Search Results for author: Alexandre Rame

Found 8 papers, 4 papers with code

Direct Language Model Alignment from Online AI Feedback

no code implementations7 Feb 2024 Shangmin Guo, Biao Zhang, Tianlin Liu, Tianqi Liu, Misha Khalman, Felipe Llinares, Alexandre Rame, Thomas Mesnard, Yao Zhao, Bilal Piot, Johan Ferret, Mathieu Blondel

Moreover, responses in these datasets are often sampled from a language model distinct from the one being aligned, and since the model evolves over training, the alignment phase is inevitably off-policy.

Language Modelling

Beyond Task Performance: Evaluating and Reducing the Flaws of Large Multimodal Models with In-Context Learning

1 code implementation1 Oct 2023 Mustafa Shukor, Alexandre Rame, Corentin Dancette, Matthieu Cord

Based on our ICL study, (3) we push ICL further and propose new multimodal ICL variants such as; Multitask-ICL, Chain-of-Hindsight-ICL, and Self-Correcting-ICL.

In-Context Learning Instruction Following +1

UnIVAL: Unified Model for Image, Video, Audio and Language Tasks

1 code implementation30 Jul 2023 Mustafa Shukor, Corentin Dancette, Alexandre Rame, Matthieu Cord

Our model is efficiently pretrained on many tasks, based on task balancing and multimodal curriculum learning.

Out-of-Distribution Generalization

Fishr: Invariant Gradient Variances for Out-of-Distribution Generalization

2 code implementations7 Sep 2021 Alexandre Rame, Corentin Dancette, Matthieu Cord

In this paper, we introduce a new regularization - named Fishr - that enforces domain invariance in the space of the gradients of the loss: specifically, the domain-level variances of gradients are matched across training domains.

Domain Generalization Out-of-Distribution Generalization

CoRe: Color Regression for Multicolor Fashion Garments

no code implementations6 Oct 2020 Alexandre Rame, Arthur Douillard, Charles Ollion

That's why in addition to a first color classifier, we include a second regression stage for refinement in our newly proposed architecture.

regression

OMNIA Faster R-CNN: Detection in the wild through dataset merging and soft distillation

no code implementations6 Dec 2018 Alexandre Rame, Emilien Garreau, Hedi Ben-Younes, Charles Ollion

Similarly to self-training methods, the predictions of these initial detectors mitigate the missing annotations on the complementary datasets.

Domain Adaptation object-detection +2

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