News

  • New Publication at NALOMA 2026

    We are pleased to inform you that the following paper has been accepted at the 6th NALOMA (NAtural Language Meets LOgic and MAchine Learning) workshop, co-located with ESSLLI from August 3–7 in Prague.

    Leon Hammerla and Alexander Mehler. 2026. Negation in Reasoning Traces: Interpretable Signals of Correctness and Provenance. Proceedings of the 6th Workshop on Natural Logic Meets Machine Learning (NALOMA). accepted.
    BibTeX
    @inproceedings{Hammerla:Mehler:2026:b,
      title     = {Negation in Reasoning Traces: Interpretable Signals of Correctness
                   and Provenance},
      author    = {Leon Hammerla and Alexander Mehler},
      booktitle = {Proceedings of the 6th Workshop on Natural Logic Meets Machine Learning (NALOMA)},
      year      = {2026},
      address   = {Prague (Czech Republic)},
      keywords  = {neglab},
      note      = {accepted}
    }
  • New publications at XR Salento 2026

    We are pleased to inform you about the acceptance of the following paper at XR Salento 2026 which will be published in Lecture Notes in Computer Science (LNCS) by Springer:

    Patrick Schrottenbacher, Alexander Mehler, Vivienne Bernhardt, Leon Rohe and Giuseppe Abrami. 2026. ReEmote: Towards Emotion Representation in VR Through Va.Si.Li-Lab. Proceedings of XR Salento 2026. accepted.
    BibTeX
    @inproceedings{Schrottenbacher:et:al:2026:a,
      author    = {Schrottenbacher, Patrick and Mehler, Alexander and Bernhardt, Vivienne
                   and Rohe, Leon and Abrami, Giuseppe},
      title     = {ReEmote: Towards Emotion Representation in {VR} Through {Va.Si.Li}-Lab},
      booktitle = {Proceedings of XR Salento 2026},
      year      = {2026},
      publisher = {Springer International Publishing},
      keywords  = {VR, XR, affective computing, virtual humans, emotion detection, FACES},
      abstract  = {Human social interactions are inherently multimodal, shaped not
                   only by what speakers convey but also by cues such as facial expressions,
                   posture, and gestures. Together, these channels shape both participants'
                   perceptions and behaviors, further reinforcing conversational
                   feedback loops. This multimodal system extends to VR, where avatars
                   serve as proxies for human interaction, making both visual and
                   auditory fidelity essential for engaging. To properly utilize
                   the emotional expression space that virtual environments allow,
                   we introduce ReEmote. ReEmote extends the capabilities of Va.Si.Li-Lab,
                   a collaborative, multi-user VR platform built on Ubiq. While Va.Si.Li-Lab
                   supports user emotional expression through facial and hand tracking,
                   ReEmote extends this by introducing schema-based emotion mappings
                   that affect both avatars and their environments. This fosters
                   immersive, emotionally aware environments that are beneficial
                   for human and chatbot agent interactions, where human users and
                   virtual agents share an emotional expression space. By enabling
                   richer emotional dynamics, ReEmote opens up new ways of designing
                   affective and engaging virtual experiences.In this paper, we describe
                   the design choices behind ReEmote and present an evaluation of
                   the graphical validity of the emotion representation introduced
                   by ReEmote. Our results indicate that emotions can be validly
                   represented through avatar facial expressions that users can quickly
                   identify as Ekman's basic emotions.This opens up several possibilities
                   for extending emotion-related text-to-speech (TTS) applications
                   in Extended Reality (XR) with ReEmote. The paper also outlines
                   use cases for XR-based TTS applications.},
      note      = {accepted}
    }