4 citations · 5 across the 16 of their papers we have counts for
5 papers · 1 filter
The Power of Many: Multi-Agent Multimodal Models for Cultural Image Captioning
Longju Bai, Angana Borah, Oana Ignat +1
Large Multimodal Models (LMMs) exhibit impressive performance across various multimodal tasks. However, their effectiveness in cross-cultural contexts remains limited due to the pr…
Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone
Rada Mihalcea, Oana Ignat, Longju Bai +7
This paper presents a vision for creating AI systems that are inclusive at every stage of development, from data collection to model design and evaluation. We address key limitatio…
Towards Implicit Bias Detection and Mitigation in Multi-Agent LLM Interactions
Angana Borah, Rada Mihalcea
As Large Language Models (LLMs) continue to evolve, they are increasingly being employed in numerous studies to simulate societies and execute diverse social tasks. However, LLMs a…
Application Specific Compression of Deep Learning Models
Rohit Raj Rai, Angana Borah, Amit Awekar
Large Deep Learning models are compressed and deployed for specific applications. However, current Deep Learning model compression methods do not utilize the information about the…
Towards Region-aware Bias Evaluation Metrics
Angana Borah, Aparna Garimella, Rada Mihalcea
When exposed to human-generated data, language models are known to learn and amplify societal biases. While previous works introduced benchmarks that can be used to assess the bias…