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20182026
most citedShopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models

2 citations · 3 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CL2026

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…

cs.CL2026

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.…

cs.CL2026

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…

cs.CL2018

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…

cs.CL2018

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…