4 citations · 6 across the 13 of their papers we have counts for
16 papers
AM-Bench: A Unified Taxonomy and Evaluation Suite for Agentic Misalignment
Eric Zhang, Terry Jingchen Zhang, Chijioke Ugwuanyi +3
As LLM-based agents are deployed with increasing autonomy in real-world environments, a critical failure mode emerges: agentic misalignment, where agents choose harmful actions ove…
When Agents Lie: Premeditation, Persistence, and Exploitation in Repeated Games
Jerick Shi, Terry Jingcheng Zhang, Bernhard Schölkopf +2
As large language models are deployed as autonomous agents that communicate intentions before acting, a critical safety question is whether agents that publicly commit to actions w…
Mechanism Design Is Not Enough: Prosocial Agents for Cooperative AI
Xuanqiang Angelo Huang, Charlie Tharas, Samuele Marro +4
Ensuring that AI agents behave safely and beneficially when interacting with other parties has emerged as one of the central challenges of modern AI safety. While mechanism design,…
Stargazer: A Scalable Model-Fitting Benchmark Environment for AI Agents under Astrophysical Constraints
Xinge Liu, Terry Jingchen Zhang, Bernhard Schölkopf +2
The rise of autonomous AI agents suggests that dynamic benchmark environments with built-in feedback on scientifically grounded tasks are needed to evaluate the capabilities of the…
Evaluating Cooperation in LLM Social Groups through Elected Leadership
Ryan Faulkner, Anushka Deshpande, David Guzman Piedrahita +2
Governing common-pool resources requires agents to develop enduring strategies through cooperation and self-governance to avoid collective failure. While foundation models have sho…
Cheap Talk, Empty Promise: Frontier LLMs easily break public promises for self-interest
Jerick Shi, Terry Jingcheng Zhang, Zhijing Jin +1
Large language models are increasingly deployed as autonomous agents in multi-agent settings where they communicate intentions and take consequential actions with limited human ove…
CoopEval: Benchmarking Cooperation-Sustaining Mechanisms and LLM Agents in Social Dilemmas
Emanuel Tewolde, Xiao Zhang, David Guzman Piedrahita +2
It is increasingly important that LLM agents interact effectively and safely with other goal-pursuing agents, yet, recent works report the opposite trend: LLMs with stronger reason…
From Sycophancy to Deception: A Unified Taxonomy for LLM Spontaneous Misalignment
Jerick Shi, Terry Jingcheng Zhang, Zhijing Jin +1
Large language models (LLMs) could produce systematically misaligned output, from hallucinated citations to strategic deception of evaluators, yet these phenomena are studied by se…
Are LLMs Good Safety Agents or a Propaganda Engine?
Neemesh Yadav, Francesco Ortu, Jiarui Liu +5
Large Language Models (LLMs) are trained to refuse to respond to harmful content. However, systematic analyses of whether this behavior is truly a reflection of its safety policies…
SocialHarmBench: Revealing LLM Vulnerabilities to Socially Harmful Requests
Punya Syon Pandey, Hai Son Le, Devansh Bhardwaj +2
Large language models (LLMs) are increasingly deployed in contexts where their failures can have direct sociopolitical consequences. Yet, existing safety benchmarks rarely test vul…
When Seeing Overrides Knowing: Disentangling Knowledge Conflicts in Vision-Language Models
Francesco Ortu, Zhijing Jin, Diego Doimo +1
Vision-language models (VLMs) increasingly combine visual and textual information to perform complex tasks. However, conflicts between their internal knowledge and external visual…
NLP for Social Good: A Survey and Outlook of Challenges, Opportunities, and Responsible Deployment
Antonia Karamolegkou, Angana Borah, Eunjung Cho +30
Natural language processing (NLP) now shapes many aspects of our world, yet its potential for positive social impact is underexplored. This paper surveys work in ``NLP for Social G…
Are Language Models Consequentialist or Deontological Moral Reasoners?
Keenan Samway, Max Kleiman-Weiner, David Guzman Piedrahita +3
As AI systems increasingly navigate applications in healthcare, law, and governance, understanding how they handle ethically complex scenarios becomes critical. Previous work has m…
When Ethics and Payoffs Diverge: LLM Agents in Morally Charged Social Dilemmas
Steffen Backmann, David Guzman Piedrahita, Terry Jingchen Zhang +4
Recent advances in LLMs have enabled their use in complex agentic roles, involving decision-making with humans or other agents, making ethical alignment a critical concern. While p…
Revealing Hidden Mechanisms of Cross-Country Content Moderation with Natural Language Processing
Neemesh Yadav, Jiarui Liu, Francesco Ortu +3
The ability of Natural Language Processing (NLP) methods to categorize text into multiple classes has motivated their use in online content moderation tasks, such as hate speech an…
Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone
Rada Mihalcea, Oana Ignat, Longju Bai +7
This paper presents a vision for creating AI systems that are inclusive at every stage of development, from data collection to model design and evaluation. We address key limitatio…