21 citations · 21 across the 2 of their papers we have counts for
5 papers
ConvApparel: A Benchmark Dataset and Validation Framework for User Simulators in Conversational Recommenders
Ofer Meshi, Krisztian Balog, Sally Goldman +5
The promise of LLM-based user simulators to improve conversational AI is hindered by a critical "realism gap," leading to systems that are optimized for simulated interactions, but…
Evaluating Cost-Accuracy Trade-offs in Multimodal Search Relevance Judgements
Silvia Terragni, Hoang Cuong, Joachim Daiber +2
Large Language Models (LLMs) have demonstrated potential as effective search relevance evaluators. However, there is a lack of comprehensive guidance on which models consistently p…
One Configuration to Rule Them All? Towards Hyperparameter Transfer in Topic Models using Multi-Objective Bayesian Optimization
Silvia Terragni, Ismail Harrando, Pasquale Lisena +2
Topic models are statistical methods that extract underlying topics from document collections. When performing topic modeling, a user usually desires topics that are coherent, dive…
Contrastive Language-Image Pre-training for the Italian Language
Federico Bianchi, Giuseppe Attanasio, Raphael Pisoni +3
CLIP (Contrastive Language-Image Pre-training) is a very recent multi-modal model that jointly learns representations of images and texts. The model is trained on a massive amount…
Cross-lingual Contextualized Topic Models with Zero-shot Learning
Federico Bianchi, Silvia Terragni, Dirk Hovy +2
Many data sets (e.g., reviews, forums, news, etc.) exist parallelly in multiple languages. They all cover the same content, but the linguistic differences make it impossible to use…