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Found 6 papers, 2 papers with code
Step-wise Adaptive Integration of Supervised Fine-tuning and Reinforcement Learning for Task-Specific LLMs
Large language models (LLMs) excel at mathematical reasoning and logical problem-solving.
Alignment faking in large language models
Explaining this gap, in almost all cases where the model complies with a harmful query from a free user, we observe explicit alignment-faking reasoning, with the model stating it is strategically answering harmful queries in training to preserve its preferred harmlessness behavior out of training.
BugBlitz-AI: An Intelligent QA Assistant
The evolution of software testing from manual to automated methods has significantly influenced quality assurance (QA) practices.
Bolt: Bridging the Gap between Auto-tuners and Hardware-native Performance
Today's auto-tuners (e. g., AutoTVM, Ansor) generate efficient tensor programs by navigating a large search space to identify effective implementations, but they do so with opaque hardware details.
Experimental Demonstration of Learned Time-Domain Digital Back-Propagation
We present the first experimental demonstration of learned time-domain digital back-propagation (DBP), in 64-GBd dual-polarization 64-QAM signal transmission over 1014 km.
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness
For sensitive problems, such as medical imaging or fraud detection, Neural Network (NN) adoption has been slow due to concerns about their reliability, leading to a number of algorithms for explaining their decisions.
Ranked #1 on
Robust classification
on CIFAR-10
