53 citations · 70 across the 12 of their papers we have counts for
13 papers
Group Deliberation Oriented Multi-Agent Conversational Model for Complex Reasoning
Zheyu Shi, Dong Qiu, Shanlong Yu
This paper proposes a group deliberation oriented multi-agent conversational model to address the limitations of single large language models in complex reasoning tasks. The model…
Script Gap: Evaluating LLM Triage on Indian Languages in Native vs Romanized Scripts in a Real World Setting
Manurag Khullar, Utkarsh Desai, Poorva Malviya +2
Large Language Models (LLMs) are increasingly deployed in high-stakes clinical applications in India. Speakers of Indian languages frequently communicate using romanized text rathe…
RescueLens: LLM-Powered Triage and Action on Volunteer Feedback for Food Rescue
Naveen Raman, Jingwu Tang, Zhiyu Chen +4
Food rescue organizations simultaneously tackle food insecurity and waste by working with volunteers to redistribute food from donors who have excess to recipients who need it. Vol…
Contextual Budget Bandit for Food Rescue Volunteer Engagement
Ariana Tang, Naveen Raman, Fei Fang +1
Volunteer-based food rescue platforms tackle food waste by matching surplus food to communities in need. These platforms face the dual problem of maintaining volunteer engagement a…
Resolving UnderEdit & OverEdit with Iterative & Neighbor-Assisted Model Editing
Bhiman Kumar Baghel, Emma Jordan, Zheyuan Ryan Shi +1
Large Language Models (LLMs) are widely deployed in downstream tasks, but keeping their knowledge up-to-date via retraining or fine-tuning is often computationally expensive. Model…
Global Rewards in Restless Multi-Armed Bandits
Naveen Raman, Zheyuan Ryan Shi, Fei Fang
Restless multi-armed bandits (RMAB) extend multi-armed bandits so pulling an arm impacts future states. Despite the success of RMABs, a key limiting assumption is the separability…
Where It Really Matters: Few-Shot Environmental Conservation Media Monitoring for Low-Resource Languages
Sameer Jain, Sedrick Scott Keh, Shova Chettri +8
Environmental conservation organizations routinely monitor news content on conservation in protected areas to maintain situational awareness of developments that can have an enviro…
Bandit Data-Driven Optimization
Zheyuan Ryan Shi, Zhiwei Steven Wu, Rayid Ghani +1
Applications of machine learning in the non-profit and public sectors often feature an iterative workflow of data acquisition, prediction, and optimization of interventions. There…
Artificial Intelligence for Social Good: A Survey
Zheyuan Ryan Shi, Claire Wang, Fei Fang
Artificial intelligence for social good (AI4SG) is a research theme that aims to use and advance artificial intelligence to address societal issues and improve the well-being of th…
Learning and Planning in the Feature Deception Problem
Zheyuan Ryan Shi, Ariel D. Procaccia, Kevin S. Chan +5
Today's high-stakes adversarial interactions feature attackers who constantly breach the ever-improving security measures. Deception mitigates the defender's loss by misleading the…
Draining the Water Hole: Mitigating Social Engineering Attacks with CyberTWEAK
Zheyuan Ryan Shi, Aaron Schlenker, Brian Hay +5
Cyber adversaries have increasingly leveraged social engineering attacks to breach large organizations and threaten the well-being of today's online users. One clever technique, th…
Deep Reinforcement Learning for Green Security Games with Real-Time Information
Yufei Wang, Zheyuan Ryan Shi, Lantao Yu +4
Green Security Games (GSGs) have been proposed and applied to optimize patrols conducted by law enforcement agencies in green security domains such as combating poaching, illegal l…
Designing the Game to Play: Optimizing Payoff Structure in Security Games
Zheyuan Ryan Shi, Ziye Tang, Long Tran-Thanh +2
Effective game-theoretic modeling of defender-attacker behavior is becoming increasingly important. In many domains, the defender functions not only as a player but also the design…