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20162026
most citedEncoding Syntactic Constituency Paths for Frame-Semantic Parsing with Graph Convolutional Networks

9 citations · 36 across the 13 of their papers we have counts for

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18 papers · 1 filter

cs.CL20231 cited

Multi-party Goal Tracking with LLMs: Comparing Pre-training, Fine-tuning, and Prompt Engineering

Angus Addlesee, Weronika Sieińska, Nancie Gunson +3

This paper evaluates the extent to which current Large Language Models (LLMs) can capture task-oriented multi-party conversations (MPCs). We have recorded and transcribed 29 MPCs b…

cs.CL2023

SimpleMTOD: A Simple Language Model for Multimodal Task-Oriented Dialogue with Symbolic Scene Representation

Bhathiya Hemanthage, Christian Dondrup, Phil Bartie +1

SimpleMTOD is a simple language model which recasts several sub-tasks in multimodal task-oriented dialogues as sequence prediction tasks. SimpleMTOD is built on a large-scale trans…

cs.CL2021

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…

cs.CL20209 cited

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…

cs.CL2020

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…

cs.CL20201 cited

CompGuessWhat?!: A Multi-task Evaluation Framework for Grounded Language Learning

Alessandro Suglia, Ioannis Konstas, Andrea Vanzo +4

Approaches to Grounded Language Learning typically focus on a single task-based final performance measure that may not depend on desirable properties of the learned hidden represen…