrophic Forgetting: Integrating General Capabilities For Domain-Specific LLMs
Chengyuan Liu, Yangyang Kang, Shihang Wang +5
The performance on general tasks decreases after Large Language Models (LLMs) are fine-tuned on domain-specific tasks, the phenomenon is known as Catastrophic Forgetting (CF). Howe…