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cs.CL2025

Robust and Fine-Grained Detection of AI Generated Texts

Ram Mohan Rao Kadiyala, Siddartha Pullakhandam, Kanwal Mehreen +11

An ideal detection system for machine generated content is supposed to work well on any generator as many more advanced LLMs come into existence day by day. Existing systems often…

cs.CL2025

Improving Multilingual Capabilities with Cultural and Local Knowledge in Large Language Models While Enhancing Native Performance

Ram Mohan Rao Kadiyala, Siddartha Pullakhandam, Siddhant Gupta +6

Large Language Models (LLMs) have shown remarkable capabilities, but their development has primarily focused on English and other high-resource languages, leaving many languages un…

cs.CL2024

1-800-SHARED-TASKS at RegNLP: Lexical Reranking of Semantic Retrieval (LeSeR) for Regulatory Question Answering

Jebish Purbey, Drishti Sharma, Siddhant Gupta +3

This paper presents the system description of our entry for the COLING 2025 RegNLP RIRAG (Regulatory Information Retrieval and Answer Generation) challenge, focusing on leveraging…

cs.CL2024

SeQwen at the Financial Misinformation Detection Challenge Task: Sequential Learning for Claim Verification and Explanation Generation in Financial Domains

Jebish Purbey, Siddhant Gupta, Nikhil Manali +4

This paper presents the system description of our entry for the COLING 2025 FMD challenge, focusing on misinformation detection in financial domains. We experimented with a combina…

cs.CL2024

1-800-SHARED-TASKS @ NLU of Devanagari Script Languages: Detection of Language, Hate Speech, and Targets using LLMs

Jebish Purbey, Siddartha Pullakhandam, Kanwal Mehreen +4

This paper presents a detailed system description of our entry for the CHiPSAL 2025 shared task, focusing on language detection, hate speech identification, and target detection in…

cs.CL2024

Augmenting Legal Decision Support Systems with LLM-based NLI for Analyzing Social Media Evidence

Ram Mohan Rao Kadiyala, Siddartha Pullakhandam, Kanwal Mehreen +2

This paper presents our system description and error analysis of our entry for NLLP 2024 shared task on Legal Natural Language Inference (L-NLI) \citep{hagag2024legallenssharedtask…