Papers by Krish Sharma
Counter Turing Test (CT2): AI-Generated Text Detection is Not as Easy as You May Think - Introducing AI Detectability Index (ADI) (2023.emnlp-main)
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Megha Chakraborty, S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Shreya Gautam, Tanay Kumar, Krish Sharma, Niyar Barman, Chandan Gupta, Vinija Jain, Aman Chadha, Amit Sheth, Amitava Das
| Challenge: | a number of issues have arisen regarding the risk and consequences of AI-generated text detection. |
| Approach: | They propose a counter-turing test to evaluate the robustness of existing AGTD methods . they propose ADI, a quantifiable spectrum to assess detectability of LLMs . |
| Outcome: | The proposed method evaluates the robustness of existing AGTD methods . it shows that larger LLMs tend to have lower ADI, indicating they are less detectable . |
TELL-TALE: Task Efficient LLMs with Task Aware Layer Elimination (2026.findings-acl)
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| Challenge: | Large Language Models typically come with a fixed architecture, but not all layers contribute equally to every downstream task. |
| Approach: | They propose an inference-time method that selectively removes irrelevant or detrimental layers . the method is hardware-agnostic, requires no retraining, and operates entirely at inference time . |
| Outcome: | The proposed method matches or surpasses baseline performance while reducing computational costs. |