7 citations · 30 across the 12 of their papers we have counts for
12 papers
Simulating Complex Multi-Turn Tool Calling Interactions in Stateless Execution Environments
Maxwell Crouse, Ibrahim Abdelaziz, Kshitij Fadnis +6
Synthetic data has proven itself to be a valuable resource for tuning smaller, cost-effective language models to handle the complexities of multi-turn tool calling conversations. W…
RAGAPHENE: A RAG Annotation Platform with Human Enhancements and Edits
Kshitij Fadnis, Sara Rosenthal, Maeda Hanafi +2
Retrieval Augmented Generation (RAG) is an important aspect of conversing with Large Language Models (LLMs) when factually correct information is important. LLMs may provide answer…
MTRAG: A Multi-Turn Conversational Benchmark for Evaluating Retrieval-Augmented Generation Systems
Yannis Katsis, Sara Rosenthal, Kshitij Fadnis +7
Retrieval-augmented generation (RAG) has recently become a very popular task for Large Language Models (LLMs). Evaluating them on multi-turn RAG conversations, where the system is…
InspectorRAGet: An Introspection Platform for RAG Evaluation
Kshitij Fadnis, Siva Sankalp Patel, Odellia Boni +4
Large Language Models (LLM) have become a popular approach for implementing Retrieval Augmented Generation (RAG) systems, and a significant amount of effort has been spent on build…
PrimeQA: The Prime Repository for State-of-the-Art Multilingual Question Answering Research and Development
Avirup Sil, Jaydeep Sen, Bhavani Iyer +12
The field of Question Answering (QA) has made remarkable progress in recent years, thanks to the advent of large pre-trained language models, newer realistic benchmark datasets wit…
Project CLAI: Instrumenting the Command Line as a New Environment for AI Agents
Mayank Agarwal, Jorge J. Barroso, Tathagata Chakraborti +5
This whitepaper reports on Project CLAI (Command Line AI), which aims to bring the power of AI to the command line interface (CLI). The CLAI platform sets up the CLI as a new envir…
Infusing Knowledge into the Textual Entailment Task Using Graph Convolutional Networks
Pavan Kapanipathi, Veronika Thost, Siva Sankalp Patel +10
Textual entailment is a fundamental task in natural language processing. Most approaches for solving the problem use only the textual content present in training data. A few approa…
Path-Based Contextualization of Knowledge Graphs for Textual Entailment
Kshitij Fadnis, Kartik Talamadupula, Pavan Kapanipathi +3
In this paper, we introduce the problem of knowledge graph contextualization -- that is, given a specific NLP task, the problem of extracting meaningful and relevant sub-graphs fro…
Knowledge-incorporating ESIM models for Response Selection in Retrieval-based Dialog Systems
Jatin Ganhotra, Siva Sankalp Patel, Kshitij Fadnis
Goal-oriented dialog systems, which can be trained end-to-end without manually encoding domain-specific features, show tremendous promise in the customer support use-case e.g. flig…
Quantized-Dialog Language Model for Goal-Oriented Conversational Systems
R. Chulaka Gunasekara, David Nahamoo, Lazaros C. Polymenakos +2
We propose a novel methodology to address dialog learning in the context of goal-oriented conversational systems. The key idea is to quantize the dialog space into clusters and cre…
A Unified Implicit Dialog Framework for Conversational Search
Song Feng, R. Chulaka Gunasekara, Sunil Shashidhara +2
We propose a unified Implicit Dialog framework for goal-oriented, information seeking tasks of Conversational Search applications. It aims to enable dialog interactions with domain…
UbuntuWorld 1.0 LTS - A Platform for Automated Problem Solving & Troubleshooting in the Ubuntu OS
Tathagata Chakraborti, Kartik Talamadupula, Kshitij P. Fadnis +2
In this paper, we present UbuntuWorld 1.0 LTS - a platform for developing automated technical support agents in the Ubuntu operating system. Specifically, we propose to use the Bas…