activity
20232026
most citedMEGAnno+: A Human-LLM Collaborative Annotation System

4 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Blue Data Intelligence Layer: Streaming Data and Agents for Multi-source Multi-modal Data-Centric Applications

Moin Aminnaseri, Farima Fatahi Bayat, Nikita Bhutani +17

NL2SQL systems aim to address the growing need for natural language interaction with data. However, real-world information rarely maps to a single SQL query because (1) users expre…

cs.AI2025

Orchestrating Agents and Data for Enterprise: A Blueprint Architecture for Compound AI

Eser Kandogan, Nikita Bhutani, Dan Zhang +3

Large language models (LLMs) have gained significant interest in industry due to their impressive capabilities across a wide range of tasks. However, the widespread adoption of LLM…

cs.DB2024★ 1 cited

A Blueprint Architecture of Compound AI Systems for Enterprise

Eser Kandogan, Sajjadur Rahman, Nikita Bhutani +11

Large Language Models (LLMs) have showcased remarkable capabilities surpassing conventional NLP challenges, creating opportunities for use in production use cases. Towards this goa…

cs.CL2024★ 4 cited

MEGAnno+: A Human-LLM Collaborative Annotation System

Hannah Kim, Kushan Mitra, Rafael Li Chen +2

Large language models (LLMs) can label data faster and cheaper than humans for various NLP tasks. Despite their prowess, LLMs may fall short in understanding of complex, sociocultu…

cs.HC2023★ 2 cited

MEGAnno: Exploratory Labeling for NLP in Computational Notebooks

Dan Zhang, Hannah Kim, Rafael Li Chen +2

We present MEGAnno, a novel exploratory annotation framework designed for NLP researchers and practitioners. Unlike existing labeling tools that focus on data labeling only, our fr…