Papers with METER
DOPA METER – A Tool Suite for Metrical Document Profiling and Aggregation (2023.emnlp-demo)
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| Challenge: | Xiao et al., 2022) examines the behavior of written language in a metrical way. |
| Approach: | They propose a tool suite for the metrical investigation of written language that provides diagnostic means for its division into discourse categories, such as registers, genres, and style. |
| Outcome: | The proposed system provides means for scoring linguistic behavior at the lexical, syntactic and semantic dimension. |
Improving Personalized Explanation Generation through Visualization (2022.acl-long)
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| Challenge: | Existing explainable recommendation models generate repetitive sentences for different items or empty sentences with insufficient details. |
| Approach: | They propose a visual-enhanced approach to generate rating scores and text explanations using visualization generation and text–image matching discrimination. |
| Outcome: | The proposed approach improves both the text quality and the diversity and explainability of the generated explanations. |
METER: Evaluating Multi-Level Contextual Causal Reasoning in Large Language Models (2026.acl-long)
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| Challenge: | Existing benchmarks evaluate contextual causal reasoning in fragmented settings, failing to ensure context consistency or cover the full causal hierarchy. |
| Approach: | They use a unified context to benchmark large language models' contextual causal reasoning skills. |
| Outcome: | The proposed benchmarks show that LLMs are susceptible to distraction by irrelevant but factually correct information at lower level of causality. |