Oceania
These butter-sized hatchlings will someday be the biggest lizards on Earth
The endangered baby Komodo dragons were recently born at ZooTampa. Breakthroughs, discoveries, and DIY tips sent every weekday. Though Komodo Dragons () live only on a few Indonesian islands --including the aptly named island of Komodo--they're pretty famous reptiles . That's because they are the largest and heaviest lizards in the world, growing up to eight to ten feet long and weighing between 100 and 150 pounds on average. With a forked tongue, long claws, and a strong venomous bite, they certainly live up to their mythological name.
Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter
Until now, no tabular method has consistently outperformed classical supervised learning, which ignores these shifts.
Diffusion-based Curriculum Reinforcement Learning
V arious approaches have been proposed for the generation of curriculum goals.
Appendix A Additional results This appendix section shows additional results and corresponding plots to support the insights
Section A.2 shows results using a chat-style verbalized numeric Section A.3 shows results on four extra benchmark tasks made available with Finally, Section A.5 presents and discusses results on feature In this section, we evaluate risk score calibration on the income prediction task across different subpopulations, such as typically done as part of a fairness audit. Figures A1-A2 show group-conditional calibration curves for all models on the ACSIncome task, evaluated on three subgroups specified by the race attribute in the ACS data. We show the three race categories with largest representation. The'Mixtral 8x22B' and'Yi 34B' models shown are the worst offenders, where samples belonging to the'Black' population see consistently lower scores for the same positive label probability when compared to the'Asian' or'White' populations. On average, the'Mixtral 8x22B (it)' model classifies a Black individual with a In fact, this score bias can be reversed for some base models, overestimating scores from Black individuals compared with other subgroups.
Evaluating language models as risk scores
Current question-answering benchmarks predominantly focus on accuracy in realizable prediction tasks.
Man Ho Lam 1 Eric John Li
Evaluating Large Language Models' (LLMs) anthropomorphic capabilities has
FinBen: A Holistic Financial Benchmark for Large Language Models
Their novel solutions outperformed GPT -4, showcasing FinBen's potential to drive innovations in financial LLMs.