Memory-Based Semantic Parsing
We present a memory-based model for context-dependent semantic parsing. Previous approaches focus on enabling the decoder to copy or modify the parse from the previous utterance, assuming there is a dependency between the current and previous parses. In this work, we propose to represent contextual information using an external memory. We learn a context memory controller that manages the memory by maintaining the cumulative meaning of sequential user utterances. We evaluate our approach on three semantic parsing benchmarks. Experimental results show that our model can better process context-dependent information and demonstrates improved performance without using task-specific decoders.
Code (1)
Tasks
DecoderSemantic ParsingMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Compressing Transformer-Based Semantic Parsing Models using Compositional Code Embeddings
The current state-of-the-art task-oriented semantic parsing models use BERT or RoBERTa as pretrained encoders; these models have huge memory footprints. This poses a challenge to their deployment for voice assistants suc…
Semantic ParsingMemory Based Video Scene Parsing
Video scene parsing is a long-standing challenging task in computer vision, aiming to assign pre-defined semantic labels to pixels of all frames in a given video. Compared with image semantic segmentation, this task pays…
Scene ParsingSemantic SegmentationSyntax Aware LSTM Model for Chinese Semantic Role Labeling
As for semantic role labeling (SRL) task, when it comes to utilizing parsing information, both traditional methods and recent recurrent neural network (RNN) based methods use the feature engineering way. In this paper, w…
Chinese Semantic Role LabelingDependency ParsingFeature EngineeringSemantic Role LabelingHSGM: Hierarchical Segment-Graph Memory for Scalable Long-Text Semantics
Semantic parsing of long documents remains challenging due to quadratic growth in pairwise composition and memory requirements. We introduce \textbf{Hierarchical Segment-Graph Memory (HSGM)}, a novel framework that decom…
Semantic Role LabelingEvent ExtractionSemantic ParsingAMR ParsingSemantic Object Parsing with Graph LSTM
By taking the semantic object parsing task as an exemplar application scenario, we propose the Graph Long Short-Term Memory (Graph LSTM) network, which is the generalization of LSTM from sequential data or multi-dimensio…
ObjectSuperpixels