Bats Research
We are a machine learning research group at Brown University. We work on improving the processes by which humans teach and instruct computers.
United States of America
Pinned Repositories
alfred
A system for prompted weak supervision.
bonito
A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.
csp
Learning to compose soft prompts for compositional zero-shot learning.
labelmodels
Lightweight implementations of generative label models for weakly supervised machine learning
menghini-neurips23-code
Exploring prompt tuning with pseudolabels for multiple modalities, learning settings, and training strategies.
nplm
A weak supervision framework for (partial) labeling functions
safranchik-aaai20-code
taglets
wiser
Framework for weakly supervised deep sequence taggers, focused on named entity recognition
zsl-kg
Framework for zero-shot learning with knowledge graphs.
Bats Research's Repositories
BatsResearch/bonito
A lightweight library for generating synthetic instruction tuning datasets for your data without GPT.
BatsResearch/zsl-kg
Framework for zero-shot learning with knowledge graphs.
BatsResearch/wiser
Framework for weakly supervised deep sequence taggers, focused on named entity recognition
BatsResearch/csp
Learning to compose soft prompts for compositional zero-shot learning.
BatsResearch/alfred
A system for prompted weak supervision.
BatsResearch/menghini-neurips23-code
Exploring prompt tuning with pseudolabels for multiple modalities, learning settings, and training strategies.
BatsResearch/taglets
BatsResearch/safranchik-aaai20-code
BatsResearch/labelmodels
Lightweight implementations of generative label models for weakly supervised machine learning
BatsResearch/nayak-arxiv24-code
BatsResearch/nplm
A weak supervision framework for (partial) labeling functions
BatsResearch/efsl
Extended Few-Shot Learning: Exploiting Existing Resources for Novel Tasks
BatsResearch/ex2
If CLIP Could Talk: Understanding Vision-Language Model Representations Through Their Preferred Concept Descriptions
BatsResearch/LexC-Gen
Generate synthetic labeled data for extremely low-resource languages using bilingual lexicons.
BatsResearch/nayak-tmlr22-code
BatsResearch/fudd
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
BatsResearch/yu-aistats22-code
BatsResearch/amcl
Adversarial Multi Class Labeling
BatsResearch/piriyakulkij-mlsys22-code
BatsResearch/mazzetto-aistats21-code
BatsResearch/mazzetto-neurips22-code
BatsResearch/su-bigdata23-code
Code Repository for IEEE BigData 23 Paper "Leveraging Large Language Models for Structure Learning in Prompted Weak Supervision"
BatsResearch/clipseg
This repository contains the code of the CVPR 2022 paper "Image Segmentation Using Text and Image Prompts".
BatsResearch/LexC-Gen-Data-Archive
Data Repository for LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons
BatsResearch/mazzetto-arxiv23-code
An Adaptive Method for Weak Supervision with Drifting Data
BatsResearch/mazzetto-icml21-code