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20242026
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cs.CL2026

Findings of the Counter Turing Test: AI-Generated Text Detection

Rajarshi Roy, Gurpreet Singh, Ashhar Aziz +16

The growing capability of large language models to produce fluent, contextually coherent text has created mounting pressure on the systems and institutions responsible for ensuring…

cs.CL2026

A Comprehensive Dataset for Human vs. AI Generated Text Detection

Rajarshi Roy, Gurpreet Singh, Ashhar Aziz +17

The rapid advancement of large language models (LLMs) has led to increasingly human-like AI-generated text, raising concerns about content authenticity, misinformation, and trustwo…

cs.CL2025

RADIANT: Retrieval AugmenteD entIty-context AligNmenT -- Introducing RAG-ability and Entity-Context Divergence

Vipula Rawte, Rajarshi Roy, Gurpreet Singh +11

As Large Language Models (LLMs) continue to advance, Retrieval-Augmented Generation (RAG) has emerged as a vital technique to enhance factual accuracy by integrating external knowl…

cs.CL2025

SEPSIS: I Can Catch Your Lies -- A New Paradigm for Deception Detection

Anku Rani, Dwip Dalal, Shreya Gautam +5

Deception is the intentional practice of twisting information. It is a nuanced societal practice deeply intertwined with human societal evolution, characterized by a multitude of f…

cs.CL2024

KnowledgePrompts: Exploring the Abilities of Large Language Models to Solve Proportional Analogies via Knowledge-Enhanced Prompting

Thilini Wijesiriwardene, Ruwan Wickramarachchi, Sreeram Vennam +5

Making analogies is fundamental to cognition. Proportional analogies, which consist of four terms, are often used to assess linguistic and cognitive abilities. For instance, comple…

cs.CL2024

Counter Turing Test (): Investigating AI-Generated Text Detection for Hindi -- Ranking LLMs based on Hindi AI Detectability Index ()

Ishan Kavathekar, Anku Rani, Ashmit Chamoli +3

The widespread adoption of Large Language Models (LLMs) and awareness around multilingual LLMs have raised concerns regarding the potential risks and repercussions linked to the mi…