Papers by Agastya Seth

2 papers
UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs’ Memorization (2025.acl-long)

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Challenge: UnSeenTimeQA is a data contamination-free time-sensitive question-answering benchmark.
Approach: They propose a data contamination-free time-sensitive question-answering benchmark that avoids web-searchable queries grounded in the real world.
Outcome: The proposed benchmark avoids web-searchable queries grounded in the real world and enables on-demand generation of new samples, mitigating the risk of data leakage.
The Art of Defending: A Systematic Evaluation and Analysis of LLM Defense Strategies on Safety and Over-Defensiveness (2024.findings-acl)

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Challenge: Recent work on Large Language Models (LLMs) has identified a number of approaches to protect against their vulnerabilities and safety.
Approach: They propose to use a large collection of safe and unsafe prompts to evaluate various LLM defense strategies over both ‘safety’ and ‘over-defensiveness’.
Outcome: The proposed defense strategies are compared on multiple state-of-the-art LLMs and show that they are effective against both ‘safety’ and ‘over-defensiveness’.

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