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Found 11 papers, 3 papers with code
Can bidirectional encoder become the ultimate winner for downstream applications of foundation models?
Foundational models have the characteristics of pre-training, transfer learning, and self-supervised learning, and pre-trained models can be fine-tuned and applied to various downstream tasks.
Stochastic diagonal estimation with adaptive parameter selection
In this paper, we investigate diagonal estimation for large or implicit matrices, aiming to develop a novel and efficient stochastic algorithm that incorporates adaptive parameter selection.
Movie Recommendation with Poster Attention via Multi-modal Transformer Feature Fusion
This study proposes a multi-modal movie recommendation system by extract features of the well designed posters for each movie and the narrative text description of the movie.
EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation
EchoMamba4Rec leverages these control relationships in sequential recommendation and integrates bi-directional processing with frequency-domain filtering to capture complex patterns and dependencies in user interaction data more effectively.
Quantformer: from attention to profit with a quantitative transformer trading strategy
In traditional quantitative trading practice, navigating the complicated and dynamic financial market presents a persistent challenge.
Unleashing the potential of prompt engineering in Large Language Models: a comprehensive review
This comprehensive review delves into the pivotal role of prompt engineering in unleashing the capabilities of Large Language Models (LLMs).
Learning with linear mixed model for group recommendation systems
Accurate prediction of users' responses to items is one of the main aims of many computational advising applications.
CSGO: Constrained-Softassign Gradient Optimization For Large Graph Matching
The advanced constraining operator enables a CSGO for large graph matching, which outperforms state-of-the-art methods in experiments.
Generalized Rough Polyharmonic Splines for Multiscale PDEs with Rough Coefficients
In this paper, we demonstrate the construction of generalized Rough Polyhamronic Splines (GRPS) within the Bayesian framework, in particular, for multiscale PDEs with rough coefficients.
Numerical Analysis Numerical Analysis
Fabricated Pictures Detection with Graph Matching
Fabricating experimental pictures in research work is a serious academic misconduct, which should better be detected in the reviewing process.
Sparse inversion for derivative of log determinant
Algorithms for Gaussian process, marginal likelihood methods or restricted maximum likelihood methods often require derivatives of log determinant terms.
