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Found 8 papers, 6 papers with code
Counterfactual Evaluation of Ads Ranking Models through Domain Adaptation
We propose a domain-adapted reward model that works alongside an Offline A/B testing system for evaluating ranking models.
Online Detection of Anomalies in Temporal Knowledge Graphs with Interpretability
When new knowledge emerges, AnoT maps it onto a node in the rule graph and traverses the rule graph recursively to derive the anomaly score of the knowledge.
DTGB: A Comprehensive Benchmark for Dynamic Text-Attributed Graphs
Moreover, we conduct extensive benchmark experiments on DTGB, evaluating 7 popular dynamic graph learning algorithms and their variants of adapting to text attributes with LLM embeddings, along with 6 powerful large language models (LLMs).
StreamE: Learning to Update Representations for Temporal Knowledge Graphs in Streaming Scenarios
To reduce the parameter size, entity representations in StreamE are decoupled from the model training to serve as the memory module to store the historical information of entities.
Temporal knowledge graph representation learning with local and global evolutions
Temporal knowledge graph (TKG) representation learning aims to project entities and relations in TKG to low-dimensional vector space while preserving the evolutionary nature of TKG.
Complex Locomotion Skill Learning via Differentiable Physics
Differentiable physics enables efficient gradient-based optimizations of neural network (NN) controllers.
Privacy Preserving in Non-Intrusive Load Monitoring: A Differential Privacy Perspective
In this paper, we cast one-shot non-intrusive load monitoring (NILM) in the compressive sensing framework, and bridge the gap between theoretical accuracy of NILM inference and differential privacy's parameters.
Treat the Word As a Whole or Look Inside? Subword Embeddings Model Language Change and Typology
We use a variant of word embedding model that incorporates subword information to characterize the degree of compositionality in lexical semantics.
