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Jasjeet S. Sekhon

2 accepted papers

2025

Establishing Best Practices in Building Rigorous Agentic Benchmarks

NeurIPS 2025poster

Benchmarks are essential for quantitatively tracking progress in AI. As AI agents become increasingly capable, researchers and practitioners have introduced agentic benchmarks to evaluate agents on complex, real-world tasks. These benchmarks typically measure agent capabilities by evaluating task ou…

Cited by 0SourceScholar
2024

Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations

CVPR 2024poster

Fine-tuning pre-trained vision-language models like CLIP has yielded success on diverse downstream tasks. However several pain points persist for this paradigm: (i) directly tuning entire pre-trained models becomes both time-intensive and computationally costly. Additionally these tuned models tend…