الباحثون

Srinivasan Manoharan

المنشورات 2

نسخة أولية وصول مفتوح

Student-Guided Teacher Distillation for Efficient LLM Task Routing: Positioning Against Jev-Style System-1 Classifiers

Haifeng Wu, Srinivasan Manoharan, Jian Wan وآخرون · 2026

Zero-shot classifiers are useful for routing user requests to specialized LLM tasks, but scoring every request against a large candidate set is expensive: a zero-shot NLI classifier must evaluate one premise-hypothesis pair per label, so cost scales linearly with taxonomy size. We study a student-guided teacher distill …

نسخة أولية وصول مفتوح

Zero-Trust Authorization and Discovery for Enterprise MCP

LLM agents translate natural-language context, which may include attacker-controlled text, into privileged tool calls, so authorization must remain effective even when an agent is prompt-injected or adversarially steered. The Model Context Protocol (MCP) has become a widely adopted interface for this boundary, yet its …

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