Deep Learning
Sharing Key Semantics in Transformer Makes Efficient Image Restoration
To address these challenges, we propose boosting IR's performance by sharing the
Understanding Information Storage and Transfer in Multi-modal Large Language Models
Understanding the mechanisms of information storage and transfer in Transformer-based models is important for driving model understanding progress.
You Only Cache Once: Decoder-Decoder Architectures for Language Models Y utao Sun Li Dong
It consists of two components, i.e., a cross-decoder stacked upon a self-decoder .
A Multi-dimensional Safety Evaluation Suite for Multimodal Large Language Models
Powered by remarkable advancements in Large Language Models (LLMs), Mul-timodal Large Language Models (MLLMs) demonstrate impressive capabilities in manifold tasks.
HonestLLM: Toward an Honest and Helpful Large Language Model Chujie Gao
Particularly noteworthy is the 65.3% enhancement
TabPedia: Towards Comprehensive Visual Table Understanding with Concept Synergy
In this paper, we present a novel large vision-language model, TabPedia, equipped with a concept synergy mechanism. In this mechanism, all the involved diverse visual table understanding (VTU) tasks and multi-source visual embeddings are abstracted as concepts.