The scientific and technological objectives of QALL-ME pursued three crucial directions: multilingual open domain QA, user-driven and context-aware QA, and learning technologies for QA. The specific research objectives of the project included state-of-art advancements in the complexity of the questions handled by the system(e.g. how questions); the development of a web-based architecture for cross-language QA (i.e. question in one language, answer in a different language); the realization of real-time QA systems for concrete applications; the integration of the temporal and spatial context both for question interpretation and for answer extraction; the development of a robust framework for applying minimally supervised machine learning algorithms to QA tasks; and the integration of mature technologies for automatic speech recognition within the open domain question answering framework.
📢First Call for Papers 📢
The 22nd @iwslt event will be co-located with @aclmeeting
31 July-1 August 2025 –Vienna, Austria
Scientific submission due March 15, 2025
More details here:
@marcfede @esalesk @ELRAnews @shashwatup9k @MarineCarpuat @_janius_
**Shared Tasks**:
The @iwslt 2025 shared tasks () will focus on the following areas:
- High-resource ST
- Low-resource ST
- Instruction-following Speech Processing track
Jan 1, 2025: Release of shared task training and dev data
Our @apierg presenting our #calamita challenges at #CLiCit2024: machine translation and gender-fair generation.
Poster session upcoming, see you there!
For more details:
👉 MagneT: https://clic2024.ilc.cnr.it/wp-content/uploads/2024/12/120_calamita_long.pdf
👉 GFG: https://clic2024.ilc.cnr.it/wp-content/uploads/2024/12/122_calamita_long.pdf