4 papers · 1 filter
Task Vector Geometry Underlies Dual Modes of Task Inference in Transformers
Hao Yan, Haolin Yang, Yiqiao Zhong
Transformers are effective at inferring the latent task from context via two inference modes: recognizing a task seen during training, and adapting to a novel one. Recent interpret…
CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection
Xinlin Zhuang, Yichen Li, Xiwei Liu +11
Adapting CLIP to vertical domains is typically approached by novel fine-tuning strategies or by continual pre-training (CPT) on large domain-specific datasets. Yet, data itself rem…
scAGC: Learning Adaptive Cell Graphs with Contrastive Guidance for Single-Cell Clustering
Huifa Li, Jie Fu, Xinlin Zhuang +6
Accurate cell type annotation is a crucial step in analyzing single-cell RNA sequencing (scRNA-seq) data, which provides valuable insights into cellular heterogeneity. However, due…
ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos
Haolin Yang, Feilong Tang, Ming Hu +8
Video diffusion models (VDMs) facilitate the generation of high-quality videos, with current research predominantly concentrated on scaling efforts during training through improvem…