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Discourse Parsing On Instructional Dt Instr

Metrics

Standard Parseval (Full)

Standard Parseval (Nuclearity)

Standard Parseval (Relation)

Standard Parseval (Span)

Results

Performance results of various models on this benchmark

					Paper Title	Repository
Bottom-up (DeBERTa)	44.4	60.0	51.4	77.8	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Top-down (DeBERTa)	43.4	57.9	50.0	77.3	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Bottom-up (XLNet)	40.7	56.4	47.4	73.6	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Top-down (RoBERTa)	41.5	56.1	48.7	75.7	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Bottom-up (RoBERTa)	41.4	55.5	47.9	73.2	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Top-down (XLNet)	40.2	55.2	47.0	74.3	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Top-down (SpanBERT)	36.7	54.5	42.7	73.7	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Bottom-up (SpanBERT)	40.5	53.8	46.0	72.9	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Guz et al. (2020) (pretrained)	-	46.59	-	65.41	Unleashing the Power of Neural Discourse Parsers -- A Context and Structure Aware Approach Using Large Scale Pretraining	-
Bottom-up (BERT)	32.9	46.3	39.5	66.6	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Top-down (BERT)	30.9	44.6	37.6	65.3	A Simple and Strong Baseline for End-to-End Neural RST-style Discourse Parsing
Guz et al. (2020)	-	44.41	-	64.55	Unleashing the Power of Neural Discourse Parsers -- A Context and Structure Aware Approach Using Large Scale Pretraining	-

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Discourse Parsing On Instructional Dt Instr | SOTA | HyperAI