Zero-shot Slot Filling

8 papers with code • 3 benchmarks • 3 datasets

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Most implemented papers

Zero-shot Slot Filling with DPR and RAG

IBM/retrieve-write-slot-filling 17 Apr 2021

Recently, there has been a promising direction in evaluating language models in the same way we would evaluate knowledge bases, and the task of slot filling is the most suitable to this intent.

Robust Retrieval Augmented Generation for Zero-shot Slot Filling

ibm/kgi-slot-filling EMNLP 2021

Automatically inducing high quality knowledge graphs from a given collection of documents still remains a challenging problem in AI.

MASSIVE: A 1M-Example Multilingual Natural Language Understanding Dataset with 51 Typologically-Diverse Languages

alexa/massive 18 Apr 2022

We present the MASSIVE dataset--Multilingual Amazon Slu resource package (SLURP) for Slot-filling, Intent classification, and Virtual assistant Evaluation.

Robust Zero-Shot Cross-Domain Slot Filling with Example Values

zliucr/coach ACL 2019

Task-oriented dialog systems increasingly rely on deep learning-based slot filling models, usually needing extensive labeled training data for target domains.

GenSF: Simultaneous Adaptation of Generative Pre-trained Models and Slot Filling

shikib/generative_slot_filling SIGDIAL (ACL) 2021

We instead achieve strong alignment by simultaneously modifying both the pre-trained model and the formulation of the downstream task, which is more efficient and preserves the scalability of transfer learning.

Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot Filling

w-lw/pclc EMNLP 2021

Zero-shot cross-domain slot filling alleviates the data dependence in the case of data scarcity in the target domain, which has aroused extensive research.

A Multi-Task BERT Model for Schema-Guided Dialogue State Tracking

lefteris12/multitask-schema-guided-dst 2 Jul 2022

Task-oriented dialogue systems often employ a Dialogue State Tracker (DST) to successfully complete conversations.

Re2G: Retrieve, Rerank, Generate

ibm/kgi-slot-filling NAACL 2022

As demonstrated by GPT-3 and T5, transformers grow in capability as parameter spaces become larger and larger.