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- RAP: Retrieval-Augmented Planning with Contextual Memory for Multimodal LLM Agents101
Empirical evaluations demonstrate RAP's effectiveness, where it achieves SOTA performance in textual scenarios and notably enhances multimodal LLM agents' performance for embodied tasks, highlighting RAP's potential in advancing the functionality and applicability of LLM agents in complex, real-world applications.
- Design and data analysis of wearable sports posture measurement system based on Internet of Things32
The experimental results show that the wearable sports posture measurement system can perform stable online monitoring of the exercise process, and the data analysis results have a certain reference value for the evaluation of the patient's physical condition during rehabilitation and the daily training evaluation of athletes.
- Emphasizing Discriminative Features for Dataset Distillation in Complex Scenarios23
EDF (emphasizes the discriminative features), a dataset distillation method that enhances key discriminative regions in synthetic images using Grad-CAM activation maps using Grad-CAM activation maps.
- DD-Ranking: Rethinking the Evaluation of Dataset Distillation14
DD-Ranking, a unified evaluation framework, along with new general evaluation metrics to uncover the true performance improvements achieved by different methods are proposed, which provide a more comprehensive and fair evaluation standard for future research advancements.
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- A human pose estimation algorithm based on the integration of improved convolutional neural networks and multi-level graph structure constrained model8
A large number of qualitative and quantitative experimental results show that compared with other state-of-art methods, the integration of the deep learning network and the multi-level pictorial structure model can improve the accuracy of human pose estimation to a greater extent.
- Motion Balance Ability Detection Based on Video Analysis in Virtual Reality Environment4
This article proposes a tracking method Motion Model and Model Updater (MMMU) based on the balance acquisition and model update and intelligent adjustment of the motion model based on simple linear iterative clustering, which completes the abstraction of background images.
- CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregation2
This paper proposes a novel method for sim-to-real pose estimation, which is effective on both instance-level and category-level settings, based on the point-pair voting scheme from CPPF to vote for object centers, orientations, and scales.
- Similarity Graph Convolutional Construction Network for Interactive Action Recognition1
The result shows that the approach outperforms the state-of-the-art methods and similarity graph can solve the relationship modeling problem in interactive action recognition.
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- CDIO: Cross-Domain Inference Optimization with Resource Preference Prediction for Edge-Cloud Collaboration–
CDIO, a cross-domain inference optimization framework designed for edge-cloud collaboration, can predict resource preference types by analyzing spatial complexity and processing requirements of the task and guide resource allocation in the edge-cloud system.
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- Extending Depth of Field for Varifocal Multiview Images–
This work proposes an end-to-end method for the EDoF of varifocal multiview images, including image alignment, image optimization and image fusion, and results demonstrate the efficiency of the proposed method.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-11. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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