19 citations · 41 across the 11 of their papers we have counts for
11 papers
TAPR: Enhancing LLM Performance with a Task-Aware Prompt Rewriter
Oliver Savolainen, Emanuele Bastianelli, Hosein Azarbonyad
Large Language Models (LLMs) often require carefully crafted prompts to unlock their full potential, which can be a barrier for non-expert users. This work addresses the challenge…
Going for GOAL: A Resource for Grounded Football Commentaries
Alessandro Suglia, José Lopes, Emanuele Bastianelli +6
Recent video+language datasets cover domains where the interaction is highly structured, such as instructional videos, or where the interaction is scripted, such as TV shows. Both…
An Empirical Study on the Generalization Power of Neural Representations Learned via Visual Guessing Games
Alessandro Suglia, Yonatan Bisk, Ioannis Konstas +4
Guessing games are a prototypical instance of the "learning by interacting" paradigm. This work investigates how well an artificial agent can benefit from playing guessing games wh…
Encoding Syntactic Constituency Paths for Frame-Semantic Parsing with Graph Convolutional Networks
Emanuele Bastianelli, Andrea Vanzo, Oliver Lemon
We study the problem of integrating syntactic information from constituency trees into a neural model in Frame-semantic parsing sub-tasks, namely Target Identification (TI), FrameI…
SLURP: A Spoken Language Understanding Resource Package
Emanuele Bastianelli, Andrea Vanzo, Pawel Swietojanski +1
Spoken Language Understanding infers semantic meaning directly from audio data, and thus promises to reduce error propagation and misunderstandings in end-user applications. Howeve…
Imagining Grounded Conceptual Representations from Perceptual Information in Situated Guessing Games
Alessandro Suglia, Antonio Vergari, Ioannis Konstas +4
In visual guessing games, a Guesser has to identify a target object in a scene by asking questions to an Oracle. An effective strategy for the players is to learn conceptual repres…