41 citations · 45 across the 5 of their papers we have counts for
6 papers
Iterate on an LLM, Serve on an SLM
Keegan Wang
As frontier LLMs gain more capabilities, the cost to run them also goes up. At the same time, small language models (SLMs) also gain more capabilities but have largely been able to…
TALENT: Target-aware Efficient Tuning for Referring Image Segmentation
Shuo Jin, Siyue Yu, Bingfeng Zhang +3
Referring image segmentation aims to segment specific targets based on a natural text expression. Recently, parameter-efficient tuning (PET) has emerged as a promising paradigm. Ho…
TF-SSD: A Strong Pipeline via Synergic Mask Filter for Training-free Co-salient Object Detection
Zhijin He, Shuo Jin, Siyue Yu +4
Co-salient Object Detection (CoSOD) aims to segment salient objects that consistently appear across a group of related images. Despite the notable progress achieved by recent train…
Temporal Consistency Learning of inter-frames for Video Super-Resolution
Meiqin Liu, Shuo Jin, Chao Yao +2
Video super-resolution (VSR) is a task that aims to reconstruct high-resolution (HR) frames from the low-resolution (LR) reference frame and multiple neighboring frames. The vital…
RefineCap: Concept-Aware Refinement for Image Captioning
Yekun Chai, Shuo Jin, Junliang Xing
Automatically translating images to texts involves image scene understanding and language modeling. In this paper, we propose a novel model, termed RefineCap, that refines the outp…
Neural Text Classification by Jointly Learning to Cluster and Align
Yekun Chai, Haidong Zhang, Shuo Jin
Distributional text clustering delivers semantically informative representations and captures the relevance between each word and semantic clustering centroids. We extend the neura…