6 papers
TH-GNN: Heterogeneous Temporal Graph Neural Networks for LLM-Agent Shilling Attack Detection
Shivam Swarup, Divya Prakash Shrivastava, Rakesh Thakur
LLM agents can now generate realistic shilling profiles, fluent reviews, and coherent ratings at scale, systematically defeating recommender-system defenses. Text-only detectors th…
Quantum-RAG and PunGPT2: Advancing Low-Resource Language Generation and Retrieval for the Punjabi Language
Jaskaranjeet Singh, Rakesh Thakur
Despite rapid advances in large language models (LLMs), low-resource languages remain excluded from NLP, limiting digital access for millions. We present PunGPT2, the first fully o…
NEURODNAAI: Neural pipeline approaches for the advancing dna-based information storage as a sustainable digital medium using deep learning framework
Rakesh Thakur, Lavanya Singh, Yashika +2
DNA is a promising medium for digital information storage for its exceptional density and durability. While prior studies advanced coding theory, workflow design, and simulation to…
Capturing Opinion Shifts in Deliberative Discourse through Frequency-based Quantum deep learning methods
Rakesh Thakur, Harsh Chaturvedi, Ruqayya Shah +2
Deliberation plays a crucial role in shaping outcomes by weighing diverse perspectives before reaching decisions. With recent advancements in Natural Language Processing, it has be…
TrueGradeAI: Retrieval-Augmented and Bias-Resistant AI for Transparent and Explainable Digital Assessments
Rakesh Thakur, Shivaansh Kaushik, Gauri Chopra +1
This paper introduces TrueGradeAI, an AI-driven digital examination framework designed to overcome the shortcomings of traditional paper-based assessments, including excessive pape…
HiFACTMix: A Code-Mixed Benchmark and Graph-Aware Model for EvidenceBased Political Claim Verification in Hinglish
Rakesh Thakur, Sneha Sharma, Gauri Chopra
Fact-checking in code-mixed, low-resource languages such as Hinglish remains an underexplored challenge in natural language processing. Existing fact-verification systems largely f…