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Found 5 papers, 2 papers with code
When Hindsight is Not 20/20: Testing Limits on Reflective Thinking in Large Language Models
In this paper, we set out to clarify these capabilities under a more stringent evaluation setting in which we disallow any kind of external feedback.
Towards Training A Chinese Large Language Model for Anesthesiology
3) We introduce a standardized benchmark for evaluating medical LLM in Anesthesiology.
Learning from Polar Representation: An Extreme-Adaptive Model for Long-Term Time Series Forecasting
In the hydrology field, time series forecasting is crucial for efficient water resource management, improving flood and drought control and increasing the safety and quality of life for the general population.
Self-Supervised Video Transformers for Isolated Sign Language Recognition
This paper presents an in-depth analysis of various self-supervision methods for isolated sign language recognition (ISLR).
An Extreme-Adaptive Time Series Prediction Model Based on Probability-Enhanced LSTM Neural Networks
Forecasting time series with extreme events has been a challenging and prevalent research topic, especially when the time series data are affected by complicated uncertain factors, such as is the case in hydrologic prediction.
