collaborators

7 papers

cs.CL2026

Policy Compliance of User Requests in Natural Language for AI Systems

Pedro Cisneros-Velarde

Consider an organization whose users send requests in natural language to an AI system that fulfills them by carrying out specific tasks. In this paper, we consider the problem of…

cs.CL2026

Can One-sided Arguments Lead to Response Change in Large Language Models?

Pedro Cisneros-Velarde

Polemic questions need more than one viewpoint to express a balanced answer. Large Language Models (LLMs) can provide a balanced answer, but also take a single aligned viewpoint or…

cs.CL2026

Large Language Models can Achieve Social Balance

Pedro Cisneros-Velarde

Large Language Models (LLMs) can be deployed in situations where they process positive/negative interactions with other agents. We study how this is done under the sociological fra…

cs.AI2025

GTAlign: Game-Theoretic Alignment of LLM Assistants for Social Welfare

Siqi Zhu, David Zhang, Pedro Cisneros-Velarde +1

Large Language Models (LLMs) have achieved remarkable progress in reasoning, yet sometimes produce responses that are suboptimal for users in tasks such as writing, information see…

cs.CL2025

Bypassing Safety Guardrails in LLMs Using Humor

Pedro Cisneros-Velarde

In this paper, we show it is possible to bypass the safety guardrails of large language models (LLMs) through a humorous prompt including the unsafe request. In particular, our met…

cs.LG2025

Optimization for Neural Operators can Benefit from Width

Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee

Neural Operators that directly learn mappings between function spaces, such as Deep Operator Networks (DONs) and Fourier Neural Operators (FNOs), have received considerable attenti…