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cs.CL2026

Training Reasoning Models to Generate Diverse Scientific Ideas

Manya Wadhwa, Pranav Narayanan Venkit, Hiroaki Hayashi +3

One of the first steps of a research pipeline is generating ideas. Large Language Models (LLMs) are increasingly used to automate this step, but most of this work optimizes the qua…

cs.CL2026

Belief Cascades Drive Persuasion in LLM Agent Networks

Haoyi Qiu, Genglin Liu, Pranav Narayanan Venkit +4

Multi-agent LLM systems increasingly debate answers, coordinate research, simulate users, and mediate information flows, making agent-to-agent persuasion a basic but undermeasured…

cs.CL2026

Dont Stop Early: Scalable Enterprise Deep Research with Controlled Information Flow and Evidence-Aware Termination

Prafulla Kumar Choubey, Kung-Hsiang Huang, Pranav Narayanan Venkit +5

Enterprise deep research often fails to produce decision-ready reports due to uneven information coverage, context explosion, and premature stopping. We propose a scalable Enterpri…

cs.CL2025

Seeing is Believing? Evaluating Vision-Language Model Susceptibility in Agent-to-Agent Multimodal Persuasion

Haoyi Qiu, Yilun Zhou, Pranav Narayanan Venkit +4

As autonomous agents increasingly interact, they inevitably attempt to influence one another. While prior work in text-only settings has explored the dynamics of Agent-to-Agent (A2…

cs.CL2025

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness

Kung-Hsiang Huang, Haoyi Qiu, Yutong Dai +2

Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. However, they also face the ineffic…