2 citations · 4 across the 17 of their papers we have counts for
15 papers · 1 filter
Aligning LLMs for Multilingual Consistency in Enterprise Applications
Amit Agarwal, Hansa Meghwani, Hitesh Laxmichand Patel +3
Large language models (LLMs) remain unreliable for global enterprise applications due to substantial performance gaps between high-resource and mid/low-resource languages, driven b…
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…
Pushing on Multilingual Reasoning Models with Language-Mixed Chain-of-Thought
Guijin Son, Donghun Yang, Hitesh Laxmichand Patel +9
Recent frontier models employ long chain-of-thought reasoning to explore solution spaces in context and achieve stonger performance. While many works study distillation to build sm…
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…
AccessEval: Benchmarking Disability Bias in Large Language Models
Srikant Panda, Amit Agarwal, Hitesh Laxmichand Patel
Large Language Models (LLMs) are increasingly deployed across diverse domains but often exhibit disparities in how they handle real-life queries. To systematically investigate thes…