A comprehensive survey of ai-generated content (aigc): A history of generative ai from gan to chatgpt
Recently, ChatGPT, along with DALL-E-2 and Codex, has been gaining significant attention
from society. As a result, many individuals have become interested in related resources and …
from society. As a result, many individuals have become interested in related resources and …
A comprehensive survey on pretrained foundation models: A history from bert to chatgpt
Pretrained Foundation Models (PFMs) are regarded as the foundation for various
downstream tasks with different data modalities. A PFM (eg, BERT, ChatGPT, and GPT-4) is …
downstream tasks with different data modalities. A PFM (eg, BERT, ChatGPT, and GPT-4) is …
Palm-e: An embodied multimodal language model
Large language models excel at a wide range of complex tasks. However, enabling general
inference in the real world, eg, for robotics problems, raises the challenge of grounding. We …
inference in the real world, eg, for robotics problems, raises the challenge of grounding. We …
Objaverse: A universe of annotated 3d objects
Massive data corpora like WebText, Wikipedia, Conceptual Captions, WebImageText, and
LAION have propelled recent dramatic progress in AI. Large neural models trained on such …
LAION have propelled recent dramatic progress in AI. Large neural models trained on such …
Image as a foreign language: Beit pretraining for vision and vision-language tasks
A big convergence of language, vision, and multimodal pretraining is emerging. In this work,
we introduce a general-purpose multimodal foundation model BEiT-3, which achieves …
we introduce a general-purpose multimodal foundation model BEiT-3, which achieves …
Learn to explain: Multimodal reasoning via thought chains for science question answering
When answering a question, humans utilize the information available across different
modalities to synthesize a consistent and complete chain of thought (CoT). This process is …
modalities to synthesize a consistent and complete chain of thought (CoT). This process is …
Rt-2: Vision-language-action models transfer web knowledge to robotic control
A Brohan, N Brown, J Carbajal, Y Chebotar… - arXiv preprint arXiv …, 2023 - arxiv.org
We study how vision-language models trained on Internet-scale data can be incorporated
directly into end-to-end robotic control to boost generalization and enable emergent …
directly into end-to-end robotic control to boost generalization and enable emergent …
Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
We introduce MMMU: a new benchmark designed to evaluate multimodal models on
massive multi-discipline tasks demanding college-level subject knowledge and deliberate …
massive multi-discipline tasks demanding college-level subject knowledge and deliberate …
Llama-adapter v2: Parameter-efficient visual instruction model
How to efficiently transform large language models (LLMs) into instruction followers is
recently a popular research direction, while training LLM for multi-modal reasoning remains …
recently a popular research direction, while training LLM for multi-modal reasoning remains …
Inner monologue: Embodied reasoning through planning with language models
Recent works have shown how the reasoning capabilities of Large Language Models
(LLMs) can be applied to domains beyond natural language processing, such as planning …
(LLMs) can be applied to domains beyond natural language processing, such as planning …