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Federated Learning for Speech Recognition: Revisiting Current Trends Towards Large-Scale ASR

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This paper was accepted at the Federated Learning in the Age of Foundation Models workshop at NeurIPS 2023. While automatic speech recognition (ASR) has...
Apple

Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration

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A recent line of work shows that notions of multigroup fairness imply surprisingly strong notions of omniprediction: loss minimization guarantees that apply not...
Apple

What Algorithms can Transformers Learn? A Study in Length Generalization

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This paper was accepted at the MATH workshop at NeurIPS 2023. Large language models exhibit surprising emergent generalization properties, yet also struggle on many...
Apple

SAM-CLIP: Merging Vision Foundation Models towards Semantic and Spatial Understanding

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This paper was accepted at the UniReps Workshop at NeurIPS 2023. The landscape of publicly available vision foundation models (VFMs), such as CLIP and...
Apple

Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs

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Recent work in Natural Language Processing and Computer Vision has been using textual information – e.g., entity names and descriptions – available in...
Apple

Empirical Methods in Natural Language Processing (EMNLP) 2023

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Apple is sponsoring the Empirical Methods in Natural Language Processing (EMNLP) conference, which will take place in person from December 6 to 10...
Apple

ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models

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Large Language Models (LLMs) with billions of parameters have drastically transformed AI applications. However, their demanding computation during inference has raised significant challenges...
Apple

Automating Behavioral Testing in Machine Translation

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Behavioral testing in NLP allows fine-grained evaluation of systems by examining their linguistic capabilities through the analysis of input-output behavior. Unfortunately, existing work...
Apple

How to Scale Your EMA

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*=Equal Contributors Preserving training dynamics across batch sizes is an important tool for practical machine learning as it enables the trade-off between batch size...
Apple

Diffusion Models as Masked Audio-Video Learners

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This paper was accepted at the Machine Learning for Audio Workshop at NeurIPS 2023. Over the past several years, the synchronization between audio and...
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