Papers by Longxuan Yu

2 papers
3R: Enhancing Sentence Representation Learning via Redundant Representation Reduction (2025.emnlp-main)

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Challenge: Existing approaches to improve sentence representations lack fine-grained guidance on reducing redundant information.
Approach: They propose a method that dynamically identifies redundant information from a dimensional perspective and trains the SRL model to redistribute semantics on different dimensions.
Outcome: The proposed method improves sentence representations on seven semantic text similarity benchmarks.
CausalEval: Towards Better Causal Reasoning in Language Models (2025.naacl-long)

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Challenge: Large language models (LLMs) have been used for a variety of tasks, including problem-solving, decision-making, and understanding of the world.
Approach: They propose a review of existing methods aimed at enhancing LMs for causal reasoning . they categorize existing methods as reasoning engines or as helpers providing knowledge or data to traditional methods .
Outcome: The proposed methods perform better than existing methods on a range of tasks.

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