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Found 4 papers, 3 papers with code
A Simple Baseline for Predicting Events with Auto-Regressive Tabular Transformers
Moreover, these approaches often assume specific use-cases, for example that we know the labels of all historic events or that we only predict a pre-specified label and not the data's features themselves.
Transformers Can Do Arithmetic with the Right Embeddings
The poor performance of transformers on arithmetic tasks seems to stem in large part from their inability to keep track of the exact position of each digit inside of a large span of digits.
Coercing LLMs to do and reveal (almost) anything
It has recently been shown that adversarial attacks on large language models (LLMs) can "jailbreak" the model into making harmful statements.
Neural Auctions Compromise Bidder Information
It has been shown that neural networks can be used to approximate optimal mechanisms while satisfying the constraints that an auction be strategyproof and individually rational.
