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Found 5 papers, 2 papers with code
Anyprefer: An Agentic Framework for Preference Data Synthesis
High-quality preference data is essential for aligning foundation models with human values through preference learning.
GePBench: Evaluating Fundamental Geometric Perception for Multimodal Large Language Models
To address this limitation, we introduce GePBench, a novel benchmark designed to assess the geometric perception capabilities of MLLMs.
AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability
Multimodal Large Language Models (MLLMs) are widely regarded as crucial in the exploration of Artificial General Intelligence (AGI).
Ranked #155 on
Visual Question Answering
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EFUF: Efficient Fine-grained Unlearning Framework for Mitigating Hallucinations in Multimodal Large Language Models
Multimodal large language models (MLLMs) have attracted increasing attention in the past few years, but they may still generate descriptions that include objects not present in the corresponding images, a phenomenon known as object hallucination.
DRIN: Dynamic Relation Interactive Network for Multimodal Entity Linking
Multimodal Entity Linking (MEL) is a task that aims to link ambiguous mentions within multimodal contexts to referential entities in a multimodal knowledge base.
