Papers with task-specific designs
Towards Generative Aspect-Based Sentiment Analysis (2021.acl-short)
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| Challenge: | Existing work on Aspect-based sentiment analysis ignores the rich label semantics of ABSA. |
| Approach: | They propose to tackle various ABSA tasks in a unified generative framework . they propose to use annotation-style and extraction-style modeling to enable training . |
| Outcome: | The proposed framework achieves state-of-the-art on four ABSA tasks across multiple benchmark datasets. |
Mem2Seq: Effectively Incorporating Knowledge Bases into End-to-End Task-Oriented Dialog Systems (P18-1)
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| Challenge: | End-to-end task-oriented dialog systems often suffer from the challenge of incorporating knowledge bases. |
| Approach: | They propose a novel yet simple end-to-end differentiable model called memory-tosequence to address this issue. |
| Outcome: | The proposed model can be trained faster and achieve state-of-the-art performance on three different task-oriented dialog datasets. |
PRISM: Efficient Long-Range Reasoning With Short-Context LLMs (2025.emnlp-main)
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| Challenge: | Existing solutions to long-range language tasks require large compute budgets and complex task-specific design choices. |
| Approach: | They propose an in-context method that uses structured schemas to generate short-contemporary outputs. |
| Outcome: | a new in-context method outperforms baselines on diverse tasks with 4x shorter contexts . it scales down to tiny contexts without increasing costs or sacrificing quality . |