2 citations · 8 across the 11 of their papers we have counts for
11 papers
Counterfactual Fairness Evaluation of LLM-Based Contact Center Agent Quality Assurance System
Kawin Mayilvaghanan, Siddhant Gupta, Ayush Kumar
Large Language Models (LLMs) are increasingly deployed in contact-center Quality Assurance (QA) to automate agent performance evaluation and coaching feedback. While LLMs offer unp…
Tool-Aware Planning in Contact Center AI: Evaluating LLMs through Lineage-Guided Query Decomposition
Varun Nathan, Shreyas Guha, Ayush Kumar
We present a domain-grounded framework and benchmark for tool-aware plan generation in contact centers, where answering a query for business insights, our target use case, requires…
Spot the BlindSpots: Systematic Identification and Quantification of Fine-Grained LLM Biases in Contact Center Summaries
Kawin Mayilvaghanan, Siddhant Gupta, Ayush Kumar
Abstractive summarization is a core application in contact centers, where Large Language Models (LLMs) generate millions of summaries of call transcripts daily. Despite their appar…
Why Synthetic Isn't Real Yet: A Diagnostic Framework for Contact Center Dialogue Generation
Rishikesh Devanathan, Varun Nathan, Ayush Kumar
Synthetic data is increasingly critical for contact centers, where privacy constraints and data scarcity limit the availability of real conversations. However, generating synthetic…
Towards Probing Contact Center Large Language Models
Varun Nathan, Ayush Kumar, Digvijay Ingle +1
Fine-tuning large language models (LLMs) with domain-specific instructions has emerged as an effective method to enhance their domain-specific understanding. Yet, there is limited…
Exploring the Limits of Natural Language Inference Based Setup for Few-Shot Intent Detection
Ayush Kumar, Vijit Malik, Jithendra Vepa
Intent Detection is one of the core tasks of dialog systems. Few-shot Intent Detection is challenging due to limited number of annotated utterances for novel classes. Generalized F…