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Found 4 papers, 2 papers with code
Alleviating Over-smoothing for Unsupervised Sentence Representation
Currently, learning better unsupervised sentence representations is the pursuit of many natural language processing communities.
Bridge the Gap between Language models and Tabular Understanding
For instance, TPLMs jointly pre-trained with table and text input could be effective for tasks also with table-text joint input like table question answering, but it may fail for tasks with only tables or text as input such as table retrieval.
Thousand to One: Semantic Prior Modeling for Conceptual Coding
To this end, we propose a novel end-to-end semantic prior modeling-based conceptual coding scheme towards extremely low bitrate image compression, which leverages semantic-wise deep representations as a unified prior for entropy estimation and texture synthesis.
Conceptual Compression via Deep Structure and Texture Synthesis
To this end, we propose a novel conceptual compression framework that encodes visual data into compact structure and texture representations, then decodes in a deep synthesis fashion, aiming to achieve better visual reconstruction quality, flexible content manipulation, and potential support for various vision tasks.
