most citedConfronting LLMs with Traditional ML: Rethinking the Fairness of Large Language Models in Tabular Classifications

2 citations · 2 across the 4 of their papers we have counts for

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cs.AI2026

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…

cs.AI2026

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…