Papers with label annotation

2 papers
ER-Test: Evaluating Explanation Regularization Methods for Language Models (2022.findings-emnlp)

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Challenge: Explanation regularization (ER) aims to improve NLM generalization by pushing the NLM’s machine rationales to align with human rationale.
Approach: They propose a framework for evaluating ER models’ OOD generalization along three dimensions: unseen datasets, contrast set tests, and functional tests.
Outcome: The proposed framework evaluates ER models’ OOD generalization across unseen datasets, contrast set tests, and functional tests.
Don’t Reinvent the Wheel: Efficient Instruction-Following Text Embedding based on Guided Space Transformation (2025.acl-long)

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Challenge: Existing methods for text embedding require re-encoding the entire corpus for each instruction.
Approach: They propose a framework that generates dynamic text embeddings that adapt to user instructions, highlighting specific attributes of text.
Outcome: The proposed framework improves instruction-following text embedding quality over state-of-the-art methods while speeding up processing on large datasets.

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