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Found 6 papers, 1 papers with code
A Unified Framework and Dataset for Assessing Gender Bias in Vision-Language Models
Large vision-language models (VLMs) are widely getting adopted in industry and academia.
MAFIA: Multi-Adapter Fused Inclusive LanguAge Models
In this work, we aim to modularly debias a pretrained language model across multiple dimensions.
MAPLE: Multilingual Evaluation of Parameter Efficient Finetuning of Large Language Models
Prior work on multilingual evaluation has shown that there is a large gap between the performance of LLMs on English and other languages.
MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and Tasks
We also perform a study on data contamination and find that several models are likely to be contaminated with multilingual evaluation benchmarks, necessitating approaches to detect and handle contamination while assessing the multilingual performance of LLMs.
Benchmarking and Improving Text-to-SQL Generation under Ambiguity
Research in Text-to-SQL conversion has been largely benchmarked against datasets where each text query corresponds to one correct SQL.
Diverse Parallel Data Synthesis for Cross-Database Adaptation of Text-to-SQL Parsers
Text-to-SQL parsers typically struggle with databases unseen during the train time.
