Papers by Yumeng Ma

2 papers
GeoLaux: A Benchmark for Evaluating MLLMs’ Geometry Performance on Long-Step Problems Requiring Auxiliary Lines (2026.acl-long)

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Challenge: Existing benchmarks for Geometry problem solving lack fine-grained evaluation for long-step problems necessitating auxiliary line construction.
Approach: They present a fine-grained annotated dataset with long-step reasoning and auxiliary line construction that provides a detailed evaluation of 23 leading MLLMs.
Outcome: The proposed model performs significantly worse on long-step problems than short-step ones, with 18 models showing a performance drop of over 50%.
Synergizing Stylometrics with Semantics: Dual-Path Framework for LLM Detection and Attribution (2026.findings-acl)

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Challenge: Existing methods for identifying MGTs rely on statistical likelihood or deep embeddings.
Approach: They propose a framework that extracts model-specific stylistic fingerprints across lexical, syntactic, and structural dimensions.
Outcome: The proposed framework achieves a Macro-F1 score of 95.6% on the Wikipedia dataset.

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