From 0fdd21e6b6d86c26f6cf8dc63fadd855775e3173 Mon Sep 17 00:00:00 2001 From: Yuan Yao Date: Fri, 2 Feb 2024 18:09:30 +0800 Subject: [PATCH] Update README.md --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index 992340a..a568bf7 100644 --- a/README.md +++ b/README.md @@ -49,7 +49,7 @@ - 🏆 **Trustworthy Behavior.** - LMMs are known for suffering from hallucination, often generating text that is not factually grounded in images (e.g., faithfully describing non-existing objects in images). OmniLMM-12B is **the first state-of-the-art open-source LMM aligned via multimodal RLHF for trustworthy behavior** (using our recent [RLHF-V](https://rlhf-v.github.io/) technique). It **ranks #1** among open-source models on [MMHal-Bench](https://huggingface.co/datasets/Shengcao1006/MMHal-Bench), and **outperforms GPT-4V** on [Object HalBench](https://arxiv.org/abs/2312.00849). + LMMs are known for suffering from hallucination, often generating text that is not factually grounded in images (e.g., faithfully describing non-existing objects in images). OmniLMM-12B is **the first state-of-the-art open-source LMM aligned via multimodal RLHF for trustworthy behavior** (using the recent [RLHF-V](https://rlhf-v.github.io/) technique). It **ranks #1** among open-source models on [MMHal-Bench](https://huggingface.co/datasets/Shengcao1006/MMHal-Bench), and **outperforms GPT-4V** on [Object HalBench](https://arxiv.org/abs/2312.00849). - 🕹 **Real-time Multimodal Interaction.** @@ -196,7 +196,7 @@ We combine the OmniLMM-12B and GPT-3.5 (text-only) into a **real-time multimodal - 🙌 **Bilingual Support.** - OmniLMM-3B is **the first edge-deployable LMM supporting bilingual multimodal interaction in English and Chinese**. This is achieved by generalizing multimodal capabilities across languages, a technique from our ICLR 2024 spotlight [paper](https://arxiv.org/abs/2308.12038). + OmniLMM-3B is **the first edge-deployable LMM supporting bilingual multimodal interaction in English and Chinese**. This is achieved by generalizing multimodal capabilities across languages, a technique from the ICLR 2024 spotlight [paper](https://arxiv.org/abs/2308.12038). ### Evaluation