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Found 5 papers, 3 papers with code
Enhancing LLM Factual Accuracy with RAG to Counter Hallucinations: A Case Study on Domain-Specific Queries in Private Knowledge-Bases
We proposed an end-to-end system design towards utilizing Retrieval Augmented Generation (RAG) to improve the factual accuracy of Large Language Models (LLMs) for domain-specific and time-sensitive queries related to private knowledge-bases.
Bipartite Graph Pre-training for Unsupervised Extractive Summarization with Graph Convolutional Auto-Encoders
Pre-trained sentence representations are crucial for identifying significant sentences in unsupervised document extractive summarization.
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
Our research, initially spurred by test-time evasion attacks, investigates the intersection of adversarial training and backdoor attacks within federated learning, introducing Adversarial Robustness Unhardening (ARU).
Tencent's Multilingual Machine Translation System for WMT22 Large-Scale African Languages
This paper describes Tencent's multilingual machine translation systems for the WMT22 shared task on Large-Scale Machine Translation Evaluation for African Languages.
SAFELearning: Enable Backdoor Detectability In Federated Learning With Secure Aggregation
For model privacy, local model parameters in federated learning shall be obfuscated before sent to the remote aggregator.
