1 citations · 2 across the 5 of their papers we have counts for
5 papers
InstructAttribute: Fine-grained Object Attributes editing with Instruction
Xingxi Yin, Jingfeng Zhang, Yue Deng +3
Text-to-image (T2I) diffusion models are widely used in image editing due to their powerful generative capabilities. However, achieving fine-grained control over specific object at…
ColorEdit: Training-free Image-Guided Color editing with diffusion model
Xingxi Yin, Zhi Li, Jingfeng Zhang +2
Text-to-image (T2I) diffusion models, with their impressive generative capabilities, have been adopted for image editing tasks, demonstrating remarkable efficacy. However, due to a…
VideoCogQA: A Controllable Benchmark for Evaluating Cognitive Abilities in Video-Language Models
Chenglin Li, Qianglong Chen, Zhi Li +2
Recent advancements in Large Video-Language Models (LVLMs) have led to promising results in multimodal video understanding. However, it remains unclear whether these models possess…
Optimizing Instruction Synthesis: Effective Exploration of Evolutionary Space with Tree Search
Chenglin Li, Qianglong Chen, Zhi Li +5
Instruction tuning is a crucial technique for aligning language models with humans' actual goals in the real world. Extensive research has highlighted the quality of instruction da…
Improving Faithfulness of Large Language Models in Summarization via Sliding Generation and Self-Consistency
Taiji Li, Zhi Li, Yin Zhang
Despite large language models (LLMs) have demonstrated impressive performance in various tasks, they are still suffering from the factual inconsistency problem called hallucination…