Papers with multi-document tasks
Peek Across: Improving Multi-Document Modeling via Cross-Document Question-Answering (2023.acl-long)
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| Challenge: | Among recent NLP research, multi-document processing is gaining increasing attention due to the need to handle and process an increasing amount of textual data and available documents online. |
| Approach: | They propose to pre-train a generic multi-document model from a cross-document question answering pre-training objective by generating salient sentences from one document and challenging it to recover the sentence from which it was generated. |
| Outcome: | The proposed model outperforms zero-shot GPT-3.5 and GPT-4 in multiple document tasks and generates the correct answer and the salient sentence from a salient document. |
Extending Multi-Text Sentence Fusion Resources via Pyramid Annotations (2022.naacl-main)
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| Challenge: | Existing datasets for sentence fusion tasks are limited in size and scope . despite recent advances, cross-document tasks such as multi-document summarization have not progressed with the same pace. |
| Approach: | They propose to extend a sentence fusion dataset by almost four times its original size . they relabel the dataset and employ more data sources to improve model performance . |
| Outcome: | The proposed dataset triples the size of an earlier dataset and improves performance . it also includes more complex training instances better reflecting those found in "the wild" |
RefusalBench: Generative Evaluation of Selective Refusal in Grounded Language Models (2026.eacl-long)
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| Challenge: | Language models fail to selectively refuse to answer based on flawed context, study finds . current benchmarks fail to evaluate complex capabilities like selective refusal . |
| Approach: | They propose a framework that generates diagnostic test cases through controlled linguistic perturbation. |
| Outcome: | The proposed framework employs 176 perturbation strategies across six categories of uncertainty and three intensity levels. |