Large Language Model
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.
