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Found 5 papers, 0 papers with code
Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
We introduce phi-3-mini, a 3. 8 billion parameter language model trained on 3. 3 trillion tokens, whose overall performance, as measured by both academic benchmarks and internal testing, rivals that of models such as Mixtral 8x7B and GPT-3. 5 (e. g., phi-3-mini achieves 69% on MMLU and 8. 38 on MT-bench), despite being small enough to be deployed on a phone.
Ranked #5 on
MMR total
on MRR-Benchmark
(using extra training data)
Personalized Face Inpainting with Diffusion Models by Parallel Visual Attention
Specifically, we insert parallel attention matrices to each cross-attention module in the denoising network, which attends to features extracted from reference images by an identity encoder.
Language Models Get a Gender Makeover: Mitigating Gender Bias with Few-Shot Data Interventions
Since large-scale retraining of these models from scratch is both time and compute-expensive, a variety of approaches have been previously proposed that de-bias a pre-trained model.
Self-supervised Multi-view Disentanglement for Expansion of Visual Collections
In this work, we consider the setting where a query for similar images is derived from a collection of images.
Generating Compositional Color Representations from Text
While this dataset is specialized for our investigations on color, the method can be extended to other visual dimensions where composition is of interest.
