Papers by Ishan Kavathekar

2 papers
Counter Turing Test (CT2): Investigating AI-Generated Text Detection for Hindi - Ranking LLMs based on Hindi AI Detectability Index (ADI_hi) (2024.findings-emnlp)

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Challenge: a growing number of large language models are being used to detect AI-generated text . a recent study has found that some techniques to bypass detection are fragile .
Approach: They propose to use 26 LLMs to evaluate their proficiency in generating Hindi text . they propose to introduce a Hindi AI Detectability Index to assess and rank LLM models based on their detectability levels.
Outcome: The proposed methods are effective in English, but struggle in Hindi . the proposed methods show that they are susceptible to fragility .
TAMAS: Benchmarking Adversarial Risks in Multi-Agent LLM Systems (2026.acl-long)

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Challenge: Existing benchmarks and datasets focus on single-agent settings, failing to capture the unique vulnerabilities of multi-agend LLM dynamics and co-ordination.
Approach: They propose a benchmark to evaluate the robustness and safety of multi-agent LLM systems.
Outcome: The proposed benchmark evaluates the robustness and safety of multi-agent LLM systems.

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