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Found 8 papers, 4 papers with code
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
In conclusion, this paper provides valuable insights into the potential applications and challenges of MLLMs in human-centric computing.
Federated Full-Parameter Tuning of Billion-Sized Language Models with Communication Cost under 18 Kilobytes
Pre-trained large language models (LLMs) need fine-tuning to improve their responsiveness to natural language instructions.
Learning Multi-Pattern Normalities in the Frequency Domain for Efficient Time Series Anomaly Detection
Anomaly detection significantly enhances the robustness of cloud systems.
CodeScope: An Execution-based Multilingual Multitask Multidimensional Benchmark for Evaluating LLMs on Code Understanding and Generation
To bridge these gaps between existing benchmarks and expectations from practical applications, we introduce CodeScope, an execution-based, multilingual, multi-task, multi-dimensional evaluation benchmark for comprehensively gauging LLM capabilities on coding tasks.
LARA: A Light and Anti-overfitting Retraining Approach for Unsupervised Time Series Anomaly Detection
Retraining a large neural network model with limited data is vulnerable to overfitting.
Resisting Backdoor Attacks in Federated Learning via Bidirectional Elections and Individual Perspective
Existing approaches defend against backdoor attacks in federated learning (FL) mainly through a) mitigating the impact of infected models, or b) excluding infected models.
PePNet: A Periodicity-Perceived Workload Prediction Network Supporting Rare Occurrence of Heavy Workload
This impairs the prediction accuracy of neural network-based models on heavy workload.
Cyclic Arbitrage in Decentralized Exchanges
We find that traders have executed 292, 606 cyclic arbitrages over eleven months and exploited more than 138 million USD in revenue.
