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Found 6 papers, 4 papers with code
Towards a Unified Language Model for Knowledge-Intensive Tasks Utilizing External Corpus
Through generative retrieval (GR) approach, language models can achieve superior retrieval performance by directly generating relevant document identifiers (DocIDs).
Generative Retrieval via Term Set Generation
On top of the term-set DocID, we propose a permutation-invariant decoding algorithm, with which the term set can be generated in any permutation yet will always lead to the corresponding document.
Pre-training to Match for Unified Low-shot Relation Extraction
Low-shot relation extraction~(RE) aims to recognize novel relations with very few or even no samples, which is critical in real scenario application.
Can Prompt Probe Pretrained Language Models? Understanding the Invisible Risks from a Causal View
Prompt-based probing has been widely used in evaluating the abilities of pretrained language models (PLMs).
Element Intervention for Open Relation Extraction
Open relation extraction aims to cluster relation instances referring to the same underlying relation, which is a critical step for general relation extraction.
From Bag of Sentences to Document: Distantly Supervised Relation Extraction via Machine Reading Comprehension
By re-organizing all sentences about an entity as a document and extracting relations via querying the document with relation-specific questions, the document-based DS paradigm can simultaneously encode and exploit all sentence-level, inter-sentence-level, and entity-level evidence.
Ranked #1 on
Relationship Extraction (Distant Supervised)
on NYT
