4 papers
Language-Image Alignment with Fixed Text Encoders
Jingfeng Yang, Ziyang Wu, Yue Zhao +1
Currently, the most dominant approach to establishing language-image alignment is to pre-train text and image encoders jointly through contrastive learning, such as CLIP and its va…
Thinking Preference Optimization
Wang Yang, Hongye Jin, Jingfeng Yang +2
Supervised Fine-Tuning (SFT) has been a go-to and effective method for enhancing long chain-of-thought (CoT) reasoning in relatively small LLMs by fine-tuning them with long CoT re…
LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning
Hongye Jin, Xiaotian Han, Jingfeng Yang +5
It is well known that LLMs cannot generalize well to long contexts whose lengths are larger than the training sequence length. This poses challenges when employing LLMs for process…
Segment Anything without Supervision
XuDong Wang, Jingfeng Yang, Trevor Darrell
The Segmentation Anything Model (SAM) requires labor-intensive data labeling. We present Unsupervised SAM (UnSAM) for promptable and automatic whole-image segmentation that does no…