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From the 1 of 9 linked papers with an AI index.

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9 papers

cs.IR2026

Can Argus Judge Them All? Comparing VLMs Across Domains

Harsh Joshi, Gautam Siddharth Kashyap, Rafiq Ali +5

The paper introduces ARGUS-EVAL, a framework that assesses vision-language models on both capability and reliability across domains, and uses it to compare several VLMs on retrieva…

cs.CL2026

ChildGuard: A Specialized Dataset for Combatting Child-Targeted Hate Speech

Gautam Siddharth Kashyap, Mohammad Anas Azeez, Rafiq Ali +3

Mental health industry faces growing concerns regarding hate speech directed at children's on social media, as exposure to such content can contribute to adverse psychological outc…

cs.CL2026

Truth, Trust, and Trouble: Medical AI on the Edge

Mohammad Anas Azeez, Rafiq Ali, Ebad Shabbir +4

Large Language Models (LLMs) hold significant promise for transforming digital health by enabling automated medical question answering. However, ensuring these models meet critical…

cs.CL2026

Are Large Language Models Economically Viable for Industry Deployment?

Abdullah Mohammad, Sushant Kumar Ray, Pushkar Arora +5

Generative AI-powered by Large Language Models (LLMs)-is increasingly deployed in industry across healthcare decision support, financial analytics, enterprise retrieval, and conver…

cs.CL2026

They Said Memes Were Harmless-We Found the Ones That Hurt: Decoding Jokes, Symbols, and Cultural References

Sahil Tripathi, Gautam Siddharth Kashyap, Mehwish Nasim +3

Meme-based social abuse detection is challenging because harmful intent often relies on implicit cultural symbolism and subtle cross-modal incongruence. Prior approaches, from fusi…

cs.CL2026

Revealing the Truth with ConLLM for Detecting Multi-Modal Deepfakes

Gautam Siddharth Kashyap, Harsh Joshi, Niharika Jain +4

The rapid rise of deepfake technology poses a severe threat to social and political stability by enabling hyper-realistic synthetic media capable of manipulating public perception.…