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.
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- United States of America
- http://cs.brown.edu/people/sbach/
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- menghini-neurips23-code Public
Exploring prompt tuning with pseudolabels for multiple modalities, learning settings, and training strategies.
BatsResearch/menghini-neurips23-code’s past year of commit activity - planetarium Public
Dataset and benchmark for assessing LLMs in translating natural language descriptions of planning problems into PDDL
BatsResearch/planetarium’s past year of commit activity - cross-lingual-detox Public
Code for "Preference Tuning For Toxicity Mitigation Generalizes Across Languages." Paper accepted at Findings of EMNLP 2024
BatsResearch/cross-lingual-detox’s past year of commit activity - LexC-Gen-Data-Archive Public
Data Repository for LexC-Gen: Generating Data for Extremely Low-Resource Languages with Large Language Models and Bilingual Lexicons
BatsResearch/LexC-Gen-Data-Archive’s past year of commit activity - nayak-aclfindings24-code Public
BatsResearch/nayak-aclfindings24-code’s past year of commit activity - labelmodels Public
Lightweight implementations of generative label models for weakly supervised machine learning
BatsResearch/labelmodels’s past year of commit activity