Buzzards Bay: Transitioning to Continuous Water Quality Monitoring
This project aims to study the transition from traditional "grab sample" water quality monitoring to continuous, sensor-based monitoring in Buzzards Bay, Massachusetts.
Foxbounder App
Use a computer-vision algorithm to automatically detect whether or not a photograph contains an animal for The Nature Conservancy to use with trail-cam footage.
International Phonetic Alphabet Transcription
Fine tune a speech recognition model to use the international phonetic alphabet.
EagleCam
Improve a video analysis model for identifying the type of food (rodent, lizard, fish) that an eagle is bringing to its nest for the U.S. Fish and Wildlife Services.
Entities in Context
Entities in ContextPartner: Meta Platforms Inc.Participants: Saeed Goodarzi, Nikhil Kagita, Dennis MinnDescription: We revisited the generalization effectiveness of LLMs by focusing on named entities. Named entities are ubiquitous in current Natural Language Understanding benchmarks, yet they have been largely ignored in order to examine the impact on models' reasoning capabilities. We subjected models to the same evaluation data while modifying them to iterate through a large array of named entities from diverse demographics.
Simple Strategies to Select Layers for Fine-Tuning Language Encoders
Simple Strategies to Select Layers for Fine-Tuning Language Encoders Partner: Microsoft, MAIDAP Participants: Gayatri Belapurkar, Saloni Chalkapurkar, Abhilasha Lodha, Yuanming Tao Description: We proposed two-layer selection methods for fine-tuning language encoders that can comprehensively make the transfer learning process for common NLP tasks such as GLUE and SuperGLUE more resource efficient.