4 citations · 7 across the 9 of their papers we have counts for
9 papers
Learning to Detect UI Principle Violations via Reinforcement Learning
Nishi Mehta, Swathi Alse, Himani Kumawat +2
Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional correctness. A generated interf…
Translate-R1: Cost-Aware Translation Tool Use via Reinforcement Learning
Pratik Jayarao, Chaitanya Dwivedi, Himanshu Gupta +5
The performance gap across languages in LLMs is well documented, and closing it natively requires pretraining or fine-tuning on corpora that, for most languages, are quite limited.…
Expert Upcycling: Shifting the Compute-Efficient Frontier of Mixture-of-Experts
Chaitanya Dwivedi, Binxuan Huang, Himanshu Gupta +3
Mixture-of-Experts (MoE) has become the dominant architecture for scaling large language models: frontier models routinely decouple total parameters from per-token computation thro…
Code Mixologist : A Practitioner's Guide to Building Code-Mixed LLMs
Himanshu Gupta, Pratik Jayarao, Chaitanya Dwivedi +1
Code-mixing and code-switching (CSW) remain challenging phenomena for large language models (LLMs). Despite recent advances in multilingual modeling, LLMs often struggle in mixed-l…
Explicit Reasoning Makes Better Judges: A Systematic Study on Accuracy, Efficiency, and Robustness
Pratik Jayarao, Himanshu Gupta, Neeraj Varshney +1
As Large Language Models (LLMs) are increasingly adopted as automated judges in benchmarking and reward modeling, ensuring their reliability, efficiency, and robustness has become…
Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models
Yilun Jin, Zheng Li, Chenwei Zhang +19
Online shopping is a complex multi-task, few-shot learning problem with a wide and evolving range of entities, relations, and tasks. However, existing models and benchmarks are com…
Retraining DistilBERT for a Voice Shopping Assistant by Using Universal Dependencies
Pratik Jayarao, Arpit Sharma
In this work, we retrained the distilled BERT language model for Walmart's voice shopping assistant on retail domain-specific data. We also injected universal syntactic dependencie…
Intent Detection for code-mix utterances in task oriented dialogue systems
Pratik Jayarao, Aman Srivastava
Intent detection is an essential component of task oriented dialogue systems. Over the years, extensive research has been conducted resulting in many state of the art models direct…
Exploring the importance of context and embeddings in neural NER models for task-oriented dialogue systems
Pratik Jayarao, Chirag Jain, Aman Srivastava
Named Entity Recognition (NER), a classic sequence labelling task, is an essential component of natural language understanding (NLU) systems in task-oriented dialog systems for slo…