← Search

Sujay Kumar Jauhar

7 accepted papers

2026

Actions Speak Louder than Prompts: A Large-Scale Study of LLMs for Graph Inference

ICLR 2026oral

Large language models (LLMs) are increasingly leveraged for text-rich graph machine learning tasks, with node classification standing out due to its high-impact application domains such as fraud detection and recommendation systems. Yet, despite a surge of interest, the field lacks a principled und…

Cited by 0SourceScholar
2025

ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models

NAACL 2025long

The pace of scientific research, vital for improving human life, is complex, slow, and needs specialized expertise. Meanwhile, novel, impactful research often stems from both a deep understanding of prior work, and a cross-pollination of ideas across domains and fields. To enhance the productivity o…

2024

Interpretable User Satisfaction Estimation for Conversational Systems with Large Language Models

ACL 2024long

Accurate and interpretable user satisfaction estimation (USE) is critical for understanding, evaluating, and continuously improving conversational systems. Users express their satisfaction or dissatisfaction with diverse conversational patterns in both general-purpose (ChatGPT and Bing Copilot) and…

2024

Knowledge-Centric Templatic Views of Documents

EMNLP 2024finding

Authors seeking to communicate with broader audiences often share their ideas in various document formats, such as slide decks, newsletters, reports, and posters. Prior work on document generation has generally tackled the creation of each separate format to be a different task, leading to fragmente…

Cited by 2SourcePDFScholar
2023

Making Large Language Models Better Data Creators

EMNLP 2023long main

Although large language models (LLMs) have advanced the state-of-the-art in NLP significantly, deploying them for downstream applications is still challenging due to cost, responsiveness, control, or concerns around privacy and security. As such, trainable models are still the preferred option in so…

Cited by 0SourcecodeScholar
2022

LITE: Intent-based Task Representation Learning Using Weak Supervision

NAACL 2022long

Users write to-dos as personal notes to themselves, about things they need to complete, remember or organize. To-do texts are usually short and under-specified, which poses a challenge for current text representation models. Yet, understanding and representing their meaning is the first step towards…

2021

Learning to Decompose and Organize Complex Tasks

NAACL 2021long

People rely on digital task management tools, such as email or to-do apps, to manage their tasks. Some of these tasks are large and complex, leading to action paralysis and feelings of being overwhelmed on the part of the user. The micro-productivity literature has shown that such tasks could benefi…