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Found 8 papers, 3 papers with code
Efficient Long Sequential Low-rank Adaptive Attention for Click-through rate Prediction
In the context of burgeoning user historical behavior data, Accurate click-through rate(CTR) prediction requires effective modeling of lengthy user behavior sequences.
Interweaving Memories of a Siamese Large Language Model
A promising approach to mitigate this issue is to recall prior memories based on the original knowledge.
A Unified Temporal Knowledge Graph Reasoning Model Towards Interpolation and Extrapolation
Comprehensive experiments show that TPAR outperforms SOTA methods on the link prediction task for both the interpolation and the extrapolation settings.
The Solution for the ICCV 2023 1st Scientific Figure Captioning Challenge
In this paper, we propose a solution for improving the quality of captions generated for figures in papers.
Robust Semi-Supervised Learning for Self-learning Open-World Classes
Existing semi-supervised learning (SSL) methods assume that labeled and unlabeled data share the same class space.
MixTEA: Semi-supervised Entity Alignment with Mixture Teaching
More importantly, in pseudo mapping learning, we propose a bi-directional voting (BDV) strategy that fuses the alignment decisions in different directions to estimate the uncertainty via the joint matching confidence score.
Soft Retargeting Network for Click Through Rate Prediction
In this paper, we focus on a new type of user interest, i. e., user retargeting interest.
Tensor-Train Parameterization for Ultra Dimensionality Reduction
Thus, we propose a tensor-train parameterization for ultra dimensionality reduction (TTPUDR) in which the traditional LPP mapping is tensorized in terms of tensor-trains and the LPP objective is replaced with the Frobenius norm to increase the robustness of the model.
