Papers by Eric Robertson
Semantic Novelty Detection and Characterization in Factual Text Involving Named Entities (2022.emnlp-main)
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| Challenge: | Existing topic-based novelty detection methods do not perform semantic reasoning involving relations between named entities in text and their background knowledge. |
| Approach: | They propose a model to detect whether a text is novel or not . they propose to use a factual text to characterize novelty. |
| Outcome: | The proposed model outperforms 10 baselines by large margins on the novelty detection task. |
A Unified Evaluation Framework for Novelty Detection and Accommodation in NLP with an Instantiation in Authorship Attribution (2023.findings-acl)
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| Challenge: | State-of-the-art natural language processing models have been shown to achieve remarkable performance in ‘closed-world’ settings where all the labels in the evaluation set are known at training time. |
| Approach: | They propose a multi-stage task to evaluate a system's performance on pipelined novelty ‘detection’ and ‘accommodation’ tasks. |
| Outcome: | The proposed model performs poorly in ‘closed-world’ settings where all the labels in the evaluation set are known at training time. |
Semantic Novelty Detection in Natural Language Descriptions (2021.emnlp-main)
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Nianzu Ma, Alexander Politowicz, Sahisnu Mazumder, Jiahua Chen, Bing Liu, Eric Robertson, Scott Grigsby
| Challenge: | Existing novelty detection algorithms are coarse-grained, working at the document or topic level. |
| Approach: | They propose to use a fine-grained semantic novelty detection problem to solve a novel novel scene problem. |
| Outcome: | The proposed model outperforms baseline models on the proposed task by large margins. |