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Coding Agents are Strong Prompt Optimizers
Agamdeep Singh, Srishti Gautam, Priyanshu Gupta +3
Search-based prompt optimizers improve prompts through iterative search: they propose edits, execute fresh rollouts, score the resulting trajectories, and retain only edits that im…
CricRAG: Retrieval Augmented Vision-Language Models for Personalized Cricket Coaching
Agamdeep Singh, Sujit PB, Mayank Vatsa
Vision-Language Models (VLMs) offer promising capabilities for automated sports coaching but face a fundamental limitation: they implicitly compare against professional standards,…
Reason Wide, Not Deep: Amortizing the Reasoning Premium into Distilled Skills
Agamdeep Singh, Srishti Gautam, Priyanshu Gupta +3
Reasoning modes of language models outperform their non-reasoning counterparts on multi-step agentic tasks, but pay a 3-6x premium in output tokens on every episode -- much of it s…