Papers by Bhavani Thuraisingham

2 papers
LPC: A Logits and Parameter Calibration Framework for Continual Learning (2022.findings-emnlp)

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Challenge: Existing approaches to solve catastrophic forgetting problem are varied . current approaches to learn continuous learning are based on replay-based methods .
Approach: They propose to calibrate parameters and logits so that preserving old parameters and generalized learning on new concepts can be solved simultaneously.
Outcome: The proposed model achieves state-of-the-art performance in all scenarios.
PEAR: Planner-Executor Agent Robustness Benchmark (2026.findings-eacl)

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Challenge: Existing studies examine isolated attack surfaces or specific scenarios, leaving a lack of holistic understanding of MAS vulnerabilities.
Approach: They propose a benchmark to evaluate the utility and vulnerability of planner–executor MAS.
Outcome: The proposed benchmark evaluates planner–executor MAS on a widely adopted design.

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