The main cause of high latency in LLMs is the sequential decoding process, which autoregressively generates all labels and mentions for NER, significantly increase the sequence length.

With the success of deep learning, there are growing concerns over interpretability (Lipton, 2018). Ideally, the explanation should be both faithful (reflecting the model's actual behavior) and plausible

"Large Language Model" in their titles or abstracts were submitted to arXiv.

Inspired by the above motivation, we collect real cunning texts as our raw data from a famous Chinese online forum, the "Ruozhiba" (retard forum)

Current approaches to learning cooperative multi-agent behaviors assume relatively restrictive settings.

We introduce motion graph, a novel approach to the video prediction problem, which predicts future video frames from limited past data.