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Found 3 papers, 1 papers with code
TAAT: Think and Act from Arbitrary Texts in Text2Motion
In this challenging dataset, we benchmark existing state-of-the-art methods and propose a novel two-stage framework to extract action labels from arbitrary texts by the Large Language Model (LLM) and then generate motions from action labels.
HumanNeRF-SE: A Simple yet Effective Approach to Animate HumanNeRF with Diverse Poses
Our architecture involving both explicit and implicit representation is simple yet effective.
Improving Stack Overflow question title generation with copying enhanced CodeBERT model and bi-modal information
However, only using the code snippets in the question body cannot provide sufficient information for title generation, and LSTMs cannot capture the long-range dependencies between tokens.
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