Papers with mining hard negatives

2 papers
Generating Contrastive Narratives Using the Brownian Bridge Process for Narrative Coherence Learning (2024.acl-long)

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Challenge: Existing methods for learning narrative coherence are coarse-grained and superficial . existing methods are inadequate for learning negative samples, which are irrelevant or repetitive .
Approach: They propose two strategies for mining hard negatives using the Brownian Bridge process . they evaluate the method on several tasks and show it is applicable to many applications .
Outcome: The proposed method proves that it is applicable to many applications.
On Synthetic Data Strategies for Domain-Specific Generative Retrieval (2025.acl-long)

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Challenge: Generative retrieval models can be used to generate ranked lists of potentially relevant document identifiers for a user query.
Approach: They propose a synthetic data generation strategy for a two-stage training framework that focuses on learning to decode document identifiers from queries and a strategy for mining hard negatives based on initial model's predictions.
Outcome: The proposed model can generate ranked lists of potentially relevant document identifiers for a user query and then refine ranking through preference learning.

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