most citedThe Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

11 citations · 19 across the 11 of their papers we have counts for

collaborators

11 papers

cs.CL20232 cited

Are Personalized Stochastic Parrots More Dangerous? Evaluating Persona Biases in Dialogue Systems

Yixin Wan, Jieyu Zhao, Aman Chadha +2

Recent advancements in Large Language Models empower them to follow freeform instructions, including imitating generic or specific demographic personas in conversations. We define…

cs.CL2023

Counter Turing Test CT^2: AI-Generated Text Detection is Not as Easy as You May Think -- Introducing AI Detectability Index

Megha Chakraborty, S. M Towhidul Islam Tonmoy, S M Mehedi Zaman +9

With the rise of prolific ChatGPT, the risk and consequences of AI-generated text has increased alarmingly. To address the inevitable question of ownership attribution for AI-gener…

cs.AI202311 cited

The Troubling Emergence of Hallucination in Large Language Models -- An Extensive Definition, Quantification, and Prescriptive Remediations

Vipula Rawte, Swagata Chakraborty, Agnibh Pathak +5

The recent advancements in Large Language Models (LLMs) have garnered widespread acclaim for their remarkable emerging capabilities. However, the issue of hallucination has paralle…

cs.CL2023

CONFLATOR: Incorporating Switching Point based Rotatory Positional Encodings for Code-Mixed Language Modeling

Mohsin Ali, Kandukuri Sai Teja, Neeharika Gupta +5

The mixing of two or more languages is called Code-Mixing (CM). CM is a social norm in multilingual societies. Neural Language Models (NLMs) like transformers have been effective o…

cs.CL20233 cited

Overview of Memotion 3: Sentiment and Emotion Analysis of Codemixed Hinglish Memes

Shreyash Mishra, S Suryavardan, Megha Chakraborty +9

Analyzing memes on the internet has emerged as a crucial endeavor due to the impact this multi-modal form of content wields in shaping online discourse. Memes have become a powerfu…

cs.LG2023

RESTORE: Graph Embedding Assessment Through Reconstruction

Hong Yung Yip, Chidaksh Ravuru, Neelabha Banerjee +4

Following the success of Word2Vec embeddings, graph embeddings (GEs) have gained substantial traction. GEs are commonly generated and evaluated extrinsically on downstream applicat…