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Found 5 papers, 2 papers with code
ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline
Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem-solving.
Boosting Physical Layer Black-Box Attacks with Semantic Adversaries in Semantic Communications
To this end, we present SemBLK, a novel method that can learn to generate destructive physical layer semantic attacks for an ESC system under the black-box setting, where the adversaries are imperceptible to humans.
Modelling and Explaining Legal Case-based Reasoners through Classifiers
In this paper we combine the modal logic approach (binary-input classifier, BLC) to classifiers and their explanations given by Liu & Lorini (2021) with Horty's account of factor-based CBR, since both a classifier and CBR map sets of features to decisions or classifications.
CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers
Large-scale pretrained transformers have created milestones in text (GPT-3) and text-to-image (DALL-E and CogView) generation.
Ranked #12 on
Video Generation
on UCF-101
A unified logical framework for explanations in classifier systems
Finally, we present two extensions of our language: a dynamic extension by the notion of assignment enabling classifier change and an epistemic extension in which the classifier's uncertainty about the actual input can be represented.
