Search Results for author: Can Jin

Found 6 papers, 3 papers with code

RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models

no code implementations2 Feb 2025 Can Jin, Hongwu Peng, Anxiang Zhang, Nuo Chen, Jiahui Zhao, Xi Xie, Kuangzheng Li, Shuya Feng, Kai Zhong, Caiwen Ding, Dimitris N. Metaxas

In an Information Retrieval (IR) system, reranking plays a critical role by sorting candidate passages according to their relevance to a specific query.

Information Retrieval

LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation

1 code implementation2 Feb 2025 Can Jin, Ying Li, Mingyu Zhao, Shiyu Zhao, Zhenting Wang, Xiaoxiao He, Ligong Han, Tong Che, Dimitris N. Metaxas

Visual prompting has gained popularity as a method for adapting pre-trained models to specific tasks, particularly in the realm of parameter-efficient tuning.

Inductive Bias Visual Prompting

Graph Canvas for Controllable 3D Scene Generation

no code implementations27 Nov 2024 Libin Liu, Shen Chen, Sen Jia, Jingzhe Shi, Zhongyu Jiang, Can Jin, Wu Zongkai, Jenq-Neng Hwang, Lei LI

Spatial intelligence is foundational to AI systems that interact with the physical world, particularly in 3D scene generation and spatial comprehension.

In-Context Learning Scene Generation

APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking

no code implementations20 Jun 2024 Can Jin, Hongwu Peng, Shiyu Zhao, Zhenting Wang, Wujiang Xu, Ligong Han, Jiahui Zhao, Kai Zhong, Sanguthevar Rajasekaran, Dimitris N. Metaxas

Existing automatic prompt engineering algorithms primarily focus on language modeling and classification tasks, leaving the domain of IR, particularly reranking, underexplored.

Information Retrieval Language Modeling +4

Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate

1 code implementation5 Feb 2024 Can Jin, Tong Che, Hongwu Peng, Yiyuan Li, Dimitris N. Metaxas, Marco Pavone

The student learners are trained by the main model and, in turn, provide feedback to help the main model capture more generalizable and imitable correlations.

Image Classification Language Modelling +1

Visual Prompting Upgrades Neural Network Sparsification: A Data-Model Perspective

1 code implementation3 Dec 2023 Can Jin, Tianjin Huang, Yihua Zhang, Mykola Pechenizkiy, Sijia Liu, Shiwei Liu, Tianlong Chen

The rapid development of large-scale deep learning models questions the affordability of hardware platforms, which necessitates the pruning to reduce their computational and memory footprints.

Image Classification Visual Prompting

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