However, sampling is not the only source of uncertainty. In practice, distributions change between locations and across time.

The acronym dataset is a QA task that requires models to decode financial acronyms. The FinMA7B-full model achieved the highest ROUGE-1 score of 0.12 and the B.1 Why was the datasheet created? B.2 Has the dataset been used already? If so, where are the results so others can compare (e.g., links to published papers)? Y es, the dataset has already been used. It was employed in the FinLLM Share Task during the FinNLP-AgentScen Workshop at IJCAI 2024, known as the FinLLM Challenge.

Figure 10: Illustration of the frame-based pupil segmentation: (a) the input eye image I; (b) the generate binary mask M; and (c) the detected pupil boundary Q and the pupil center c. 16 C More Details in Experiment C.1 Evaluation metrics The detailed description of the four metrics adopted for the dataset evalution are as follows:

We seek to address the limitations of existing datasets in this area. Many such datasets lack a coherent traffic network graph to describe the relationship between sensors.

Unqualified images are removed as described in Appendix A.3. Was the "raw" data saved in addition to the preprocessed/cleaned/labeled data (e.g., to