3 accepted papers
Large Language Models (LLMs) with extended context lengths face significant computational challenges during the pre-filling phase, primarily due to the quadratic complexity of self-attention. Existing methods typically employ dynamic pattern matching and block-sparse low-level implementations. Howev
Multimodal knowledge graph completion (MKGC) aims to predict missing triples in MKGs using multimodal information. Recent research typically either extracts information from each modality separately to predict, then ensembles the predictions at the decision stage, or projects multiple modalities int…
Affordance refers to the functional properties that an agent perceives and utilizes from its environment, and is key perceptual information required for robots to perform actions. This information is rich and multimodal in nature. Existing multimodal affordance methods face limitations in extracting