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Found 4 papers, 1 papers with code
Confidence Calibration and Rationalization for LLMs via Multi-Agent Deliberation
Uncertainty estimation is a significant issue for current large language models (LLMs) that are generally poorly calibrated and over-confident, especially with reinforcement learning from human feedback (RLHF).
Visual Analytics for Generative Transformer Models
While transformer-based models have achieved state-of-the-art results in a variety of classification and generation tasks, their black-box nature makes them challenging for interpretability.
Training Socially Aligned Language Models on Simulated Social Interactions
Social alignment in AI systems aims to ensure that these models behave according to established societal values.
Robust Power Allocation for UAV-aided ISAC Systems with Uncertain Location Sensing Errors
Unmanned aerial vehicle (UAV) holds immense potential in integrated sensing and communication (ISAC) systems for the Internet of Things (IoT).
