From the 1 of 19 linked papers with an AI index.
2 citations · 2 across the 4 of their papers we have counts for
7 papers · 1 filter
LongLLaVA: Scaling Multi-modal LLMs to 1000 Images Efficiently via a Hybrid Architecture
Xidong Wang, Dingjie Song, Shunian Chen +5
Expanding the long-context capabilities of Multi-modal Large Language Models~(MLLMs) is critical for advancing video understanding and high-resolution image analysis. Achieving thi…
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Jimin Huang, Mengxi Xiao, Dong Li +41
Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…
Humans or LLMs as the Judge? A Study on Judgement Biases
Guiming Hardy Chen, Shunian Chen, Ziche Liu +2
Adopting human and large language models (LLM) as judges (a.k.a human- and LLM-as-a-judge) for evaluating the performance of LLMs has recently gained attention. Nonetheless, this a…
HuatuoGPT-II, One-stage Training for Medical Adaption of LLMs
Junying Chen, Xidong Wang, Ke Ji +11
Adapting a language model into a specific domain, a.k.a `domain adaption', is a common practice when specialized knowledge, e.g. medicine, is not encapsulated in a general language…
MLLM-Bench: Evaluating Multimodal LLMs with Per-sample Criteria
Wentao Ge, Shunian Chen, Guiming Hardy Chen +14
Multimodal large language models (MLLMs) have broadened the scope of AI applications. Existing automatic evaluation methodologies for MLLMs are mainly limited in evaluating queries…
ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models
Guiming Hardy Chen, Shunian Chen, Ruifei Zhang +7
Large vision-language models (LVLMs) have shown premise in a broad range of vision-language tasks with their strong reasoning and generalization capabilities. However, they require…