Slot Filling

23 papers with code · Natural Language Processing

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Greatest papers with code

Learning End-to-End Goal-Oriented Dialog

24 May 2016facebookresearch/ParlAI

We show similar result patterns on data extracted from an online concierge service.

GOAL-ORIENTED DIALOG SLOT FILLING

Data Programming: Creating Large Training Sets, Quickly

NeurIPS 2016 HazyResearch/snorkel

Additionally, in initial user studies we observed that data programming may be an easier way for non-experts to create machine learning models when training data is limited or unavailable.

REGRESSION SLOT FILLING

Neural Baby Talk

CVPR 2018 jiasenlu/NeuralBabyTalk

We introduce a novel framework for image captioning that can produce natural language explicitly grounded in entities that object detectors find in the image.

IMAGE CAPTIONING SLOT FILLING

Position-aware Attention and Supervised Data Improve Slot Filling

EMNLP 2017 yuhaozhang/tacred-relation

The combination of better supervised data and a more appropriate high-capacity model enables much better relation extraction performance.

KNOWLEDGE BASE POPULATION KNOWLEDGE GRAPHS RELATION EXTRACTION SLOT FILLING

Slot-Gated Modeling for Joint Slot Filling and Intent Prediction

NAACL 2018 MiuLab/SlotGated-SLU

Attention-based recurrent neural network models for joint intent detection and slot filling have achieved the state-of-the-art performance, while they have independent attention weights.

INTENT DETECTION SLOT FILLING SPOKEN DIALOGUE SYSTEMS SPOKEN LANGUAGE UNDERSTANDING

Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling

6 Sep 2016DSKSD/RNN-for-Joint-NLU

Attention-based encoder-decoder neural network models have recently shown promising results in machine translation and speech recognition.

INTENT CLASSIFICATION INTENT DETECTION SLOT FILLING

Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset

12 Sep 2019google-research-datasets/dstc8-schema-guided-dialogue

This allows a single dialogue system to easily support a large number of services and facilitates simple integration of new services without requiring additional training data.

DIALOGUE STATE TRACKING SLOT FILLING

A Knowledge-Grounded Neural Conversation Model

7 Feb 2017DSTC-MSR-NLP/DSTC7-End-to-End-Conversation-Modeling

We generalize the widely-used Seq2Seq approach by conditioning responses on both conversation history and external "facts", allowing the model to be versatile and applicable in an open-domain setting.

SLOT FILLING

Natural Language Does Not Emerge `Naturally' in Multi-Agent Dialog

EMNLP 2017 batra-mlp-lab/lang-emerge

A number of recent works have proposed techniques for end-to-end learning of communication protocols among cooperative multi-agent populations, and have simultaneously found the emergence of grounded human-interpretable language in the protocols developed by the agents, learned without any human supervision!

SLOT FILLING