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Found 20 papers, 10 papers with code
Learn to Adapt for Generalized Zero-Shot Text Classification
Generalized zero-shot text classification aims to classify textual instances from both previously seen classes and incrementally emerging unseen classes.
Generative-Contrastive Heterogeneous Graph Neural Network
In recent years, inspired by self-supervised learning, contrastive Heterogeneous Graphs Neural Networks (HGNNs) have shown great potential by utilizing data augmentation and discriminators for downstream tasks.
Scientific Large Language Models: A Survey on Biological & Chemical Domains
Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence.
CETN: Contrast-enhanced Through Network for CTR Prediction
Click-through rate (CTR) Prediction is a crucial task in personalized information retrievals, such as industrial recommender systems, online advertising, and web search.
Ranked #4 on
Click-Through Rate Prediction
on Avazu
Venn: Resource Management Across Federated Learning Jobs
Scheduling edge resources among multiple FL jobs is different from GPU scheduling for cloud ML because of the ephemeral nature and planetary scale of participating devices as well as the overlapping resource requirements of diverse FL jobs.
DoseDiff: Distance-aware Diffusion Model for Dose Prediction in Radiotherapy
Treatment planning, which is a critical component of the radiotherapy workflow, is typically carried out by a medical physicist in a time-consuming trial-and-error manner.
HyperTuner: A Cross-Layer Multi-Objective Hyperparameter Auto-Tuning Framework for Data Analytic Services
Besides, experiments with different training datasets, different optimization objectives and different machine learning platforms verify that HyperTuner can well adapt to various data analytic service scenarios.
ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models
To address these challenges in English language teaching, we first present ArguGPT, a balanced corpus of 4, 038 argumentative essays generated by 7 GPT models in response to essay prompts from three sources: (1) in-class or homework exercises, (2) TOEFL and (3) GRE writing tasks.
Investigating Transfer Learning in Multilingual Pre-trained Language Models through Chinese Natural Language Inference
These results, however, come with important caveats: cross-lingual models often perform best when trained on a mixture of English and high-quality monolingual NLI data (OCNLI), and are often hindered by automatically translated resources (XNLI-zh).
MUSE: Multi-faceted Attention for Signed Network Embedding
Signed network embedding is an approach to learn low-dimensional representations of nodes in signed networks with both positive and negative links, which facilitates downstream tasks such as link prediction with general data mining frameworks.
Hypernetwork Dismantling via Deep Reinforcement Learning
Network dismantling aims to degrade the connectivity of a network by removing an optimal set of nodes.
Causal Learner: A Toolbox for Causal Structure and Markov Blanket Learning
Causal Learner is a toolbox for learning causal structure and Markov blanket (MB) from data.
Heterogeneous Information Network-based Interest Composition with Graph Neural Network for Recommendation
Then, users' interests in each item from each pair of related meta-paths are calculated by a combination of the user and item representations.
HyperCI: A Higher Order Collective Influence Measure for Hypernetwork Dismantling
However, conventional network dismantling approaches focus on simple network which models only pairwise interaction between nodes while groupwise interactions among arbitrary number of nodes are ubiquitous in networked systems like integrated circuits.
Social and Information Networks Physics and Society
Session-based Social and Dependency-aware Software Recommendation
With the increase of complexity of modern software, social collaborative coding and reuse of open source software packages become more and more popular, which thus greatly enhances the development efficiency and software quality.
CLUE: A Chinese Language Understanding Evaluation Benchmark
The advent of natural language understanding (NLU) benchmarks for English, such as GLUE and SuperGLUE allows new NLU models to be evaluated across a diverse set of tasks.
How Distance Transform Maps Boost Segmentation CNNs: An Empirical Study
The \emph{second contribution} is that we systematically evaluated five benchmark methods on two representative public datasets.
Ensemble Methods to Distinguish Mainland and Taiwan Chinese
This paper describes the IUCL system at VarDial 2019 evaluation campaign for the task of discriminating between Mainland and Taiwan variation of mandarin Chinese.
Path of Vowel Raising in Chengdu Dialect of Mandarin
He and Rao (2013) reported a raising phenomenon of /a/ in /Xan/ (X being a consonant or a vowel) in Chengdu dialect of Mandarin, i. e. /a/ is realized as [epsilon] for young speakers but [ae] for older speakers, but they offered no acoustic analysis.
