30 citations · 58 across the 22 of their papers we have counts for
23 papers
Model vs. User: Whose Values Prevail? Inference-Time Value Alignment in Multi-Turn Conversations
Enrico Liscio, Anne Arzberger, Aditya Shankar +1
Human values shape how we expect language models to behave. Dominant alignment approaches treat values as global objectives, although the appropriate value orientation is personal…
Objective-Behavior Alignment: Diagnostics for MORL Policy Selection
Antonio Mone, Zuzanna Osika, Florian Felten +4
Real-world decision-making often requires optimizing multiple competing objectives simultaneously. In reinforcement learning (RL), this is typically addressed by combining reward s…
Not All Subjectivity Is the Same! Defining Desiderata for the Evaluation of Subjectivity in NLP
Urja Khurana, Michiel van der Meer, Enrico Liscio +2
Subjective judgments are part of several NLP datasets and recent work is increasingly prioritizing models whose outputs reflect this diversity of perspectives. Such responses allow…
Reading Between the Signs: Predicting Future Suicidal Ideation from Adolescent Social Media Texts
Paul Blum, Enrico Liscio, Ruixuan Zhang +2
Suicide is a leading cause of death, yet predicting it remains a significant challenge. Risk factors such as depression or substance use are commonly used for prediction, but their…
Signs of Struggle: Spotting Cognitive Distortions across Language and Register
Abhishek Kuber, Enrico Liscio, Ruixuan Zhang +2
Rising mental health issues among youth have increased interest in automated approaches for detecting early signs of psychological distress in digital text. One key focus is the id…
Diverse Committees with Incomplete or Inaccurate Approval Ballots
Feline Lindeboom, Martijn Brehm, Davide Grossi +1
We study diversity in approval-based committee elections with incomplete or inaccurate information. We define diversity according to the Maximum Coverage problem, which is known to…
Exploring Equity of Climate Policies using Multi-Agent Multi-Objective Reinforcement Learning
Palok Biswas, Zuzanna Osika, Isidoro Tamassia +5
Addressing climate change requires coordinated policy efforts of nations worldwide. These efforts are informed by scientific reports, which rely in part on Integrated Assessment Mo…
Multi-Objective Reinforcement Learning for Water Management
Zuzanna Osika, Roxana Rădulescu, Jazmin Zatarain Salazar +2
Many real-world problems (e.g., resource management, autonomous driving, drug discovery) require optimizing multiple, conflicting objectives. Multi-objective reinforcement learning…
News is More than a Collection of Facts: Moral Frame Preserving News Summarization
Enrico Liscio, Michela Lorandi, Pradeep K. Murukannaiah
News articles are more than collections of facts; they reflect journalists' framing, shaping how events are presented to the audience. One key aspect of framing is the choice to wr…
Navigating Trade-offs: Policy Summarization for Multi-Objective Reinforcement Learning
Zuzanna Osika, Jazmin Zatarain-Salazar, Frans A. Oliehoek +1
Multi-objective reinforcement learning (MORL) is used to solve problems involving multiple objectives. An MORL agent must make decisions based on the diverse signals provided by di…
Annotator-Centric Active Learning for Subjective NLP Tasks
Michiel van der Meer, Neele Falk, Pradeep K. Murukannaiah +1
Active Learning (AL) addresses the high costs of collecting human annotations by strategically annotating the most informative samples. However, for subjective NLP tasks, incorpora…
A Hybrid Intelligence Method for Argument Mining
Michiel van der Meer, Enrico Liscio, Catholijn M. Jonker +3
Large-scale survey tools enable the collection of citizen feedback in opinion corpora. Extracting the key arguments from a large and noisy set of opinions helps in understanding th…
An Empirical Analysis of Diversity in Argument Summarization
Michiel van der Meer, Piek Vossen, Catholijn M. Jonker +1
Presenting high-level arguments is a crucial task for fostering participation in online societal discussions. Current argument summarization approaches miss an important facet of t…
Value Preferences Estimation and Disambiguation in Hybrid Participatory Systems
Enrico Liscio, Luciano C. Siebert, Catholijn M. Jonker +1
Understanding citizens' values in participatory systems is crucial for citizen-centric policy-making. We envision a hybrid participatory system where participants make choices and…
Morality is Non-Binary: Building a Pluralist Moral Sentence Embedding Space using Contrastive Learning
Jeongwoo Park, Enrico Liscio, Pradeep K. Murukannaiah
Recent advances in NLP show that language models retain a discernible level of knowledge in deontological ethics and moral norms. However, existing works often treat morality as bi…
Enabling the Digital Democratic Revival: A Research Program for Digital Democracy
Davide Grossi, Ulrike Hahn, Michael Mäs +26
This white paper outlines a long-term scientific vision for the development of digital-democracy technology. We contend that if digital democracy is to meet the ambition of enablin…
What Lies beyond the Pareto Front? A Survey on Decision-Support Methods for Multi-Objective Optimization
Zuzanna Osika, Jazmin Zatarain Salazar, Diederik M. Roijers +2
We present a review that unifies decision-support methods for exploring the solutions produced by multi-objective optimization (MOO) algorithms. As MOO is applied to solve diverse…
Do Differences in Values Influence Disagreements in Online Discussions?
Michiel van der Meer, Piek Vossen, Catholijn M. Jonker +1
Disagreements are common in online discussions. Disagreement may foster collaboration and improve the quality of a discussion under some conditions. Although there exist methods fo…
Reflective Hybrid Intelligence for Meaningful Human Control in Decision-Support Systems
Catholijn M. Jonker, Luciano Cavalcante Siebert, Pradeep K. Murukannaiah
With the growing capabilities and pervasiveness of AI systems, societies must collectively choose between reduced human autonomy, endangered democracies and limited human rights, a…
MOPaC: The Multiple Offers Protocol for Multilateral Negotiations with Partial Consensus
Pradeep K. Murukannaiah, Catholijn M. Jonker
Existing protocols for multilateral negotiation require a full consensus among the negotiating parties. In contrast, we propose a protocol for multilateral negotiation that allows…
Towards Social Situation Awareness in Support Agents
Ilir Kola, Pradeep K. Murukannaiah, Catholijn M. Jonker +1
Artificial agents that support people in their daily activities (e.g., virtual coaches and personal assistants) are increasingly prevalent. Since many daily activities are social i…
Reason Against the Machine: Future Directions for Mass Online Deliberation
Ruth Shortall, Anatol Itten, Michiel van der Meer +2
Designers of online deliberative platforms aim to counter the degrading quality of online debates. Support technologies such as machine learning and natural language processing ope…
A Data-Driven Method for Recognizing Automated Negotiation Strategies
Ming Li, Pradeep K. Murukannaiah, Catholijn M. Jonker
Understanding an opponent agent helps in negotiating with it. Existing works on understanding opponents focus on preference modeling (or estimating the opponent's utility function)…