1 citations · 4 across the 6 of their papers we have counts for
6 papers
Aligning Multimodal LLM with Human Preference: A Survey
Tao Yu, Yi-Fan Zhang, Chaoyou Fu +14
Large language models (LLMs) can handle a wide variety of general tasks with simple prompts, without the need for task-specific training. Multimodal Large Language Models (MLLMs),…
LogoRA: Local-Global Representation Alignment for Robust Time Series Classification
Huanyu Zhang, Yi-Fan Zhang, Zhang Zhang +2
Unsupervised domain adaptation (UDA) of time series aims to teach models to identify consistent patterns across various temporal scenarios, disregarding domain-specific differences…
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
Yi-Fan Zhang, Huanyu Zhang, Haochen Tian +10
Comprehensive evaluation of Multimodal Large Language Models (MLLMs) has recently garnered widespread attention in the research community. However, we observe that existing benchma…
Beyond LLaVA-HD: Diving into High-Resolution Large Multimodal Models
Yi-Fan Zhang, Qingsong Wen, Chaoyou Fu +4
Seeing clearly with high resolution is a foundation of Large Multimodal Models (LMMs), which has been proven to be vital for visual perception and reasoning. Existing works usually…
Addressing Concept Shift in Online Time Series Forecasting: Detect-then-Adapt
YiFan Zhang, Weiqi Chen, Zhaoyang Zhu +7
Online updating of time series forecasting models aims to tackle the challenge of concept drifting by adjusting forecasting models based on streaming data. While numerous algorithm…
Debiasing Multimodal Large Language Models via Penalization of Language Priors
YiFan Zhang, Yang Shi, Weichen Yu +6
In the realms of computer vision and natural language processing, Multimodal Large Language Models (MLLMs) have become indispensable tools, proficient in generating textual respons…