activity
20202025
most citedEmoUS: Simulating User Emotions in Task-Oriented Dialogues

14 citations · 37 across the 18 of their papers we have counts for

collaborators

20 papers

cs.CL2025

Prompt reinforcing for long-term planning of large language models

Hsien-Chin Lin, Benjamin Matthias Ruppik, Carel van Niekerk +6

Large language models (LLMs) have achieved remarkable success in a wide range of natural language processing tasks and can be adapted through prompting. However, they remain subopt…

cs.CL2025

Post-Training Large Language Models via Reinforcement Learning from Self-Feedback

Carel van Niekerk, Renato Vukovic, Benjamin Ruppik +4

Large Language Models (LLMs) often produce plausible but poorly-calibrated answers, limiting their reliability on reasoning-intensive tasks. Recent research suggests that Chain-of-…

cs.CL2025

All Learning Has an Emotional Basis, So Does Task-Oriented Dialogue

Shutong Feng, Hsien-chin Lin, Nurul Lubis +5

Task-oriented dialogue (ToD) systems aim to help users accomplish goals through natural language interaction. Beyond task success, effective ToD systems must also maintain positive…

cs.CL2025

Text-to-SQL Task-oriented Dialogue Ontology Construction

Renato Vukovic, Carel van Niekerk, Michael Heck +5

Large language models (LLMs) are widely used as general-purpose knowledge sources, but they rely on parametric knowledge, limiting explainability and trustworthiness. In task-orien…

cs.CL2024

Learning from Noisy Labels via Self-Taught On-the-Fly Meta Loss Rescaling

Michael Heck, Christian Geishauser, Nurul Lubis +6

Correct labels are indispensable for training effective machine learning models. However, creating high-quality labels is expensive, and even professionally labeled data contains e…

cs.CL2024

Local Topology Measures of Contextual Language Model Latent Spaces With Applications to Dialogue Term Extraction

Benjamin Matthias Ruppik, Michael Heck, Carel van Niekerk +5

A common approach for sequence tagging tasks based on contextual word representations is to train a machine learning classifier directly on these embedding vectors. This approach h…

cs.CL2024

Infusing Emotions into Task-oriented Dialogue Systems: Understanding, Management, and Generation

Shutong Feng, Hsien-chin Lin, Christian Geishauser +6

Emotions are indispensable in human communication, but are often overlooked in task-oriented dialogue (ToD) modelling, where the task success is the primary focus. While existing w…

cs.CL2024

Dialogue Ontology Relation Extraction via Constrained Chain-of-Thought Decoding

Renato Vukovic, David Arps, Carel van Niekerk +4

State-of-the-art task-oriented dialogue systems typically rely on task-specific ontologies for fulfilling user queries. The majority of task-oriented dialogue data, such as custome…

cs.CL2023★ 3 cited

A Confidence-based Acquisition Model for Self-supervised Active Learning and Label Correction

Carel van Niekerk, Christian Geishauser, Michael Heck +6

Supervised neural approaches are hindered by their dependence on large, meticulously annotated datasets, a requirement that is particularly cumbersome for sequential tasks. The qua…

cs.CL2023

From Chatter to Matter: Addressing Critical Steps of Emotion Recognition Learning in Task-oriented Dialogue

Shutong Feng, Nurul Lubis, Benjamin Ruppik +6

Emotion recognition in conversations (ERC) is a crucial task for building human-like conversational agents. While substantial efforts have been devoted to ERC for chit-chat dialogu…

math.GT2023

Algorithms for Computing Invariants of Trisected Branched Covers

Patricia Cahn, Gordana Matic, Benjamin Ruppik

We give diagrammatic algorithms for computing the group trisection, homology groups, and intersection form of a closed, orientable, smooth 4-manifold, presented as a branched cover…

cs.CL2023★ 14 cited

EmoUS: Simulating User Emotions in Task-Oriented Dialogues

Hsien-Chin Lin, Shutong Feng, Christian Geishauser +6

Existing user simulators (USs) for task-oriented dialogue systems only model user behaviour on semantic and natural language levels without considering the user persona and emotion…

cs.CL2023★ 1 cited

ChatGPT for Zero-shot Dialogue State Tracking: A Solution or an Opportunity?

Michael Heck, Nurul Lubis, Benjamin Ruppik +6

Recent research on dialogue state tracking (DST) focuses on methods that allow few- and zero-shot transfer to new domains or schemas. However, performance gains heavily depend on a…

math.GT2023

A group-theoretic framework for low-dimensional topology

Sarah Blackwell, Robion Kirby, Michael Klug +2

A correspondence, by way of Heegaard splittings, between closed oriented 3-manifolds and pairs of surjections from a surface group to a free group has been studied by Stallings, Ja…

math.GT2022

Unknotting via null-homologous twists and multi-twists

Samantha Allen, Kenan Ince, Seungwon Kim +2

The untwisting number of a knot K is the minimum number of null-homologous twists required to convert K to the unknot. Such a twist can be viewed as a generalization of a crossing…

cs.CL2022

Dialogue Term Extraction using Transfer Learning and Topological Data Analysis

Renato Vukovic, Michael Heck, Benjamin Matthias Ruppik +3

Goal oriented dialogue systems were originally designed as a natural language interface to a fixed data-set of entities that users might inquire about, further described by domain,…

math.GT2020★ 4 cited

Homotopy classification of 4-manifolds whose fundamental group is dihedral

Daniel Kasprowski, John Nicholson, Benjamin Ruppik

We show that the homotopy type of a finite oriented Poincaré 4-complex is determined by its quadratic 2-type provided its fundamental group is finite and has a dihedral Sylow 2-sub…

math.GT2020★ 4 cited

Deep and shallow slice knots in 4-manifolds

Michael Klug, Benjamin Ruppik

We consider slice disks for knots in the boundary of a smooth compact 4-manifold . We call a knot deep slice in if there is a smooth properly embe…

math.GT2020★ 8 cited

Unknotting numbers of 2-spheres in the 4-sphere

Jason Joseph, Michael Klug, Benjamin Ruppik +1

We compare two naturally arising notions of unknotting number for 2-spheres in the 4-sphere: namely, the minimal number of 1-handle stabilizations needed to obtain an unknotted sur…

math.GT2020★ 3 cited

Homotopy classification of 4-manifolds with finite abelian 2-generator fundamental groups

Daniel Kasprowski, Mark Powell, Benjamin Ruppik

We show that for an oriented 4-dimensional Poincaré complex with finite fundamental group, whose 2-Sylow subgroup is abelian with at most 2 generators, the homotopy type is determi…