Papers with METER

3 papers
DOPA METER – A Tool Suite for Metrical Document Profiling and Aggregation (2023.emnlp-demo)

Copied to clipboard

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)

Copied to clipboard

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)

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations