SOTAVerified

Slot Filling

The goal of Slot Filling is to identify from a running dialog different slots, which correspond to different parameters of the user’s query. For instance, when a user queries for nearby restaurants, key slots for location and preferred food are required for a dialog system to retrieve the appropriate information. Thus, the main challenge in the slot-filling task is to extract the target entity.

Source: Real-time On-Demand Crowd-powered Entity Extraction

Image credit: Robust Retrieval Augmented Generation for Zero-shot Slot Filling

Papers

Showing 151–200 of 458 papers

TitleStatusHype
Neuralizing Regular Expressions for Slot Filling—0
An Explicit-Joint and Supervised-Contrastive Learning Framework for Few-Shot Intent Classification and Slot Filling—0
Making Document-Level Information Extraction Right for the Right Reasons—0
Decision-Theoretic Question Generation for Situated Reference Resolution: An Empirical Study and Computational Model—0
Bridge to Target Domain by Prototypical Contrastive Learning and Label Confusion: Re-explore Zero-Shot Learning for Slot FillingCode1
Call Larisa Ivanovna: Code-Switching Fools Multilingual NLU ModelsCode0
An Enhanced Span-based Decomposition Method for Few-Shot Sequence LabelingCode1
Learning Neural Templates for Recommender Dialogue SystemCode1
Towards Joint Intent Detection and Slot Filling via Higher-order Attention—0
SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising—0
Semi-Supervised Few-Shot Intent Classification and Slot Filling—0
Slot Filling for Biomedical Information ExtractionCode0
Phrase Retrieval Learns Passage Retrieval, TooCode1
Traffic Event Detection as a Slot Filling Problem—0
A Context-Aware Hierarchical BERT Fusion Network for Multi-turn Dialog Act DetectionCode0
ShopTalk: A System for Conversational Faceted Search—0
InFoBERT: Zero-Shot Approach to Natural Language Understanding Using Contextualized Word Embedding—0
Robust Retrieval Augmented Generation for Zero-shot Slot FillingCode1
HAN: Higher-order Attention Network for Spoken Language Understanding—0
SLIM: Explicit Slot-Intent Mapping with BERT for Joint Multi-Intent Detection and Slot FillingCode1
Ontology-Enhanced Slot Filling—0
Augmenting Slot Values and Contexts for Spoken Language Understanding with Pretrained ModelsCode0
Joint Multiple Intent Detection and Slot Filling via Self-distillation—0
Slot Transferability for Cross-domain Slot Filling—0
Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems—0
结合边界预测和动态模板方法的槽填充模型(Slot Filling Model with Boundary Prediction and Dynamic Template)—0
基于BERT的意图分类与槽填充联合方法(Joint Method of Intention Classification and Slot Filling Based on BERT)—0
面向中文口语理解的基于依赖引导的字特征槽填充模型(A Dependency-Guided Character-Based Slot Filling Model for Chinese Spoken Language Understanding)—0
QA-Driven Zero-shot Slot Filling with Weak Supervision Pretraining—0
A Joint and Domain-Adaptive Approach to Spoken Language Understanding—0
Token-Level Supervised Contrastive Learning for Punctuation RestorationCode1
Question Answering over Knowledge Graphs with Neural Machine Translation and Entity Linking—0
Where are we in semantic concept extraction for Spoken Language Understanding?—0
GenSF: Simultaneous Adaptation of Generative Pre-trained Models and Slot FillingCode0
Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLPCode1
CONDA: a CONtextual Dual-Annotated dataset for in-game toxicity understanding and detection—0
GL-GIN: Fast and Accurate Non-Autoregressive Model for Joint Multiple Intent Detection and Slot FillingCode1
Would you like to tell me more? Generating a corpus of psychotherapy dialogues—0
Spoken Language Understanding for Task-oriented Dialogue Systems with Augmented Memory Networks—0
Event Time Extraction and Propagation via Graph Attention NetworksCode1
Novel Slot Detection: A Benchmark for Discovering Unknown Slot Types in the Task-Oriented Dialogue SystemCode1
Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling—0
Effective Slot Filling via Weakly-Supervised Dual-Model LearningCode0
SeaD: End-to-end Text-to-SQL Generation with Schema-aware DenoisingCode2
From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language UnderstandingCode0
Speech2Slot: An End-to-End Knowledge-based Slot Filling from Speech—0
Zero-shot Slot Filling with DPR and RAGCode1
Integration of Pre-trained Networks with Continuous Token Interface for End-to-End Spoken Language Understanding—0
Bridging the Gap Between Clean Data Training and Real-World Inference for Spoken Language Understanding—0
Few-shot Intent Classification and Slot Filling with Retrieved Examples—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1single ngramKILT-AC73.2—Unverified
2KGI_1KILT-AC72.31—Unverified
3MetaRAGKILT-AC71.1—Unverified
4KGI_0 (reupload)KILT-AC68.32—Unverified
5WikipediaKILT-AC67.2—Unverified
6Multitask DPR + BARTKILT-AC50.64—Unverified
710kKILT-AC41.34—Unverified
8DensePhrasesKILT-AC41.34—Unverified
9RAGKILT-AC36.83—Unverified
10Coop. Distil BertKILT-AC34.13—Unverified
#ModelMetricClaimedVerifiedStatus
1Re2GKILT-AC75.84—Unverified
2KGI_1KILT-AC69.14—Unverified
3WikipediaKILT-AC64.64—Unverified
4MetaRAGKILT-AC61.88—Unverified
5single ngramKILT-AC60.08—Unverified
6KGI_0 (reupload)KILT-AC55.54—Unverified
7Coop. DistilBertKILT-AC36.68—Unverified
8DensePhrasesKILT-AC27.84—Unverified
910kKILT-AC27.84—Unverified
10RAGKILT-AC23.12—Unverified
#ModelMetricClaimedVerifiedStatus
1BiSLUMicro F197.2—Unverified
2SLIM (PACL)Micro F196.8—Unverified
3SLIMMicro F196.5—Unverified
4Uni-MISMicro F196.4—Unverified
5TFMNMicro F196.4—Unverified
6TFMN (PACL)Micro F196.3—Unverified
7RoBERTa (PACL)Micro F196.2—Unverified
8DGIFMicro F195.9—Unverified
9SSRANMicro F195.8—Unverified
10MISCAMicro F195.2—Unverified
#ModelMetricClaimedVerifiedStatus
1MISCAMicro F190.5—Unverified
2Co-guiding NetMicro F189.8—Unverified
3SSRANMicro F189.4—Unverified
4BiSLUMicro F189.4—Unverified
5UGENMicro F189.2—Unverified
6Topic InformationMicro F188.7—Unverified
7SLIMMicro F188.5—Unverified
8Global Intent-Slot Co-occurenceMicro F188.5—Unverified
9DGIFMicro F188.5—Unverified
10Uni-MISMicro F188.3—Unverified
#ModelMetricClaimedVerifiedStatus
1CTRANF10.98—Unverified
2Bi-model with a decoderF10.97—Unverified
3Joint BERTF10.96—Unverified
4Stack-Propagation (+BERT)F10.96—Unverified
5JointBERT-CAEF10.96—Unverified
6AGIFF10.96—Unverified
7Joint BERT + CRFF10.96—Unverified
8Attention Encoder-Decoder NNF10.96—Unverified
9Context EncoderF10.96—Unverified
10SF-IDF10.96—Unverified
#ModelMetricClaimedVerifiedStatus
1CTRANF198.3—Unverified
2Stack-Propagation (+BERT)F197—Unverified
3JointBERT-CAEF197—Unverified
4AGIFF194.8—Unverified
5Stack-PropagationF194.2—Unverified
6Context EncoderF193.6—Unverified
7SF-IDF192.23—Unverified
8Slot-Gated BLSTM with AttensionF188.8—Unverified
9DecomposedMetaSLF1 (1-shot) avg74.89—Unverified
10Capsule-NLUF10.92—Unverified
#ModelMetricClaimedVerifiedStatus
1TDT 0-6F10.81—Unverified
2Partially Fine-tuned HuBERTF10.75—Unverified
3Multi-SLURPF10.64—Unverified
4Finstreder (Conformer)F10.4—Unverified
5Finstreder (Quartznet)F10.31—Unverified
#ModelMetricClaimedVerifiedStatus
1XLM-R BaseSlot F1 Score83.6—Unverified
2mT5 Base (encoder-only)Slot F1 Score82.2—Unverified
3mT5 Base (text-to-text)Slot F1 Score81.3—Unverified
#ModelMetricClaimedVerifiedStatus
1JointBERT-CAESlot F195.5—Unverified
#ModelMetricClaimedVerifiedStatus
1CM-NetF186.16—Unverified
#ModelMetricClaimedVerifiedStatus
1MIDASF1 score98.56—Unverified
#ModelMetricClaimedVerifiedStatus
1MIDASF1 score99.28—Unverified
#ModelMetricClaimedVerifiedStatus
1Fashion GAEFITB96.9—Unverified
#ModelMetricClaimedVerifiedStatus
1General SLU Model w/ ProfileF10.83—Unverified