Then, we decouple stance-related causal features from stance-unrelated noncausal features and encourage their independence in both tasks. Considering the underlying causal mechanisms, we propose a ...

Traffic flow prediction is critical for Intelligent Transportation Systems to alleviate congestion and optimize traffic management. The existing basic Encoder-Decoder Transformer model for multi-step ...

The causal capabilities of large language models (LLMs) is a matter of significant debate, with critical implications for the use of LLMs in societally impactful domains such as medicine, science, law ...

Modular Python implementation of encoder-only, decoder-only and encoder-decoder transformer architectures from scratch, as detailed in Attention Is All You Need.

Tensor ProducT ATTenTion (TPA) Transformer (T6) is a state-of-the-art transformer model that leverages Tensor Product Attention (TPA) mechanisms to enhance performance and reduce KV cache size. This ...