6 citations · 12 across the 8 of their papers we have counts for
3 papers · 1 filter
ReALM: Reference Resolution As Language Modeling
Joel Ruben Antony Moniz, Soundarya Krishnan, Melis Ozyildirim +4
Reference resolution is an important problem, one that is essential to understand and successfully handle context of different kinds. This context includes both previous turns and…
SynthDST: Synthetic Data is All You Need for Few-Shot Dialog State Tracking
Atharva Kulkarni, Bo-Hsiang Tseng, Joel Ruben Antony Moniz +3
In-context learning with Large Language Models (LLMs) has emerged as a promising avenue of research in Dialog State Tracking (DST). However, the best-performing in-context learning…
Can Large Language Models Understand Context?
Yilun Zhu, Joel Ruben Antony Moniz, Shruti Bhargava +6
Understanding context is key to understanding human language, an ability which Large Language Models (LLMs) have been increasingly seen to demonstrate to an impressive extent. Howe…