Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP
Large pretrained vision-language models like CLIP have shown promising generalization capability, but may struggle in specialized domains (e.g., satellite imagery) or fine-grained classification...
Empirical Methods in Natural Language Processing (EMNLP) 2024
Empirical Methods in Natural Language Processing (EMNLP) 2024
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Computational Bottlenecks of Training Small-Scale Large Language Models
This paper was accepted at the Efficient Natural Language and Speech Processing (ENLSP) workshop at NeurIPS Workshop 2024.
While large language models (LLMs) dominate...
On Device Llama 3.1 with Core ML
Many app developers are interested in building on device experiences that integrate increasingly capable large language models (LLMs). Running these models locally on...
Towards Cross-Cultural Machine Translation with Retrieval-Augmented Generation from Multilingual Knowledge Graphs
Translating text that contains entity names is a challenging task, as cultural-related references can vary significantly across languages. These variations may also be...
Promoting Cross-Modal Representations to Improve Multimodal Foundation Models for Physiological Signals
Many healthcare applications are inherently multimodal, involving several physiological signals. As sensors for these signals become more common, improving machine learning methods for...
Smart Audit System Empowered by LLM
Manufacturing quality audits are pivotal for ensuring high product standards in mass production environments. Traditional auditing processes, however, are labor-intensive and heavily reliant...
Divide-or-Conquer? Which Part Should You Distill Your LLM?
Recent methods have demonstrated that Large Language Models (LLMs) can solve reasoning tasks better when they are encouraged to solve subtasks of the...
Combining Machine Learning and Homomorphic Encryption in the Apple Ecosystem
At Apple, we believe privacy is a fundamental human right. Our work to protect user privacy is informed by a set of privacy...
Towards Data-Centric RLHF: Simple Metrics for Preference Dataset Comparison
The goal of aligning language models to human preferences requires data that reveal these preferences. Ideally, time and money can be spent carefully...
