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- Automatic Spatially-Aware Fashion Concept Discovery341
This paper proposes an automatic spatially-aware concept discovery approach using weakly labeled image-text data from shopping websites, and decomposes the visual-semantic embedding space into multiple concept-specific subspaces to facilitate structured browsing and attribute-feedback product retrieval.
- LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples326
It is demonstrated that nonsensical prompts composed of random tokens can also elicit the LLMs to respond with hallucinations, and an automatic hallucination triggering method is formalized as thehallucination attack in an adversarial way.
- MetaTool Benchmark for Large Language Models: Deciding Whether to Use Tools and Which to Use244
MetaTool is introduced, a benchmark designed to evaluate whether LLMs have tool usage awareness and can correctly choose tools, and recommends that tool developers choose an appropriate rewrite model for generating new descriptions based on the downstream LLM the tool will apply to.
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- Predicting remaining useful life of rolling bearings based on deep feature representation and long short-term memory neural network129
A new remaining useful life prediction approach based on deep feature representation and long short-term memory neural network is proposed, and a new criterion, named support vector data normalized correlation coefficient, is proposed to automatically divide the whole bearing life as normal state and fast degradation state.
- 1000× Faster Camera and Machine Vision with Ordinary Devices116
A spiking neural network-based machine vision system that combines the speed of the machine and the mechanism of biological vision, achieving high-speed object detection and tracking 1,000x faster than human vision is developed.
- The iMaterialist Fashion Attribute Dataset93
This work contributes to the community a new dataset called iMaterialist Fashion Attribute (iFashion-Attribute), constructed from over one million fashion images with a label space that includes 8 groups of 228 fine-grained attributes in total, which is the first known million-scale multi-label and fine- grained image dataset.
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- Deep learning-based evaluation of the relationship between mandibular third molar and mandibular canal on CBCT67
An automated approach based on CNNs for detection and evaluation of the M3 and MC on CBCT has been established, which can be utilized to improve diagnostic efficiency and facilitate the precision diagnosis and treatment of M3.
- Ta-Coated Titanium Surface With Superior Bacteriostasis And Osseointegration64
In vivo biological studies showed that Ta modification significantly promoted the osseointegration of implants by stimulating the expression of bone-forming proteins, which may provide some insights into clinical applications of Ta-coated Ti implants, especially in possibly infected situations.
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- On the Trustworthiness of Generative Foundation Models: Guideline, Assessment, and Perspective60
A holistic framework for advancing trustworthiness in GenAI is established, paving the way for safer and more responsible integration of GenFMs into critical applications and releasing the toolkit for dynamic evaluation.
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- Deep Association: End-to-end Graph-Based Learning for Multiple Object Tracking with Conv-Graph Neural Network40
An efficient end-to-end model, Deep Association Network (DAN), to learn the graph-based training data, which are constructed by spatial-temporal interaction of objects, up to the state-of-the-art methods without extra-dataset on MOT16 and DukeMTMCT.
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- Spectrum-Effect Relationship in Chinese Herbal Medicine: Current Status and Future Perspectives32
This review proves the validity and development potential of the SER and provides a reference for the development and application of quality evaluation methods for CHM.
- A Siamese network-based tracking framework for hyperspectral video31
A novel deep hyperspectral tracker based on Siamese network (SiamHT) is presented, designed to extract the spatial and spectral semantic features, respectively, and fused to estimate the state of a target.
- GRAPH-BASED REGULARIZATION FOR REGRESSION PROBLEMS WITH HIGHLY-CORRELATED DESIGNS26
This work considers a high-dimensional regression setting in which a graph governs both correlations among the covariates and the similarity among regression coefficients, and proposes graph-based regularization that yields mean-squared error guarantees for a broad range of covariance graph structures.
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- Deep Trajectory Post-Processing and Position Projection for Single & Multiple Camera Multiple Object Tracking24
Position Projection Network (PPN) is presented to convert trajectory position from local camera-coordinate to global world-coodrinate, which provides adequate and accurate temporal-spatial information for trajectory association.
Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-14. 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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