collaborators

10 papers

cs.CL2026

Can AI Truly Represent Your Voice in Deliberations? A Comprehensive Study of Large-Scale Opinion Aggregation with LLMs

Shenzhe Zhu, Shu Yang, Michiel A. Bakker +2

Large-scale public deliberations generate thousands of free-form contributions that must be synthesized into representative and neutral summaries for policy use. While LLMs have be…

cs.CY2026

Permission Manifests for Web Agents

Samuele Marro, Alan Chan, Xinxing Ren +12

The rise of Large Language Model (LLM)-based web agents represents a significant shift in automated interactions with the web. Unlike traditional crawlers that follow simple conven…

cs.CR2025

Identity Management for Agentic AI: The new frontier of authorization, authentication, and security for an AI agent world

Tobin South, Subramanya Nagabhushanaradhya, Ayesha Dissanayaka +18

The rapid rise of AI agents presents urgent challenges in authentication, authorization, and identity management. Current agent-centric protocols (like MCP) highlight the demand fo…

cs.AI2025

ReCAP: Recursive Context-Aware Reasoning and Planning for Large Language Model Agents

Zhenyu Zhang, Tianyi Chen, Weiran Xu +2

Long-horizon tasks requiring multi-step reasoning and dynamic re-planning remain challenging for large language models (LLMs). Sequential prompting methods are prone to context dri…

cs.AI2025

The Automated but Risky Game: Modeling and Benchmarking Agent-to-Agent Negotiations and Transactions in Consumer Markets

Shenzhe Zhu, Jiao Sun, Yi Nian +3

AI agents are increasingly used in consumer-facing applications to assist with tasks such as product search, negotiation, and transaction execution. In this paper, we explore a fut…

cs.AI2025

Analyzing sequential activity and travel decisions with interpretable deep inverse reinforcement learning

Yuebing Liang, Shenhao Wang, Jiangbo Yu +3

Travel demand modeling has shifted from aggregated trip-based models to behavior-oriented activity-based models because daily trips are essentially driven by human activities. To a…