Customer-obsessed science
-
September 30, 2024From pricing estimation and regulatory compliance to inventory management and chatbot assistants, machine learning models help Amazon Pharmacy customers stay healthy and save time and money.
-
September 19, 2024“Agentic workflows” that use multiple, fine-tuned smaller LLMs — rather than one large one — can improve efficiency.
-
September 16, 2024A position paper presented at ACL proposes a framework for more-accurate human evaluation of LLMs.
-
-
September 29 - October 4, 2024
-
October 21 - 25, 2024
-
September 25, 2024
Now open until November 6, Amazon Research Awards will be seeking proposals in the following research areas: AI for Information Security, Automated Reasoning, AWS AI, AWS Cryptography, and Sustainability.
-
EMNLP 20232023As large language models (LLMs) have shown effectiveness with different prompting methods, such as Chain of Thought, Program of Thought, we find that these methods have formed a great complementarity to each other on math reasoning tasks. In this work, we propose XoT, an integrated problem solving framework by prompting LLMs with diverse reasoning thoughts. For each question, XoT always begins with selecting
-
EMNLP 20232023Text classifiers are an indispensable tool for machine learning practitioners, but adapting them to new classes is expensive. To reduce the cost of new classes, previous work exploits class descriptions and/or labels from existing classes. However, these approaches leave a gap in the model development cycle as they support either zero- or few-shot learning but not both. Existing classifiers either do not
-
EMNLP 20232023Conventional speech-to-text translation (ST) systems are trained on single-speaker utterances, and they may not generalize to real-life scenarios where the audio contains conversations by multiple speakers. In this paper, we tackle single-channel multi-speaker conversational ST with an end-to-end and multi-task training model, named Speaker-Turn Aware Conversational Speech Translation, that combines automatic
-
EMNLP 20232023Readability refers to how easily a reader can understand a written text. Several factors affect the readability level, such as the complexity of the text, its subject matter, and the reader’s background knowledge. Generating summaries based on different readability levels is critical for enabling knowledge consumption by diverse audiences. However, current text generation approaches lack refined control
-
EMNLP 20232023Real-time semantic matching is vital to web and product search. Transformer-based models have shown to be highly effective at encoding queries into an embedding space where semantically similar entities (queries or results) are in close proximity. However, the computational complexity of large transformer models limits their utilization for real-time matching. In this paper, we propose KD-Boost, a novel
Resources
-
We look for talent from around the world for applied scientists, data scientists, economists, research scientists, scholars, academics, PhDs, and interns.
-
We collaborate with leading academic organizations to drive innovation and to ensure that research is creating solutions whose benefits are shared broadly.
-
Learn more about the awards and recognitions that Amazon researches from around the world have been honored with during their tenure.