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Challenges and applications of large language models
Large Language Models (LLMs) went from non-existent to ubiquitous in the machine
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
learning discourse within a few years. Due to the fast pace of the field, it is difficult to identify …
[HTML][HTML] A survey of GPT-3 family large language models including ChatGPT and GPT-4
Large language models (LLMs) are a special class of pretrained language models (PLMs)
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …
obtained by scaling model size, pretraining corpus and computation. LLMs, because of their …
Next-gpt: Any-to-any multimodal llm
While recently Multimodal Large Language Models (MM-LLMs) have made exciting strides,
they mostly fall prey to the limitation of only input-side multimodal understanding, without the …
they mostly fall prey to the limitation of only input-side multimodal understanding, without the …
Multimodal foundation models: From specialists to general-purpose assistants
Neural compression is the application of neural networks and other machine learning
methods to data compression. Recent advances in statistical machine learning have opened …
methods to data compression. Recent advances in statistical machine learning have opened …
Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion
Recent text-to-image diffusion models have demonstrated an astonishing capacity to
generate high-quality images. However, researchers mainly studied the way of synthesizing …
generate high-quality images. However, researchers mainly studied the way of synthesizing …
Mastering text-to-image diffusion: Recaptioning, planning, and generating with multimodal llms
Diffusion models have exhibit exceptional performance in text-to-image generation and
editing. However, existing methods often face challenges when handling complex text …
editing. However, existing methods often face challenges when handling complex text …
Instancediffusion: Instance-level control for image generation
Text-to-image diffusion models produce high quality images but do not offer control over
individual instances in the image. We introduce InstanceDiffusion that adds precise instance …
individual instances in the image. We introduce InstanceDiffusion that adds precise instance …
Grounded text-to-image synthesis with attention refocusing
Driven by the scalable diffusion models trained on large-scale datasets text-to-image
synthesis methods have shown compelling results. However these models still fail to …
synthesis methods have shown compelling results. However these models still fail to …
Llmscore: Unveiling the power of large language models in text-to-image synthesis evaluation
Existing automatic evaluation on text-to-image synthesis can only provide an image-text
matching score, without considering the object-level compositionality, which results in poor …
matching score, without considering the object-level compositionality, which results in poor …
Guiding instruction-based image editing via multimodal large language models
Instruction-based image editing improves the controllability and flexibility of image
manipulation via natural commands without elaborate descriptions or regional masks …
manipulation via natural commands without elaborate descriptions or regional masks …