2 citations · 2 across the 5 of their papers we have counts for
5 papers
Exposing Weak Links in Multi-Agent Systems under Adversarial Prompting
Nirmit Arora, Sathvik Joel, Ishan Kavathekar +6
LLM-based agents are increasingly deployed in multi-agent systems (MAS). As these systems move toward real-world applications, their security becomes paramount. Existing research l…
TAMAS: Benchmarking Adversarial Risks in Multi-Agent LLM Systems
Ishan Kavathekar, Hemang Jain, Ameya Rathod +2
Large Language Models (LLMs) have demonstrated strong capabilities as autonomous agents through tool use, planning, and decision-making abilities, leading to their widespread adopt…
Small Models, Big Tasks: An Exploratory Empirical Study on Small Language Models for Function Calling
Ishan Kavathekar, Raghav Donakanti, Ponnurangam Kumaraguru +1
Function calling is a complex task with widespread applications in domains such as information retrieval, software engineering and automation. For example, a query to book the shor…
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…
InSaAF: Incorporating Safety through Accuracy and Fairness | Are LLMs ready for the Indian Legal Domain?
Yogesh Tripathi, Raghav Donakanti, Sahil Girhepuje +7
Recent advancements in language technology and Artificial Intelligence have resulted in numerous Language Models being proposed to perform various tasks in the legal domain ranging…