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Found 15 papers, 9 papers with code
Parameter-efficient Prompt Learning for 3D Point Cloud Understanding
Finally, a lightweight PointAdapter module is arranged near target tasks to enhance prompt tuning for 3D point cloud understanding.
Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing
The simulation platform integrates a traffic emission model and a speed-density traffic flow model to characterize the interactions between traffic congestion levels and emissions.
Infrastructure Crack Segmentation: Boundary Guidance Method and Benchmark Dataset
Cracks provide an essential indicator of infrastructure performance degradation, and achieving high-precision pixel-level crack segmentation is an issue of concern.
Scaling Laws of Dynamic High-Capacity Ride-Sharing
Dynamic ride-sharing services, including ride-pooling offered by ride-hailing platforms and demand-responsive buses, have become an essential part of urban mobility systems.
MLOps Spanning Whole Machine Learning Life Cycle: A Survey
We hope that this paper can serve as a quick reference manual (a survey of surveys) for newcomers (e. g., researchers, practitioners) of ML to get an overview of the MLOps process, as well as a good understanding of the key technologies used in each step of the ML process, and know where to find more details.
Global Mixup: Eliminating Ambiguity with Clustering
(2) linear combination significantly limits the sampling space for generating samples.
A novel multiobjective evolutionary algorithm based on decomposition and multi-reference points strategy
For performance assessment, the proposed algorithm is compared with existing four state-of-the-art multiobjective evolutionary algorithms on benchmark test problems with various types of Pareto optimal fronts.
Dialogue Summarization with Supporting Utterance Flow Modeling and Fact Regularization
The supporting utterance flow modeling helps to generate a coherent summary by smoothly shifting the focus from the former utterances to the later ones.
A Training-free and Reference-free Summarization Evaluation Metric via Centrality-weighted Relevance and Self-referenced Redundancy
Our metric consists of a centrality-weighted relevance score and a self-referenced redundancy score.
A Unified Dual-view Model for Review Summarization and Sentiment Classification with Inconsistency Loss
Review summarization aims at generating a concise summary that describes the key opinions and sentiment of a review, while sentiment classification aims to predict a sentiment label indicating the sentiment attitude of a review.
Exclusive Hierarchical Decoding for Deep Keyphrase Generation
A new setting is recently introduced into this problem, in which, given a document, the model needs to predict a set of keyphrases and simultaneously determine the appropriate number of keyphrases to produce.
Neural Keyphrase Generation via Reinforcement Learning with Adaptive Rewards
To address this problem, we propose a reinforcement learning (RL) approach for keyphrase generation, with an adaptive reward function that encourages a model to generate both sufficient and accurate keyphrases.
An Integrated Approach for Keyphrase Generation via Exploring the Power of Retrieval and Extraction
For further exploiting the power of extraction and retrieval, we propose a neural-based merging module to combine and re-rank the predicted keyphrases from the enhanced generative model, the extractive model, and the retrieved keyphrases.
Title-Guided Encoding for Keyphrase Generation
Keyphrase generation (KG) aims to generate a set of keyphrases given a document, which is a fundamental task in natural language processing (NLP).
Difficulty Controllable Generation of Reading Comprehension Questions
We investigate the difficulty levels of questions in reading comprehension datasets such as SQuAD, and propose a new question generation setting, named Difficulty-controllable Question Generation (DQG).
