The TTLab (Text Technology Lab), headed by Prof. Alexander Mehler, is part of the Department of Computer Science and Mathematics (Fachbereich Informatik und Mathematik) at the Goethe Universität in Frankfurt. It investigates formal, algorithmic models to deepen our understanding of information processing in the humanities. We examine diachronic, time-dependent as well as synchronic aspects of processing linguistic and non-linguistic, multimodal signs. The Lab works across several disciplines to bridge between computer science on the one hand and corpus-based research in the humanities on the other. To this end, we develop information models and algorithms for the analysis of texts, images, and other objects relevant to research in the humanities.
News
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New publications related to CORE C08
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We are pleased to announce that the following articles have been accepted or have already been published:
July, 2026. Rubrics as Semantic Subspaces: A Unified Approach to Rubric-based Constructed Response Scoring across Short Answers and Essays. Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026), 624–634.BibTeX@inproceedings{Gombert:et:al:2026:a, title = {Rubrics as Semantic Subspaces: A Unified Approach to Rubric-based Constructed Response Scoring across Short Answers and Essays}, author = {Gombert, Sebastian and Hahn, Sonja and Andersen, Nico and Camus, Leon and Sun, Zhifan and Nguyen, Ngoc Nhu Hao and Zehner, Fabian and Cong, Longwei and Mehler, Alexander and Drachsler, Hendrik}, editor = {Kochmar, Ekaterina and Alhafni, Bashar and Bann{\`o}, Stefano and Bexte, Marie and Burstein, Jill and Horbach, Andrea and Laarmann-Quante, Ronja and Tack, Anais and Yaneva, Victoria and Yuan, Zheng}, booktitle = {Proceedings of the 21st Workshop on Innovative Use of {NLP} for Building Educational Applications ({BEA} 2026)}, month = {jul}, keywords = {core, core_c08}, year = {2026}, address = {San Diego, California, USA}, publisher = {Association for Computational Linguistics}, url = {https://aclanthology.org/2026.bea-1.44/}, doi = {10.18653/v1/2026.bea-1.44}, pages = {624--634}, isbn = {979-8-89176-409-5}, pdf = {https://aclanthology.org/2026.bea-1.44.pdf}, abstract = {Rubrics are the primary reference for manual scoring of constructed responses, and there is growing interest in their use in automated scoring methodologies. In this work, we propose Aspect-Grounded Rubric{--}Answer Alignment (AGRAA), a rubric-based end-to-end scoring framework that models rubric descriptors as latent aspect spaces. Concretely, rubric descriptors are represented as low-dimensional subspaces derived from contextualised transformer embeddings, and student responses are scored according to how strongly their representations align with these rubric-induced spaces relative to the residual space outside them. This formulation provides a geometrically grounded interpretation of rubric-based scoring while enabling end-to-end training with standard transformer encoders. We introduce three distinct architectural variants and evaluate them on multiple short-answer and essay scoring datasets. Across these tasks, AGRAA achieves predictive performance highly competitive with strong neural and feature-based baselines. In addition, the framework yields interpretable intermediate representations that expose which rubric-defined aspects contribute to scoring decisions, enabling decision-aligned explanations grounded in rubric descriptors.} }
2026. NeoBridge: A Scalable Platform for Assessment Orchestration and Log Data Collection in Online Reasoning Assessments. Proceedings of the Twenty-first European Conference on Technology Enhanced Learning. accepted.BibTeX@inproceedings{Gombert:et:al:2026:b, author = {Gombert, Sebastian and Romano, Gianluca and Camus, Leon and Baumartz, Daniel and Gon{\c{c}}alves Ribeiro, Fabiola and Mehler, Alexander and Drachsler, Hendrik}, title = {{NeoBridge}: A Scalable Platform for Assessment Orchestration and Log Data Collection in Online Reasoning Assessments}, booktitle = {Proceedings of the Twenty-first European Conference on Technology Enhanced Learning}, series = {ECTEL 2026}, address = {Valencia, Spain}, year = {2026}, keywords = {core, core_c08}, eventdate = {2026-09-14/2026-09-18}, note = {accepted} } -
New Publication at NALOMA 2026
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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.
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
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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:
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} }
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