6 papers
CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data
Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94
Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…
Do Image-Text Metrics Respect Semantic Invariances?
Amit Agarwal, Hitesh Laxmichand Patel, Meizhu Liu +9
Reference-free image-to-text evaluators are now standard for scoring image-caption alignment, yet it is unclear whether they respect semantic invariances. We present an invariance…
FlexDoc: Parameterized Sampling for Diverse Multilingual Synthetic Documents for Training Document Understanding Models
Karan Dua, Hitesh Laxmichand Patel, Puneet Mittal +7
Developing document understanding models at enterprise scale requires large, diverse, and well-annotated datasets spanning a wide range of document types. However, collecting such…
SpeechWeave: Diverse Multilingual Synthetic Text & Audio Data Generation Pipeline for Training Text to Speech Models
Karan Dua, Puneet Mittal, Ranjeet Gupta +1
High-quality Text-to-Speech (TTS) model training requires extensive and diverse text and speech data. It is challenging to procure such data from real sources due to issues of doma…
PCRI: Measuring Context Robustness in Multimodal Models for Enterprise Applications
Hitesh Laxmichand Patel, Amit Agarwal, Srikant Panda +6
The reliability of Multimodal Large Language Models (MLLMs) in real-world settings is often undermined by sensitivity to irrelevant or distracting visual context, an aspect not cap…
RCI: A Score for Evaluating Global and Local Reasoning in Multimodal Benchmarks
Amit Agarwal, Hitesh Laxmichand Patel, Srikant Panda +7
Multimodal Large Language Models (MLLMs) have achieved impressive results on vision-language benchmarks, yet it remains unclear whether these benchmarks assess genuine global reaso…