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cs.AI2026

Rehearsed Multi-Agent Live Product Demonstrations with Real-Time Voice Question Answering

Rahul Khedar, Mayank Malhotra, Avinash Karn +2

Live product demonstrations are a recurring, high-cost activity in software organizations: a human presenter must select features, dispatch the corresponding interactions on a runn…

cs.AI2026

State-Grounded Multi-Agent Synthetic Data Generation for Tool-Augmented LLMs

Rahul Khedar, Eshita, Sneha Teja Sree Reddy Thondapu +10

Training tool-augmented LLM agents requires large corpora of multi-turn, tool-grounded conversational data that is expensive to annotate, privacy-constrained in production settings…

cs.AI2026

Toward Scalable Verifiable Reward: Proxy State-Based Evaluation for Multi-turn Tool-Calling LLM Agents

Yun-Shiuan Chuang, Chaitanya Kulkarni, Alec Chiu +8

Interactive large language model (LLM) agents operating via multi-turn dialogue and multi-step tool calling are increasingly used in production. Benchmarks for these agents must bo…

cs.AI2026

Ada-RS: Adaptive Rejection Sampling for Selective Thinking

Yirou Ge, Yixi Li, Alec Chiu +8

Large language models (LLMs) are increasingly being deployed in cost and latency-sensitive settings. While chain-of-thought improves reasoning, it can waste tokens on simple reques…

cs.AI2026

NEMO-4-PAYPAL: Leveraging NVIDIA's Nemo Framework for empowering PayPal's Commerce Agent

Sudhanshu Garg, Andrew Wang, Chaitanya Kulkarni +11

We present the development and optimization of PayPal's Commerce Agent, powered by NEMO-4-PAYPAL, a multi-agent system designed to revolutionize agentic commerce on the PayPal plat…