most citedRecRec: Algorithmic Recourse for Recommender Systems

6 citations · 10 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL20242 cited

Do LLMs Exhibit Human-Like Reasoning? Evaluating Theory of Mind in LLMs for Open-Ended Responses

Maryam Amirizaniani, Elias Martin, Maryna Sivachenko +2

Theory of Mind (ToM) reasoning entails recognizing that other individuals possess their own intentions, emotions, and thoughts, which is vital for guiding one's own thought process…

cs.CL20242 cited

TnT-LLM: Text Mining at Scale with Large Language Models

Mengting Wan, Tara Safavi, Sujay Kumar Jauhar +11

Transforming unstructured text into structured and meaningful forms, organized by useful category labels, is a fundamental step in text mining for downstream analysis and applicati…

cs.LG20231 cited

Detecting Spurious Correlations via Robust Visual Concepts in Real and AI-Generated Image Classification

Preetam Prabhu Srikar Dammu, Chirag Shah

Often machine learning models tend to automatically learn associations present in the training data without questioning their validity or appropriateness. This undesirable property…

cs.LG20231 cited

Addressing Weak Decision Boundaries in Image Classification by Leveraging Web Search and Generative Models

Preetam Prabhu Srikar Dammu, Yunhe Feng, Chirag Shah

Machine learning (ML) technologies are known to be riddled with ethical and operational problems, however, we are witnessing an increasing thrust by businesses to deploy them in se…

cs.CL2023

S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs

Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan +5

The traditional Dialogue State Tracking (DST) problem aims to track user preferences and intents in user-agent conversations. While sufficient for task-oriented dialogue systems su…

cs.IR20236 cited

RecRec: Algorithmic Recourse for Recommender Systems

Sahil Verma, Ashudeep Singh, Varich Boonsanong +2

Recommender systems play an essential role in the choices people make in domains such as entertainment, shopping, food, news, employment, and education. The machine learning models…