Trending Research
Monolith: Real Time Recommendation System With Collisionless Embedding Table
In this paper, we present Monolith, a system tailored for online training.
Automating the Search for Artificial Life with Foundation Models
sakanaai/asal
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With the recent Nobel Prize awarded for radical advances in protein discovery, foundation models (FMs) for exploring large combinatorial spaces promise to revolutionize many scientific fields.
Arbitrary-steps Image Super-resolution via Diffusion Inversion
zsyoaoa/invsr
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This study presents a new image super-resolution (SR) technique based on diffusion inversion, aiming at harnessing the rich image priors encapsulated in large pre-trained diffusion models to improve SR performance.
CLEAR: Conv-Like Linearization Revs Pre-Trained Diffusion Transformers Up
huage001/clear
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Diffusion Transformers (DiT) have become a leading architecture in image generation.
Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference
Encoder-only transformer models such as BERT offer a great performance-size tradeoff for retrieval and classification tasks with respect to larger decoder-only models.
Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
However, the widely adopted uniform point sampling strategy in Shape VAE training often leads to a significant loss of geometric details, limiting the quality of shape reconstruction and downstream generation tasks.
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
lihxxx/dispose
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Specifically, we generate a dense motion field from a sparse motion field and the reference image, which provides region-level dense guidance while maintaining the generalization of the sparse pose control.
Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces
vision-x-nyu/thinking-in-space
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Humans possess the visual-spatial intelligence to remember spaces from sequential visual observations.
Large Concept Models: Language Modeling in a Sentence Representation Space
facebookresearch/large_concept_model
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In this paper, we present an attempt at an architecture which operates on an explicit higher-level semantic representation, which we name a concept.
On the Measure of Intelligence
To make deliberate progress towards more intelligent and more human-like artificial systems, we need to be following an appropriate feedback signal: we need to be able to define and evaluate intelligence in a way that enables comparisons between two systems, as well as comparisons with humans.
