Papers with unified evaluation

2 papers
RECIPE-TKG: From Sparse History to Structured Reasoning for LLM-based Temporal Knowledge Graph Completion (2026.eacl-long)

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Challenge: Temporal Knowledge Graphs (TKGs) represent dynamic facts as timestamped relations between entities. Large Language Models (LLMs) have sparked interest in using pretrained generative models for TKG completion.
Approach: They propose a framework that allows for rule-based multi-hop sampling and contrastive fine-tuning to shape relational compatibility.
Outcome: Experiments show that RECIPE-TKG outperforms prior LLM-based methods across input regimes.
Leveraging Large Language Models for NLG Evaluation: Advances and Challenges (2024.emnlp-main)

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Challenge: introducing Large Language Models (LLMs) has opened new avenues for assessing generated content quality, e.g., coherence, creativity, and context relevance.
Approach: They propose a taxonomy for organizing existing LLM-based evaluation metrics and a structured framework to understand and compare them.
Outcome: The proposed taxonomy offers a framework to understand and compare LLM-based evaluation methods.

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