8 citations · 25 across the 11 of their papers we have counts for
7 papers · 1 filter
Multimodal Procedural Planning via Dual Text-Image Prompting
Yujie Lu, Pan Lu, Zhiyu Chen +3
Embodied agents have achieved prominent performance in following human instructions to complete tasks. However, the potential of providing instructions informed by texts and images…
Collaborative Generative AI: Integrating GPT-k for Efficient Editing in Text-to-Image Generation
Wanrong Zhu, Xinyi Wang, Yujie Lu +4
The field of text-to-image (T2I) generation has garnered significant attention both within the research community and among everyday users. Despite the advancements of T2I models,…
Visual Chain of Thought: Bridging Logical Gaps with Multimodal Infillings
Daniel Rose, Vaishnavi Himakunthala, Andy Ouyang +7
Recent advances in large language models elicit reasoning in a chain-of-thought that allows models to decompose problems in a human-like fashion. Though this paradigm improves mult…
WikiWhy: Answering and Explaining Cause-and-Effect Questions
Matthew Ho, Aditya Sharma, Justin Chang +4
As large language models (LLMs) grow larger and more sophisticated, assessing their "reasoning" capabilities in natural language grows more challenging. Recent question answering (…
Not All Errors are Equal: Learning Text Generation Metrics using Stratified Error Synthesis
Wenda Xu, Yilin Tuan, Yujie Lu +3
Is it possible to build a general and automatic natural language generation (NLG) evaluation metric? Existing learned metrics either perform unsatisfactorily or are restricted to t…
CLIP also Understands Text: Prompting CLIP for Phrase Understanding
An Yan, Jiacheng Li, Wanrong Zhu +3
Contrastive Language-Image Pretraining (CLIP) efficiently learns visual concepts by pre-training with natural language supervision. CLIP and its visual encoder have been explored o…