Papers with ranking system

3 papers
Graph Pattern Entity Ranking Model for Knowledge Graph Completion (N19-1)

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Challenge: Knowledge graph embedding models are so called-black box and are hard to interpret.
Approach: They propose to use graph patterns to construct an entity ranking system for each graph pattern and evaluate them using a ranking system.
Outcome: The proposed model outperforms other state-of-the-art models on standard metrics such as HITS@n and MRR.
Open-source Large Language Models are Strong Zero-shot Query Likelihood Models for Document Ranking (2023.findings-emnlp)

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Challenge: Recent studies show that large language models (LLMs) rank documents based on the probability of generating the query given the content of a document.
Approach: They propose a ranking system that integrates LLMs with a hybrid zero-shot retriever.
Outcome: The proposed system shows exceptional ranking in both zero-shot and few-shot scenarios.
Localizing Malicious Outputs from CodeLLM (2025.findings-emnlp)

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Challenge: Using FreqRank, we localize malicious components in outputs for triggered inputs and their corresponding backdoor triggers.
Approach: They propose a mutation-based defense to localize malicious components in LLM outputs and their corresponding backdoor triggers.
Outcome: The proposed defense has an average attack success rate (ASR) of 86.6% and can localize the backdoor triggers in 98% of cases.

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