Papers with classification framework
Event Causality Identification via Generation of Important Context Words (2022.starsem-1)
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| Challenge: | Prior work focused on identifying causal relation between two event mentions . current models do not output important contexts for causal prediction of two mentions. |
| Approach: | They propose to use dependency path generation as a complementary task for ECI. |
| Outcome: | The proposed model can generate both causal relation and dependency path words from input sentences. |
TAP-DLND 1.0 : A Corpus for Document Level Novelty Detection (L18-1)
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| Challenge: | Detecting novelty of an entire document is an AI frontier problem . present state-of-the-art text matching techniques are unable to process such redundancy. |
| Approach: | They propose a document-level novelty detection resource that can be used to benchmark techniques . they crawl news documents across several domains and use it to find out whether they contain new information . |
| Outcome: | The proposed dataset is compared with a standard system for document novelty detection . the proposed system can detect elements that have not appeared before, or new or original . |
Major Entity Identification: A Generalizable Alternative to Coreference Resolution (2024.emnlp-main)
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| Challenge: | Prior work identified annotation differences as one of the main reasons for the limited generalization gap in coreference resolution models. |
| Approach: | They propose an alternative referential task where the target entities are assumed to be specified in the input and the task is limited to the frequent entities. |
| Outcome: | The proposed model generalizes well across domains on multiple datasets with supervised models and LLM-based few-shot prompting. |