Search Results for author:
Found 14 papers, 7 papers with code
ConvFiT: Conversational Fine-Tuning of Pretrained Language Models
Transformer-based language models (LMs) pretrained on large text collections are proven to store a wealth of semantic knowledge.
Multilingual and Cross-Lingual Intent Detection from Spoken Data
We present a systematic study on multilingual and cross-lingual intent detection from spoken data.
Span-ConveRT: Few-shot Span Extraction for Dialog with Pretrained Conversational Representations
We introduce Span-ConveRT, a light-weight model for dialog slot-filling which frames the task as a turn-based span extraction task.
Multidirectional Associative Optimization of Function-Specific Word Representations
We present a neural framework for learning associations between interrelated groups of words such as the ones found in Subject-Verb-Object (SVO) structures.
Efficient Intent Detection with Dual Sentence Encoders
Building conversational systems in new domains and with added functionality requires resource-efficient models that work under low-data regimes (i. e., in few-shot setups).
PolyResponse: A Rank-based Approach to Task-Oriented Dialogue with Application in Restaurant Search and Booking
We present PolyResponse, a conversational search engine that supports task-oriented dialogue.
Training Neural Response Selection for Task-Oriented Dialogue Systems
Despite their popularity in the chatbot literature, retrieval-based models have had modest impact on task-oriented dialogue systems, with the main obstacle to their application being the low-data regime of most task-oriented dialogue tasks.
Show Some Love to Your n-grams: A Bit of Progress and Stronger n-gram Language Modeling Baselines
In recent years neural language models (LMs) have set the state-of-the-art performance for several benchmarking datasets.
A Repository of Conversational Datasets
Progress in Machine Learning is often driven by the availability of large datasets, and consistent evaluation metrics for comparing modeling approaches.
BIG-bench Machine Learning
Conversational Response Selection
+1
On the Relation between Linguistic Typology and (Limitations of) Multilingual Language Modeling
A key challenge in cross-lingual NLP is developing general language-independent architectures that are equally applicable to any language.
Scoring Lexical Entailment with a Supervised Directional Similarity Network
Experiments show excellent performance on scoring graded lexical entailment, raising the state-of-the-art on the HyperLex dataset by approximately 25%.
Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level Prediction
Neural architectures are prominent in the construction of language models (LMs).
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment
We introduce HyperLex - a dataset and evaluation resource that quantifies the extent of of the semantic category membership, that is, type-of relation also known as hyponymy-hypernymy or lexical entailment (LE) relation between 2, 616 concept pairs.
SimVerb-3500: A Large-Scale Evaluation Set of Verb Similarity
Verbs play a critical role in the meaning of sentences, but these ubiquitous words have received little attention in recent distributional semantics research.
