Papers by Kateryna Tymoshenko

2 papers
Cross-Pair Text Representations for Answer Sentence Selection (D18-1)

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Challenge: Existing approaches to textual entailment and question answering focus on intra-pair similarity . a simple lexical matching (marked with italics) is not enough to learn a model based on intrapair Qto-A similarities.
Approach: They propose to compute scalar products representing similarity between members of different pairs instead of using a single vector for each pair.
Outcome: The proposed approach outperforms more complex models based on neural networks.
Strong and Light Baseline Models for Fact-Checking Joint Inference (2021.findings-acl)

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Challenge: Automated fact checking is rapidly gaining attention of the NLP and AI communities.
Approach: They propose lightweight strong baselines for automated fact-checking systems . they propose to combine multiple pieces of evidence to verify a claim .
Outcome: The proposed methods outperform heavier models on the leaderboard with blind TEST set.

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