Search Results for author: Long Qin

Found 8 papers, 2 papers with code

MM-Diff: High-Fidelity Image Personalization via Multi-Modal Condition Integration

no code implementations22 Mar 2024 Zhichao Wei, Qingkun Su, Long Qin, Weizhi Wang

CLS embeddings are used on the one hand to augment the text embeddings, and on the other hand together with patch embeddings to derive a small number of detail-rich subject embeddings, both of which are efficiently integrated into the diffusion model through the well-designed multimodal cross-attention mechanism.

Image Generation

EffiVED:Efficient Video Editing via Text-instruction Diffusion Models

no code implementations18 Mar 2024 Zhenghao Zhang, Zuozhuo Dai, Long Qin, Weizhi Wang

Large-scale text-to-video models have shown remarkable abilities, but their direct application in video editing remains challenging due to limited available datasets.

Video Editing

How to Evaluate Your Dialogue Models: A Review of Approaches

no code implementations3 Aug 2021 Xinmeng Li, Wansen Wu, Long Qin, Quanjun Yin

Evaluating the quality of a dialogue system is an understudied problem.

Erroneous data generation for Grammatical Error Correction

no code implementations WS 2019 Shuyao Xu, Jiehao Zhang, Jin Chen, Long Qin

It has been demonstrated that the utilization of a monolingual corpus in neural Grammatical Error Correction (GEC) systems can significantly improve the system performance.

Grammatical Error Correction

Combining Subgoal Graphs with Reinforcement Learning to Build a Rational Pathfinder

no code implementations5 Nov 2018 Junjie Zeng, Long Qin, Yue Hu, Cong Hu, Quanjun Yin

The first advantage of the proposed method is that SSG can solve the limitations of sparse reward and local minima trap for RL agents; thus, LSPI can be used to generate paths in complex environments.

Motion Planning Optimal Motion Planning +3

CLUF: a Neural Model for Second Language Acquisition Modeling

no code implementations WS 2018 Shuyao Xu, Jin Chen, Long Qin

Second Language Acquisition Modeling is the task to predict whether a second language learner would respond correctly in future exercises based on their learning history.

Knowledge Tracing Language Acquisition +5

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