Search Results for author:
Found 3 papers, 1 papers with code
Boosting Cross-lingual Transferability in Multilingual Models via In-Context Learning
Existing cross-lingual transfer (CLT) prompting methods are only concerned with monolingual demonstration examples in the source language.
SUMBT: Slot-Utterance Matching for Universal and Scalable Belief Tracking
In goal-oriented dialog systems, belief trackers estimate the probability distribution of slot-values at every dialog turn.
Ranked #17 on
Multi-domain Dialogue State Tracking
on MULTIWOZ 2.0
Learning to Embed Semantic Correspondence for Natural Language Understanding
While learning embedding models has yielded fruitful results in several NLP subfields, most notably Word2Vec, embedding correspondence has relatively not been well explored especially in the context of natural language understanding (NLU), a task that typically extracts structured semantic knowledge from a text.
